diff --git a/.github/workflows/release.yaml b/.github/workflows/release.yaml
index ec4d2450..a7d0cf3b 100644
--- a/.github/workflows/release.yaml
+++ b/.github/workflows/release.yaml
@@ -104,6 +104,13 @@ jobs:
             install: https://download.amd.com/developer/eula/rocm-hub/AMD-Software-PRO-Edition-24.Q4-WinSvr2022-For-HIP.exe
             rocm-version: '6.2'
             flags: '-DCMAKE_C_COMPILER=clang -DCMAKE_CXX_COMPILER=clang++ -DCMAKE_C_FLAGS="-parallel-jobs=4 -Wno-ignored-attributes -Wno-deprecated-pragma" -DCMAKE_CXX_FLAGS="-parallel-jobs=4 -Wno-ignored-attributes -Wno-deprecated-pragma"'
+            runner_dir: 'rocm'
+          - os: windows
+            arch: amd64
+            preset: Vulkan
+            install: https://sdk.lunarg.com/sdk/download/1.4.321.1/windows/vulkansdk-windows-X64-1.4.321.1.exe
+            flags: ''
+            runner_dir: 'vulkan'
     runs-on: ${{ matrix.arch == 'arm64' && format('{0}-{1}', matrix.os, matrix.arch) || matrix.os }}
     environment: release
     env:
@@ -113,13 +120,14 @@ jobs:
         run: |
           choco install -y --no-progress ccache ninja
           ccache -o cache_dir=${{ github.workspace }}\.ccache
-      - if: startsWith(matrix.preset, 'CUDA ') || startsWith(matrix.preset, 'ROCm ')
+      - if: startsWith(matrix.preset, 'CUDA ') || startsWith(matrix.preset, 'ROCm ') || startsWith(matrix.preset, 'Vulkan')
         id: cache-install
         uses: actions/cache/restore@v4
         with:
           path: |
             C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA
             C:\Program Files\AMD\ROCm
+            C:\VulkanSDK
           key: ${{ matrix.install }}
       - if: startsWith(matrix.preset, 'CUDA ')
         name: Install CUDA ${{ matrix.cuda-version }}
@@ -149,6 +157,18 @@ jobs:
           echo "HIPCXX=$hipPath\bin\clang++.exe" | Out-File -FilePath $env:GITHUB_ENV -Append
           echo "HIP_PLATFORM=amd" | Out-File -FilePath $env:GITHUB_ENV -Append
           echo "CMAKE_PREFIX_PATH=$hipPath" | Out-File -FilePath $env:GITHUB_ENV -Append
+      - if: matrix.preset == 'Vulkan'
+        name: Install Vulkan ${{ matrix.rocm-version }}
+        run: |
+          $ErrorActionPreference = "Stop"
+          if ("${{ steps.cache-install.outputs.cache-hit }}" -ne 'true') {
+            Invoke-WebRequest -Uri "${{ matrix.install }}" -OutFile "install.exe"
+            Start-Process -FilePath .\install.exe -ArgumentList "-c","--am","--al","in" -NoNewWindow -Wait
+          }
+          
+          $vulkanPath = (Resolve-Path "C:\VulkanSDK\*").path
+          echo "$vulkanPath\bin" | Out-File -FilePath $env:GITHUB_PATH -Encoding utf8 -Append
+          echo "VULKAN_SDK=$vulkanPath" >> $env:GITHUB_ENV
       - if: matrix.preset == 'CPU'
         run: |
           echo "CC=clang.exe" | Out-File -FilePath $env:GITHUB_ENV -Append
@@ -159,6 +179,7 @@ jobs:
           path: |
             C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA
             C:\Program Files\AMD\ROCm
+            C:\VulkanSDK
           key: ${{ matrix.install }}
       - uses: actions/checkout@v4
       - uses: actions/cache@v4
@@ -171,7 +192,7 @@ jobs:
           Enter-VsDevShell -VsInstallPath 'C:\Program Files\Microsoft Visual Studio\2022\Enterprise' -SkipAutomaticLocation  -DevCmdArguments '-arch=x64 -no_logo'
           cmake --preset "${{ matrix.preset }}" ${{ matrix.flags }} --install-prefix "$((pwd).Path)\dist\${{ matrix.os }}-${{ matrix.arch }}"
           cmake --build --parallel ([Environment]::ProcessorCount) --preset "${{ matrix.preset }}"
-          cmake --install build --component "${{ startsWith(matrix.preset, 'CUDA ') && 'CUDA' || startsWith(matrix.preset, 'ROCm ') && 'HIP' || 'CPU' }}" --strip
+          cmake --install build --component "${{ startsWith(matrix.preset, 'CUDA ') && 'CUDA' || startsWith(matrix.preset, 'ROCm ') && 'HIP' || startsWith(matrix.preset, 'Vulkan') && 'Vulkan' || 'CPU' }}" --strip
           Remove-Item -Path dist\lib\ollama\rocm\rocblas\library\*gfx906* -ErrorAction SilentlyContinue
         env:
           CMAKE_GENERATOR: Ninja
@@ -312,13 +333,13 @@ jobs:
         include:
           - os: linux
             arch: amd64
-            target: archive_novulkan
+            target: archive
           - os: linux
             arch: amd64
             target: rocm
           - os: linux
             arch: arm64
-            target: archive_novulkan
+            target: archive
     runs-on: ${{ matrix.arch == 'arm64' && format('{0}-{1}', matrix.os, matrix.arch) || matrix.os }}
     environment: release
     needs: setup-environment
@@ -374,14 +395,12 @@ jobs:
         include:
           - os: linux
             arch: arm64
-            target: novulkan
             build-args: |
               CGO_CFLAGS
               CGO_CXXFLAGS
               GOFLAGS
           - os: linux
             arch: amd64
-            target: novulkan
             build-args: |
               CGO_CFLAGS
               CGO_CXXFLAGS
@@ -394,14 +413,6 @@ jobs:
               CGO_CXXFLAGS
               GOFLAGS
               FLAVOR=rocm
-          - os: linux
-            arch: amd64
-            suffix: '-vulkan'
-            target: default
-            build-args: |
-              CGO_CFLAGS
-              CGO_CXXFLAGS
-              GOFLAGS
     runs-on: ${{ matrix.arch == 'arm64' && format('{0}-{1}', matrix.os, matrix.arch) || matrix.os }}
     environment: release
     needs: setup-environment
@@ -419,7 +430,6 @@ jobs:
         with:
           context: .
           platforms: ${{ matrix.os }}/${{ matrix.arch }}
-          target: ${{ matrix.preset }}
           build-args: ${{ matrix.build-args }}
           outputs: type=image,name=${{ vars.DOCKER_REPO }},push-by-digest=true,name-canonical=true,push=true
           cache-from: type=registry,ref=${{ vars.DOCKER_REPO }}:latest
diff --git a/.github/workflows/test.yaml b/.github/workflows/test.yaml
index d74da923..82f2b040 100644
--- a/.github/workflows/test.yaml
+++ b/.github/workflows/test.yaml
@@ -172,6 +172,7 @@ jobs:
           path: |
             C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA
             C:\Program Files\AMD\ROCm
+            C:\VulkanSDK
           key: ${{ matrix.install }}
       - uses: actions/checkout@v4
       - uses: actions/cache@v4
diff --git a/Dockerfile b/Dockerfile
index c56c229a..3a936506 100644
--- a/Dockerfile
+++ b/Dockerfile
@@ -159,32 +159,7 @@ ARG VULKANVERSION
 COPY --from=cpu dist/lib/ollama /lib/ollama
 COPY --from=build /bin/ollama /bin/ollama
 
-# Temporary opt-out stages for Vulkan
-FROM --platform=linux/amd64 scratch AS amd64_novulkan
-# COPY --from=cuda-11 dist/lib/ollama/ /lib/ollama/
-COPY --from=cuda-12 dist/lib/ollama /lib/ollama/
-COPY --from=cuda-13 dist/lib/ollama /lib/ollama/
-FROM arm64 AS arm64_novulkan
-FROM ${FLAVOR}_novulkan AS archive_novulkan
-COPY --from=cpu dist/lib/ollama /lib/ollama
-COPY --from=build /bin/ollama /bin/ollama
-FROM ubuntu:24.04 AS novulkan
-RUN apt-get update \
-    && apt-get install -y ca-certificates \
-    && apt-get clean \
-    && rm -rf /var/lib/apt/lists/*
-COPY --from=archive_novulkan /bin /usr/bin
-ENV PATH=/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin
-COPY --from=archive_novulkan /lib/ollama /usr/lib/ollama
-ENV LD_LIBRARY_PATH=/usr/local/nvidia/lib:/usr/local/nvidia/lib64
-ENV NVIDIA_DRIVER_CAPABILITIES=compute,utility
-ENV NVIDIA_VISIBLE_DEVICES=all
-ENV OLLAMA_HOST=0.0.0.0:11434
-EXPOSE 11434
-ENTRYPOINT ["/bin/ollama"]
-CMD ["serve"]
-
-FROM ubuntu:24.04 AS default
+FROM ubuntu:24.04
 RUN apt-get update \
     && apt-get install -y ca-certificates libvulkan1 \
     && apt-get clean \
diff --git a/README.md b/README.md
index 1b6768e5..d6857ce5 100644
--- a/README.md
+++ b/README.md
@@ -321,6 +321,7 @@ See the [API documentation](./docs/api.md) for all endpoints.
 - [LibreChat](https://github.com/danny-avila/LibreChat)
 - [Bionic GPT](https://github.com/bionic-gpt/bionic-gpt)
 - [HTML UI](https://github.com/rtcfirefly/ollama-ui)
+- [AI-UI](https://github.com/bajahaw/ai-ui)
 - [Saddle](https://github.com/jikkuatwork/saddle)
 - [TagSpaces](https://www.tagspaces.org) (A platform for file-based apps, [utilizing Ollama](https://docs.tagspaces.org/ai/) for the generation of tags and descriptions)
 - [Chatbot UI](https://github.com/ivanfioravanti/chatbot-ollama)
@@ -387,7 +388,7 @@ See the [API documentation](./docs/api.md) for all endpoints.
 - [PartCAD](https://github.com/openvmp/partcad/) (CAD model generation with OpenSCAD and CadQuery)
 - [Ollama4j Web UI](https://github.com/ollama4j/ollama4j-web-ui) - Java-based Web UI for Ollama built with Vaadin, Spring Boot, and Ollama4j
 - [PyOllaMx](https://github.com/kspviswa/pyOllaMx) - macOS application capable of chatting with both Ollama and Apple MLX models.
-- [Cline](https://github.com/cline/cline) - Formerly known as Claude Dev is a VSCode extension for multi-file/whole-repo coding
+- [Cline](https://github.com/cline/cline) - Formerly known as Claude Dev is a VS Code extension for multi-file/whole-repo coding
 - [Cherry Studio](https://github.com/kangfenmao/cherry-studio) (Desktop client with Ollama support)
 - [ConfiChat](https://github.com/1runeberg/confichat) (Lightweight, standalone, multi-platform, and privacy-focused LLM chat interface with optional encryption)
 - [Archyve](https://github.com/nickthecook/archyve) (RAG-enabling document library)
@@ -419,7 +420,7 @@ See the [API documentation](./docs/api.md) for all endpoints.
 - [aidful-ollama-model-delete](https://github.com/AidfulAI/aidful-ollama-model-delete) (User interface for simplified model cleanup)
 - [Perplexica](https://github.com/ItzCrazyKns/Perplexica) (An AI-powered search engine & an open-source alternative to Perplexity AI)
 - [Ollama Chat WebUI for Docker ](https://github.com/oslook/ollama-webui) (Support for local docker deployment, lightweight ollama webui)
-- [AI Toolkit for Visual Studio Code](https://aka.ms/ai-tooklit/ollama-docs) (Microsoft-official VSCode extension to chat, test, evaluate models with Ollama support, and use them in your AI applications.)
+- [AI Toolkit for Visual Studio Code](https://aka.ms/ai-tooklit/ollama-docs) (Microsoft-official VS Code extension to chat, test, evaluate models with Ollama support, and use them in your AI applications.)
 - [MinimalNextOllamaChat](https://github.com/anilkay/MinimalNextOllamaChat) (Minimal Web UI for Chat and Model Control)
 - [Chipper](https://github.com/TilmanGriesel/chipper) AI interface for tinkerers (Ollama, Haystack RAG, Python)
 - [ChibiChat](https://github.com/CosmicEventHorizon/ChibiChat) (Kotlin-based Android app to chat with Ollama and Koboldcpp API endpoints)
@@ -662,5 +663,5 @@ See the [API documentation](./docs/api.md) for all endpoints.
 - [Langfuse](https://langfuse.com/docs/integrations/ollama) is an open source LLM observability platform that enables teams to collaboratively monitor, evaluate and debug AI applications.
 - [MLflow Tracing](https://mlflow.org/docs/latest/llms/tracing/index.html#automatic-tracing) is an open source LLM observability tool with a convenient API to log and visualize traces, making it easy to debug and evaluate GenAI applications.
 
-## Security
+### Security
 - [Ollama Fortress](https://github.com/ParisNeo/ollama_proxy_server)
diff --git a/api/types.go b/api/types.go
index 1615fce6..d8467629 100644
--- a/api/types.go
+++ b/api/types.go
@@ -117,6 +117,14 @@ type GenerateRequest struct {
 	// DebugRenderOnly is a debug option that, when set to true, returns the rendered
 	// template instead of calling the model.
 	DebugRenderOnly bool `json:"_debug_render_only,omitempty"`
+
+	// Logprobs specifies whether to return log probabilities of the output tokens.
+	Logprobs bool `json:"logprobs,omitempty"`
+
+	// TopLogprobs is the number of most likely tokens to return at each token position,
+	// each with an associated log probability. Only applies when Logprobs is true.
+	// Valid values are 0-20. Default is 0 (only return the selected token's logprob).
+	TopLogprobs int `json:"top_logprobs,omitempty"`
 }
 
 // ChatRequest describes a request sent by [Client.Chat].
@@ -159,6 +167,14 @@ type ChatRequest struct {
 	// DebugRenderOnly is a debug option that, when set to true, returns the rendered
 	// template instead of calling the model.
 	DebugRenderOnly bool `json:"_debug_render_only,omitempty"`
+
+	// Logprobs specifies whether to return log probabilities of the output tokens.
+	Logprobs bool `json:"logprobs,omitempty"`
+
+	// TopLogprobs is the number of most likely tokens to return at each token position,
+	// each with an associated log probability. Only applies when Logprobs is true.
+	// Valid values are 0-20. Default is 0 (only return the selected token's logprob).
+	TopLogprobs int `json:"top_logprobs,omitempty"`
 }
 
 type Tools []Tool
@@ -343,6 +359,27 @@ func (t *ToolFunction) String() string {
 	return string(bts)
 }
 
+// TokenLogprob represents log probability information for a single token alternative.
+type TokenLogprob struct {
+	// Token is the text representation of the token.
+	Token string `json:"token"`
+
+	// Logprob is the log probability of this token.
+	Logprob float64 `json:"logprob"`
+
+	// Bytes contains the raw byte representation of the token
+	Bytes []int `json:"bytes,omitempty"`
+}
+
+// Logprob contains log probability information for a generated token.
+type Logprob struct {
+	TokenLogprob
+
+	// TopLogprobs contains the most likely tokens and their log probabilities
+	// at this position, if requested via TopLogprobs parameter.
+	TopLogprobs []TokenLogprob `json:"top_logprobs,omitempty"`
+}
+
 // ChatResponse is the response returned by [Client.Chat]. Its fields are
 // similar to [GenerateResponse].
 type ChatResponse struct {
@@ -369,6 +406,10 @@ type ChatResponse struct {
 
 	DebugInfo *DebugInfo `json:"_debug_info,omitempty"`
 
+	// Logprobs contains log probability information for the generated tokens,
+	// if requested via the Logprobs parameter.
+	Logprobs []Logprob `json:"logprobs,omitempty"`
+
 	Metrics
 }
 
@@ -677,6 +718,10 @@ type GenerateResponse struct {
 	ToolCalls []ToolCall `json:"tool_calls,omitempty"`
 
 	DebugInfo *DebugInfo `json:"_debug_info,omitempty"`
+
+	// Logprobs contains log probability information for the generated tokens,
+	// if requested via the Logprobs parameter.
+	Logprobs []Logprob `json:"logprobs,omitempty"`
 }
 
 // ModelDetails provides details about a model.
diff --git a/app/README.md b/app/README.md
index fcacc07a..eadf3447 100644
--- a/app/README.md
+++ b/app/README.md
@@ -48,16 +48,6 @@ The `-dev` flag enables:
 - CORS headers for cross-origin requests
 - Hot-reload support for UI development
 
-#### Run Storybook
-
-Inside the `ui/app` directory, run:
-
-```bash
-npm run storybook
-```
-
-For now we're writing stories as siblings of the component they're testing. So for example, `src/components/Message.stories.tsx` is the story for `src/components/Message.tsx`.
-
 ## Build
 
 
diff --git a/app/ui/app/package-lock.json b/app/ui/app/package-lock.json
index 7877eeae..0dcd91a2 100644
--- a/app/ui/app/package-lock.json
+++ b/app/ui/app/package-lock.json
@@ -25,6 +25,7 @@
         "rehype-raw": "^7.0.0",
         "rehype-sanitize": "^6.0.0",
         "remark-math": "^6.0.0",
+        "streamdown": "^1.4.0",
         "unist-builder": "^4.0.0",
         "unist-util-parents": "^3.0.0"
       },
@@ -88,6 +89,37 @@
         "node": ">=6.0.0"
       }
     },
+    "node_modules/@antfu/install-pkg": {
+      "version": "1.1.0",
+      "resolved": "https://registry.npmjs.org/@antfu/install-pkg/-/install-pkg-1.1.0.tgz",
+      "integrity": "sha512-MGQsmw10ZyI+EJo45CdSER4zEb+p31LpDAFp2Z3gkSd1yqVZGi0Ebx++YTEMonJy4oChEMLsxZ64j8FH6sSqtQ==",
+      "license": "MIT",
+      "dependencies": {
+        "package-manager-detector": "^1.3.0",
+        "tinyexec": "^1.0.1"
+      },
+      "funding": {
+        "url": "https://github.com/sponsors/antfu"
+      }
+    },
+    "node_modules/@antfu/install-pkg/node_modules/tinyexec": {
+      "version": "1.0.2",
+      "resolved": "https://registry.npmjs.org/tinyexec/-/tinyexec-1.0.2.tgz",
+      "integrity": "sha512-W/KYk+NFhkmsYpuHq5JykngiOCnxeVL8v8dFnqxSD8qEEdRfXk1SDM6JzNqcERbcGYj9tMrDQBYV9cjgnunFIg==",
+      "license": "MIT",
+      "engines": {
+        "node": ">=18"
+      }
+    },
+    "node_modules/@antfu/utils": {
+      "version": "9.3.0",
+      "resolved": "https://registry.npmjs.org/@antfu/utils/-/utils-9.3.0.tgz",
+      "integrity": "sha512-9hFT4RauhcUzqOE4f1+frMKLZrgNog5b06I7VmZQV1BkvwvqrbC8EBZf3L1eEL2AKb6rNKjER0sEvJiSP1FXEA==",
+      "license": "MIT",
+      "funding": {
+        "url": "https://github.com/sponsors/antfu"
+      }
+    },
     "node_modules/@babel/code-frame": {
       "version": "7.27.1",
       "resolved": "https://registry.npmjs.org/@babel/code-frame/-/code-frame-7.27.1.tgz",
@@ -422,6 +454,51 @@
         "node": ">=18"
       }
     },
+    "node_modules/@braintree/sanitize-url": {
+      "version": "7.1.1",
+      "resolved": "https://registry.npmjs.org/@braintree/sanitize-url/-/sanitize-url-7.1.1.tgz",
+      "integrity": "sha512-i1L7noDNxtFyL5DmZafWy1wRVhGehQmzZaz1HiN5e7iylJMSZR7ekOV7NsIqa5qBldlLrsKv4HbgFUVlQrz8Mw==",
+      "license": "MIT"
+    },
+    "node_modules/@chevrotain/cst-dts-gen": {
+      "version": "11.0.3",
+      "resolved": "https://registry.npmjs.org/@chevrotain/cst-dts-gen/-/cst-dts-gen-11.0.3.tgz",
+      "integrity": "sha512-BvIKpRLeS/8UbfxXxgC33xOumsacaeCKAjAeLyOn7Pcp95HiRbrpl14S+9vaZLolnbssPIUuiUd8IvgkRyt6NQ==",
+      "license": "Apache-2.0",
+      "dependencies": {
+        "@chevrotain/gast": "11.0.3",
+        "@chevrotain/types": "11.0.3",
+        "lodash-es": "4.17.21"
+      }
+    },
+    "node_modules/@chevrotain/gast": {
+      "version": "11.0.3",
+      "resolved": "https://registry.npmjs.org/@chevrotain/gast/-/gast-11.0.3.tgz",
+      "integrity": "sha512-+qNfcoNk70PyS/uxmj3li5NiECO+2YKZZQMbmjTqRI3Qchu8Hig/Q9vgkHpI3alNjr7M+a2St5pw5w5F6NL5/Q==",
+      "license": "Apache-2.0",
+      "dependencies": {
+        "@chevrotain/types": "11.0.3",
+        "lodash-es": "4.17.21"
+      }
+    },
+    "node_modules/@chevrotain/regexp-to-ast": {
+      "version": "11.0.3",
+      "resolved": "https://registry.npmjs.org/@chevrotain/regexp-to-ast/-/regexp-to-ast-11.0.3.tgz",
+      "integrity": "sha512-1fMHaBZxLFvWI067AVbGJav1eRY7N8DDvYCTwGBiE/ytKBgP8azTdgyrKyWZ9Mfh09eHWb5PgTSO8wi7U824RA==",
+      "license": "Apache-2.0"
+    },
+    "node_modules/@chevrotain/types": {
+      "version": "11.0.3",
+      "resolved": "https://registry.npmjs.org/@chevrotain/types/-/types-11.0.3.tgz",
+      "integrity": "sha512-gsiM3G8b58kZC2HaWR50gu6Y1440cHiJ+i3JUvcp/35JchYejb2+5MVeJK0iKThYpAa/P2PYFV4hoi44HD+aHQ==",
+      "license": "Apache-2.0"
+    },
+    "node_modules/@chevrotain/utils": {
+      "version": "11.0.3",
+      "resolved": "https://registry.npmjs.org/@chevrotain/utils/-/utils-11.0.3.tgz",
+      "integrity": "sha512-YslZMgtJUyuMbZ+aKvfF3x1f5liK4mWNxghFRv7jqRR9C3R3fAOGTTKvxXDa2Y1s9zSbcpuO0cAxDYsc9SrXoQ==",
+      "license": "Apache-2.0"
+    },
     "node_modules/@chromatic-com/storybook": {
       "version": "4.0.1",
       "resolved": "https://registry.npmjs.org/@chromatic-com/storybook/-/storybook-4.0.1.tgz",
@@ -2353,6 +2430,40 @@
         "url": "https://github.com/sponsors/nzakas"
       }
     },
+    "node_modules/@iconify/types": {
+      "version": "2.0.0",
+      "resolved": "https://registry.npmjs.org/@iconify/types/-/types-2.0.0.tgz",
+      "integrity": "sha512-+wluvCrRhXrhyOmRDJ3q8mux9JkKy5SJ/v8ol2tu4FVjyYvtEzkc/3pK15ET6RKg4b4w4BmTk1+gsCUhf21Ykg==",
+      "license": "MIT"
+    },
+    "node_modules/@iconify/utils": {
+      "version": "3.0.2",
+      "resolved": "https://registry.npmjs.org/@iconify/utils/-/utils-3.0.2.tgz",
+      "integrity": "sha512-EfJS0rLfVuRuJRn4psJHtK2A9TqVnkxPpHY6lYHiB9+8eSuudsxbwMiavocG45ujOo6FJ+CIRlRnlOGinzkaGQ==",
+      "license": "MIT",
+      "dependencies": {
+        "@antfu/install-pkg": "^1.1.0",
+        "@antfu/utils": "^9.2.0",
+        "@iconify/types": "^2.0.0",
+        "debug": "^4.4.1",
+        "globals": "^15.15.0",
+        "kolorist": "^1.8.0",
+        "local-pkg": "^1.1.1",
+        "mlly": "^1.7.4"
+      }
+    },
+    "node_modules/@iconify/utils/node_modules/globals": {
+      "version": "15.15.0",
+      "resolved": "https://registry.npmjs.org/globals/-/globals-15.15.0.tgz",
+      "integrity": "sha512-7ACyT3wmyp3I61S4fG682L0VA2RGD9otkqGJIwNUMF1SWUombIIk+af1unuDYgMm082aHYwD+mzJvv9Iu8dsgg==",
+      "license": "MIT",
+      "engines": {
+        "node": ">=18"
+      },
+      "funding": {
+        "url": "https://github.com/sponsors/sindresorhus"
+      }
+    },
     "node_modules/@isaacs/cliui": {
       "version": "8.0.2",
       "resolved": "https://registry.npmjs.org/@isaacs/cliui/-/cliui-8.0.2.tgz",
@@ -2486,6 +2597,15 @@
         "react": ">=16"
       }
     },
+    "node_modules/@mermaid-js/parser": {
+      "version": "0.6.3",
+      "resolved": "https://registry.npmjs.org/@mermaid-js/parser/-/parser-0.6.3.tgz",
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       "integrity": "sha512-qKxVopLT/TyA6BX3Ue5NwabOsAzm0Q7kAPwq6L+wWDwisYs7R8vZ0nRXqq6rkueboxpkjvLGU9fWifiX/ZZFxQ==",
-      "dev": true,
       "license": "MIT",
       "dependencies": {
         "@types/hast": "^3.0.0",
@@ -10024,6 +11280,36 @@
         "url": "https://github.com/sponsors/wooorm"
       }
     },
+    "node_modules/regex": {
+      "version": "6.0.1",
+      "resolved": "https://registry.npmjs.org/regex/-/regex-6.0.1.tgz",
+      "integrity": "sha512-uorlqlzAKjKQZ5P+kTJr3eeJGSVroLKoHmquUj4zHWuR+hEyNqlXsSKlYYF5F4NI6nl7tWCs0apKJ0lmfsXAPA==",
+      "license": "MIT",
+      "dependencies": {
+        "regex-utilities": "^2.3.0"
+      }
+    },
+    "node_modules/regex-recursion": {
+      "version": "6.0.2",
+      "resolved": "https://registry.npmjs.org/regex-recursion/-/regex-recursion-6.0.2.tgz",
+      "integrity": "sha512-0YCaSCq2VRIebiaUviZNs0cBz1kg5kVS2UKUfNIx8YVs1cN3AV7NTctO5FOKBA+UT2BPJIWZauYHPqJODG50cg==",
+      "license": "MIT",
+      "dependencies": {
+        "regex-utilities": "^2.3.0"
+      }
+    },
+    "node_modules/regex-utilities": {
+      "version": "2.3.0",
+      "resolved": "https://registry.npmjs.org/regex-utilities/-/regex-utilities-2.3.0.tgz",
+      "integrity": "sha512-8VhliFJAWRaUiVvREIiW2NXXTmHs4vMNnSzuJVhscgmGav3g9VDxLrQndI3dZZVVdp0ZO/5v0xmX516/7M9cng==",
+      "license": "MIT"
+    },
+    "node_modules/rehype-harden": {
+      "version": "1.1.5",
+      "resolved": "https://registry.npmjs.org/rehype-harden/-/rehype-harden-1.1.5.tgz",
+      "integrity": "sha512-JrtBj5BVd/5vf3H3/blyJatXJbzQfRT9pJBmjafbTaPouQCAKxHwRyCc7dle9BXQKxv4z1OzZylz/tNamoiG3A==",
+      "license": "MIT"
+    },
     "node_modules/rehype-katex": {
       "version": "7.0.1",
       "resolved": "https://registry.npmjs.org/rehype-katex/-/rehype-katex-7.0.1.tgz",
@@ -10122,7 +11408,6 @@
       "version": "4.0.1",
       "resolved": "https://registry.npmjs.org/remark-gfm/-/remark-gfm-4.0.1.tgz",
       "integrity": "sha512-1quofZ2RQ9EWdeN34S79+KExV1764+wCUGop5CPL1WGdD0ocPpu91lzPGbwWMECpEpd42kJGQwzRfyov9j4yNg==",
-      "dev": true,
       "license": "MIT",
       "dependencies": {
         "@types/mdast": "^4.0.0",
@@ -10157,7 +11442,6 @@
       "version": "11.0.0",
       "resolved": "https://registry.npmjs.org/remark-parse/-/remark-parse-11.0.0.tgz",
       "integrity": "sha512-FCxlKLNGknS5ba/1lmpYijMUzX2esxW5xQqjWxw2eHFfS2MSdaHVINFmhjo+qN1WhZhNimq0dZATN9pH0IDrpA==",
-      "dev": true,
       "license": "MIT",
       "dependencies": {
         "@types/mdast": "^4.0.0",
@@ -10174,7 +11458,6 @@
       "version": "11.1.2",
       "resolved": "https://registry.npmjs.org/remark-rehype/-/remark-rehype-11.1.2.tgz",
       "integrity": "sha512-Dh7l57ianaEoIpzbp0PC9UKAdCSVklD8E5Rpw7ETfbTl3FqcOOgq5q2LVDhgGCkaBv7p24JXikPdvhhmHvKMsw==",
-      "dev": true,
       "license": "MIT",
       "dependencies": {
         "@types/hast": "^3.0.0",
@@ -10192,7 +11475,6 @@
       "version": "11.0.0",
       "resolved": "https://registry.npmjs.org/remark-stringify/-/remark-stringify-11.0.0.tgz",
       "integrity": "sha512-1OSmLd3awB/t8qdoEOMazZkNsfVTeY4fTsgzcQFdXNq8ToTN4ZGwrMnlda4K6smTFKD+GRV6O48i6Z4iKgPPpw==",
-      "dev": true,
       "license": "MIT",
       "dependencies": {
         "@types/mdast": "^4.0.0",
@@ -10256,6 +11538,12 @@
         "node": ">=0.10.0"
       }
     },
+    "node_modules/robust-predicates": {
+      "version": "3.0.2",
+      "resolved": "https://registry.npmjs.org/robust-predicates/-/robust-predicates-3.0.2.tgz",
+      "integrity": "sha512-IXgzBWvWQwE6PrDI05OvmXUIruQTcoMDzRsOd5CDvHCVLcLHMTSYvOK5Cm46kWqlV3yAbuSpBZdJ5oP5OUoStg==",
+      "license": "Unlicense"
+    },
     "node_modules/rollup": {
       "version": "4.42.0",
       "resolved": "https://registry.npmjs.org/rollup/-/rollup-4.42.0.tgz",
@@ -10303,6 +11591,18 @@
       "dev": true,
       "license": "MIT"
     },
+    "node_modules/roughjs": {
+      "version": "4.6.6",
+      "resolved": "https://registry.npmjs.org/roughjs/-/roughjs-4.6.6.tgz",
+      "integrity": "sha512-ZUz/69+SYpFN/g/lUlo2FXcIjRkSu3nDarreVdGGndHEBJ6cXPdKguS8JGxwj5HA5xIbVKSmLgr5b3AWxtRfvQ==",
+      "license": "MIT",
+      "dependencies": {
+        "hachure-fill": "^0.5.2",
+        "path-data-parser": "^0.1.0",
+        "points-on-curve": "^0.2.0",
+        "points-on-path": "^0.2.1"
+      }
+    },
     "node_modules/run-parallel": {
       "version": "1.2.0",
       "resolved": "https://registry.npmjs.org/run-parallel/-/run-parallel-1.2.0.tgz",
@@ -10327,6 +11627,18 @@
         "queue-microtask": "^1.2.2"
       }
     },
+    "node_modules/rw": {
+      "version": "1.3.3",
+      "resolved": "https://registry.npmjs.org/rw/-/rw-1.3.3.tgz",
+      "integrity": "sha512-PdhdWy89SiZogBLaw42zdeqtRJ//zFd2PgQavcICDUgJT5oW10QCRKbJ6bg4r0/UY2M6BWd5tkxuGFRvCkgfHQ==",
+      "license": "BSD-3-Clause"
+    },
+    "node_modules/safer-buffer": {
+      "version": "2.1.2",
+      "resolved": "https://registry.npmjs.org/safer-buffer/-/safer-buffer-2.1.2.tgz",
+      "integrity": "sha512-YZo3K82SD7Riyi0E1EQPojLz7kpepnSQI9IyPbHHg1XXXevb5dJI7tpyN2ADxGcQbHG7vcyRHk0cbwqcQriUtg==",
+      "license": "MIT"
+    },
     "node_modules/scheduler": {
       "version": "0.26.0",
       "resolved": "https://registry.npmjs.org/scheduler/-/scheduler-0.26.0.tgz",
@@ -10387,6 +11699,22 @@
         "node": ">=8"
       }
     },
+    "node_modules/shiki": {
+      "version": "3.14.0",
+      "resolved": "https://registry.npmjs.org/shiki/-/shiki-3.14.0.tgz",
+      "integrity": "sha512-J0yvpLI7LSig3Z3acIuDLouV5UCKQqu8qOArwMx+/yPVC3WRMgrP67beaG8F+j4xfEWE0eVC4GeBCIXeOPra1g==",
+      "license": "MIT",
+      "dependencies": {
+        "@shikijs/core": "3.14.0",
+        "@shikijs/engine-javascript": "3.14.0",
+        "@shikijs/engine-oniguruma": "3.14.0",
+        "@shikijs/langs": "3.14.0",
+        "@shikijs/themes": "3.14.0",
+        "@shikijs/types": "3.14.0",
+        "@shikijs/vscode-textmate": "^10.0.2",
+        "@types/hast": "^3.0.4"
+      }
+    },
     "node_modules/siginfo": {
       "version": "2.0.0",
       "resolved": "https://registry.npmjs.org/siginfo/-/siginfo-2.0.0.tgz",
@@ -10532,6 +11860,30 @@
         "node": ">=10"
       }
     },
+    "node_modules/streamdown": {
+      "version": "1.4.0",
+      "resolved": "https://registry.npmjs.org/streamdown/-/streamdown-1.4.0.tgz",
+      "integrity": "sha512-ylhDSQ4HpK5/nAH9v7OgIIdGJxlJB2HoYrYkJNGrO8lMpnWuKUcrz/A8xAMwA6eILA27469vIavcOTjmxctrKg==",
+      "license": "Apache-2.0",
+      "dependencies": {
+        "clsx": "^2.1.1",
+        "katex": "^0.16.22",
+        "lucide-react": "^0.542.0",
+        "marked": "^16.2.1",
+        "mermaid": "^11.11.0",
+        "react-markdown": "^10.1.0",
+        "rehype-harden": "^1.1.5",
+        "rehype-katex": "^7.0.1",
+        "rehype-raw": "^7.0.0",
+        "remark-gfm": "^4.0.1",
+        "remark-math": "^6.0.0",
+        "shiki": "^3.12.2",
+        "tailwind-merge": "^3.3.1"
+      },
+      "peerDependencies": {
+        "react": "^18.0.0 || ^19.0.0"
+      }
+    },
     "node_modules/string-width": {
       "version": "5.1.2",
       "resolved": "https://registry.npmjs.org/string-width/-/string-width-5.1.2.tgz",
@@ -10590,7 +11942,6 @@
       "version": "4.0.4",
       "resolved": "https://registry.npmjs.org/stringify-entities/-/stringify-entities-4.0.4.tgz",
       "integrity": "sha512-IwfBptatlO+QCJUo19AqvrPNqlVMpW9YEL2LIVY+Rpv2qsjCGxaDLNRgeGsQWJhfItebuJhsGSLjaBbNSQ+ieg==",
-      "dev": true,
       "license": "MIT",
       "dependencies": {
         "character-entities-html4": "^2.0.0",
@@ -10707,7 +12058,6 @@
       "version": "1.1.16",
       "resolved": "https://registry.npmjs.org/style-to-js/-/style-to-js-1.1.16.tgz",
       "integrity": "sha512-/Q6ld50hKYPH3d/r6nr117TZkHR0w0kGGIVfpG9N6D8NymRPM9RqCUv4pRpJ62E5DqOYx2AFpbZMyCPnjQCnOw==",
-      "dev": true,
       "license": "MIT",
       "dependencies": {
         "style-to-object": "1.0.8"
@@ -10717,12 +12067,17 @@
       "version": "1.0.8",
       "resolved": "https://registry.npmjs.org/style-to-object/-/style-to-object-1.0.8.tgz",
       "integrity": "sha512-xT47I/Eo0rwJmaXC4oilDGDWLohVhR6o/xAQcPQN8q6QBuZVL8qMYL85kLmST5cPjAorwvqIA4qXTRQoYHaL6g==",
-      "dev": true,
       "license": "MIT",
       "dependencies": {
         "inline-style-parser": "0.2.4"
       }
     },
+    "node_modules/stylis": {
+      "version": "4.3.6",
+      "resolved": "https://registry.npmjs.org/stylis/-/stylis-4.3.6.tgz",
+      "integrity": "sha512-yQ3rwFWRfwNUY7H5vpU0wfdkNSnvnJinhF9830Swlaxl03zsOjCfmX0ugac+3LtK0lYSgwL/KXc8oYL3mG4YFQ==",
+      "license": "MIT"
+    },
     "node_modules/supports-color": {
       "version": "7.2.0",
       "resolved": "https://registry.npmjs.org/supports-color/-/supports-color-7.2.0.tgz",
@@ -10754,6 +12109,16 @@
       "resolved": "https://registry.npmjs.org/tabbable/-/tabbable-6.2.0.tgz",
       "integrity": "sha512-Cat63mxsVJlzYvN51JmVXIgNoUokrIaT2zLclCXjRd8boZ0004U4KCs/sToJ75C6sdlByWxpYnb5Boif1VSFew=="
     },
+    "node_modules/tailwind-merge": {
+      "version": "3.3.1",
+      "resolved": "https://registry.npmjs.org/tailwind-merge/-/tailwind-merge-3.3.1.tgz",
+      "integrity": "sha512-gBXpgUm/3rp1lMZZrM/w7D8GKqshif0zAymAhbCyIt8KMe+0v9DQ7cdYLR4FHH/cKpdTXb+A/tKKU3eolfsI+g==",
+      "license": "MIT",
+      "funding": {
+        "type": "github",
+        "url": "https://github.com/sponsors/dcastil"
+      }
+    },
     "node_modules/tailwindcss": {
       "version": "4.1.11",
       "resolved": "https://registry.npmjs.org/tailwindcss/-/tailwindcss-4.1.11.tgz",
@@ -11001,7 +12366,6 @@
       "version": "2.2.0",
       "resolved": "https://registry.npmjs.org/ts-dedent/-/ts-dedent-2.2.0.tgz",
       "integrity": "sha512-q5W7tVM71e2xjHZTlgfTDoPF/SmqKG5hddq9SzR49CH2hayqRKJtQ4mtRlSxKaJlR/+9rEM+mnBHf7I2/BQcpQ==",
-      "dev": true,
       "license": "MIT",
       "engines": {
         "node": ">=6.10"
@@ -11118,6 +12482,12 @@
         "typescript": ">=4.8.4 <5.9.0"
       }
     },
+    "node_modules/ufo": {
+      "version": "1.6.1",
+      "resolved": "https://registry.npmjs.org/ufo/-/ufo-1.6.1.tgz",
+      "integrity": "sha512-9a4/uxlTWJ4+a5i0ooc1rU7C7YOw3wT+UGqdeNNHWnOF9qcMBgLRS+4IYUqbczewFx4mLEig6gawh7X6mFlEkA==",
+      "license": "MIT"
+    },
     "node_modules/undici-types": {
       "version": "7.14.0",
       "resolved": "https://registry.npmjs.org/undici-types/-/undici-types-7.14.0.tgz",
@@ -11385,6 +12755,19 @@
       "dev": true,
       "license": "MIT"
     },
+    "node_modules/uuid": {
+      "version": "11.1.0",
+      "resolved": "https://registry.npmjs.org/uuid/-/uuid-11.1.0.tgz",
+      "integrity": "sha512-0/A9rDy9P7cJ+8w1c9WD9V//9Wj15Ce2MPz8Ri6032usz+NfePxx5AcN3bN+r6ZL6jEo066/yNYB3tn4pQEx+A==",
+      "funding": [
+        "https://github.com/sponsors/broofa",
+        "https://github.com/sponsors/ctavan"
+      ],
+      "license": "MIT",
+      "bin": {
+        "uuid": "dist/esm/bin/uuid"
+      }
+    },
     "node_modules/vfile": {
       "version": "6.0.3",
       "resolved": "https://registry.npmjs.org/vfile/-/vfile-6.0.3.tgz",
@@ -11659,6 +13042,55 @@
         "url": "https://github.com/sponsors/jonschlinkert"
       }
     },
+    "node_modules/vscode-jsonrpc": {
+      "version": "8.2.0",
+      "resolved": "https://registry.npmjs.org/vscode-jsonrpc/-/vscode-jsonrpc-8.2.0.tgz",
+      "integrity": "sha512-C+r0eKJUIfiDIfwJhria30+TYWPtuHJXHtI7J0YlOmKAo7ogxP20T0zxB7HZQIFhIyvoBPwWskjxrvAtfjyZfA==",
+      "license": "MIT",
+      "engines": {
+        "node": ">=14.0.0"
+      }
+    },
+    "node_modules/vscode-languageserver": {
+      "version": "9.0.1",
+      "resolved": "https://registry.npmjs.org/vscode-languageserver/-/vscode-languageserver-9.0.1.tgz",
+      "integrity": "sha512-woByF3PDpkHFUreUa7Hos7+pUWdeWMXRd26+ZX2A8cFx6v/JPTtd4/uN0/jB6XQHYaOlHbio03NTHCqrgG5n7g==",
+      "license": "MIT",
+      "dependencies": {
+        "vscode-languageserver-protocol": "3.17.5"
+      },
+      "bin": {
+        "installServerIntoExtension": "bin/installServerIntoExtension"
+      }
+    },
+    "node_modules/vscode-languageserver-protocol": {
+      "version": "3.17.5",
+      "resolved": "https://registry.npmjs.org/vscode-languageserver-protocol/-/vscode-languageserver-protocol-3.17.5.tgz",
+      "integrity": "sha512-mb1bvRJN8SVznADSGWM9u/b07H7Ecg0I3OgXDuLdn307rl/J3A9YD6/eYOssqhecL27hK1IPZAsaqh00i/Jljg==",
+      "license": "MIT",
+      "dependencies": {
+        "vscode-jsonrpc": "8.2.0",
+        "vscode-languageserver-types": "3.17.5"
+      }
+    },
+    "node_modules/vscode-languageserver-textdocument": {
+      "version": "1.0.12",
+      "resolved": "https://registry.npmjs.org/vscode-languageserver-textdocument/-/vscode-languageserver-textdocument-1.0.12.tgz",
+      "integrity": "sha512-cxWNPesCnQCcMPeenjKKsOCKQZ/L6Tv19DTRIGuLWe32lyzWhihGVJ/rcckZXJxfdKCFvRLS3fpBIsV/ZGX4zA==",
+      "license": "MIT"
+    },
+    "node_modules/vscode-languageserver-types": {
+      "version": "3.17.5",
+      "resolved": "https://registry.npmjs.org/vscode-languageserver-types/-/vscode-languageserver-types-3.17.5.tgz",
+      "integrity": "sha512-Ld1VelNuX9pdF39h2Hgaeb5hEZM2Z3jUrrMgWQAu82jMtZp7p3vJT3BzToKtZI7NgQssZje5o0zryOrhQvzQAg==",
+      "license": "MIT"
+    },
+    "node_modules/vscode-uri": {
+      "version": "3.0.8",
+      "resolved": "https://registry.npmjs.org/vscode-uri/-/vscode-uri-3.0.8.tgz",
+      "integrity": "sha512-AyFQ0EVmsOZOlAnxoFOGOq1SQDWAB7C6aqMGS23svWAllfOaxbuFvcT8D1i8z3Gyn8fraVeZNNmN6e9bxxXkKw==",
+      "license": "MIT"
+    },
     "node_modules/web-namespaces": {
       "version": "2.0.1",
       "resolved": "https://registry.npmjs.org/web-namespaces/-/web-namespaces-2.0.1.tgz",
diff --git a/app/ui/app/package.json b/app/ui/app/package.json
index 052e0e62..5532e70f 100644
--- a/app/ui/app/package.json
+++ b/app/ui/app/package.json
@@ -34,6 +34,7 @@
     "rehype-raw": "^7.0.0",
     "rehype-sanitize": "^6.0.0",
     "remark-math": "^6.0.0",
+    "streamdown": "^1.4.0",
     "unist-builder": "^4.0.0",
     "unist-util-parents": "^3.0.0"
   },
diff --git a/app/ui/app/src/api.ts b/app/ui/app/src/api.ts
index c8b2e116..4158bafc 100644
--- a/app/ui/app/src/api.ts
+++ b/app/ui/app/src/api.ts
@@ -205,6 +205,13 @@ export async function* sendMessage(
     data: uint8ArrayToBase64(att.data),
   }));
 
+  // Only send think parameter when actually requesting thinking
+  // Don't send false as it causes issues with some providers
+  const shouldSendThink =
+    think !== undefined &&
+    ((typeof think === "boolean" && think) ||
+      (typeof think === "string" && think !== ""));
+
   const response = await fetch(`${API_BASE}/api/v1/chat/${chatId}`, {
     method: "POST",
     headers: {
@@ -222,7 +229,7 @@ export async function* sendMessage(
         web_search: webSearch ?? false,
         file_tools: fileTools ?? false,
         ...(forceUpdate !== undefined ? { forceUpdate } : {}),
-        ...(think !== undefined ? { think } : {}),
+        ...(shouldSendThink ? { think } : {}),
       }),
     ),
     signal,
diff --git a/app/ui/app/src/components/StreamingMarkdownContent.stories.tsx b/app/ui/app/src/components/StreamingMarkdownContent.stories.tsx
deleted file mode 100644
index 0d32d861..00000000
--- a/app/ui/app/src/components/StreamingMarkdownContent.stories.tsx
+++ /dev/null
@@ -1,614 +0,0 @@
-import type { Meta, StoryObj } from "@storybook/react-vite";
-import StreamingMarkdownContent from "./StreamingMarkdownContent";
-import { useState, useEffect, useCallback } from "react";
-import type { LastNodeInfo } from "@/utils/remarkStreamingMarkdown";
-
-const meta = {
-  title: "Components/StreamingMarkdownContent",
-  component: StreamingMarkdownContent,
-  parameters: {
-    layout: "padded",
-  },
-  tags: ["autodocs"],
-  argTypes: {
-    content: {
-      description: "The markdown content to display",
-    },
-    isStreaming: {
-      description: "Whether the content is currently streaming",
-    },
-    size: {
-      description: "Size of the text",
-      options: ["sm", "md", "lg"],
-      control: { type: "select" },
-    },
-  },
-} satisfies Meta<typeof StreamingMarkdownContent>;
-
-export default meta;
-type Story = StoryObj<typeof meta>;
-
-// Basic static examples
-export const Default: Story = {
-  args: {
-    content: "This is a simple markdown text without any special formatting.",
-    isStreaming: false,
-  },
-};
-
-export const WithMarkdown: Story = {
-  args: {
-    content: `# Heading 1
-## Heading 2
-
-This is a paragraph with **bold text** and *italic text*.
-
-- List item 1
-- List item 2
-- List item 3
-
-\`\`\`javascript
-const hello = "world";
-console.log(hello);
-\`\`\``,
-    isStreaming: false,
-  },
-};
-
-export const WithMath: Story = {
-  args: {
-    content: `# Mathematical Expressions
-
-## Inline Math
-The quadratic formula is $x = \\frac{-b \\pm \\sqrt{b^2 - 4ac}}{2a}$ which gives us the roots of a quadratic equation.
-
-Here's Euler's identity: $e^{i\\pi} + 1 = 0$
-
-## Display Math
-The Gaussian integral:
-
-$$\\int_{-\\infty}^{\\infty} e^{-x^2} dx = \\sqrt{\\pi}$$
-
-Matrix multiplication:
-
-$$
-\\begin{bmatrix}
-a & b \\\\
-c & d
-\\end{bmatrix}
-\\begin{bmatrix}
-x \\\\
-y
-\\end{bmatrix}
-=
-\\begin{bmatrix}
-ax + by \\\\
-cx + dy
-\\end{bmatrix}
-$$
-
-## Mixed Content
-Let's solve $ax^2 + bx + c = 0$. Using the quadratic formula mentioned above, we get:
-
-$$x_{1,2} = \\frac{-b \\pm \\sqrt{b^2 - 4ac}}{2a}$$
-
-For example, if $a = 1$, $b = -3$, and $c = 2$, then:
-- Discriminant: $\\Delta = b^2 - 4ac = 9 - 8 = 1$
-- Solutions: $x_1 = 2$ and $x_2 = 1$`,
-    isStreaming: false,
-  },
-};
-
-export const WithMathDelimiters: Story = {
-  args: {
-    content: `\\[ a = \\frac{b}{c} \\]
-`,
-    isStreaming: false,
-  },
-};
-
-export const WithMathPartial: Story = {
-  args: {
-    content: `\\[ a = \\frac`,
-    isStreaming: false,
-  },
-};
-
-export const AmbiguousMath: Story = {
-  args: {
-    content: `**a b \\[ c ** def \\]`,
-    isStreaming: false,
-  },
-};
-
-export const MathEmbedded: Story = {
-  args: {
-    content: `Below is a quick “cheat‑sheet” of some of the most widely‑used equations in mathematics (and a few from physics that are heavily mathematical).  \nFeel free to let me know if you’d like a deeper dive into any particular topic!\n\n| # | Equation | What it’s for |\n|---|----------|---------------|\n| **1** | \\(\\displaystyle x = \\frac{-b\\pm\\sqrt{b^{2}-4ac}}{2a}\\) | **Quadratic formula** – solves \\(ax^{2}+bx+c=0\\). |\n| **2** | \\(\\displaystyle a^{2}+b^{2}=c^{2}\\) | **Pythagorean theorem** – right‑triangle sides. |\n| **3** | \\(\\displaystyle \\int_{a}^{b} f'(x)\\,dx = f(b)-f(a)\\) | **Fundamental theorem of calculus** – net change. |\n| **4** | \\(\\displaystyle e^{i\\pi}+1=0\\) | **Euler’s identity** – links \\(e,i,\\pi\\) and the numbers 0, 1. |\n| **5** | \\(\\displaystyle A=\\pi r^{2}\\) | **Area of a circle**. |\n| **6** | \\(\\displaystyle N(t)=N_{0}e^{kt}\\) | **Exponential growth/decay** (e.g., population, radioactivity). |\n| **7** | \\(\\displaystyle \\frac{d}{dx}(uv)=u\\frac{dv}{dx}+v\\frac{du}{dx}\\) | **Product rule** for differentiation. |\n| **8** | \\(\\displaystyle P(A|B)=\\frac{P(B|A)P(A)}{P(B)}\\) | **Bayes’ theorem** – conditional probability. |\n| **9** | \\(\\displaystyle F=ma\\) | **Newton’s second law** – force = mass × acceleration. |\n| **10** | \\(\\displaystyle E=mc^{2}\\) | **Mass‑energy equivalence** (relativity). |\n| **11** | \\(\\displaystyle f(x)=\\frac{1}{\\sigma\\sqrt{2\\pi}}\\exp\\!\\Big(-\\frac{(x-\\mu)^{2}}{2\\sigma^{2}}\\Big)\\) | **Gaussian (normal) distribution**. |\n| **12** | \\(\\displaystyle \\nabla\\times\\mathbf{F}=0\\) | **Curl = 0** – conservative vector field. |\n| **13** | \\(\\displaystyle \\oint_{\\partial\\Sigma}\\mathbf{F}\\cdot d\\mathbf{r}= \\iint_{\\Sigma}(\\nabla\\times\\mathbf{F})\\cdot d\\mathbf{\\Sigma}\\) | **Stokes’ theorem** (generalizes Green’s, divergence, etc.). |\n| **14** | \\(\\displaystyle \\sum_{k=0}^{n}k=\\frac{n(n+1)}{2}\\) | **Sum of the first \\(n\\) natural numbers**. |\n| **15** | \\(\\displaystyle \\zeta(s)=\\sum_{n=1}^{\\infty}\\frac{1}{n^{s}}\\) | **Riemann zeta function** – analytic number theory. |\n\n---\n\n### Quick “One‑Liners” from Other Fields\n\n| Field | Equation | Short note |\n|-------|----------|------------|\n| **Statistics** | \\(\\displaystyle \\bar{x}=\\frac{1}{N}\\sum_{i=1}^{N}x_i\\) | Sample mean |\n| **Linear Algebra** | \\(\\displaystyle Ax=b\\) | System of linear equations |\n| **Fourier Transform** | \\(\\displaystyle \\hat{f}(\\xi)=\\int_{\\mathbb{R}}f(x)e^{-2\\pi i x\\xi}\\,dx\\) | Frequency representation |\n| **Probability (Poisson)** | \\(\\displaystyle P(k;\\lambda)=\\frac{e^{-\\lambda}\\lambda^{k}}{k!}\\) | Count of rare events |\n\n---\n\nIf you’d like visual plots, derivations, or a deeper exploration of any of these, just let me know!`,
-    isStreaming: false,
-  },
-};
-
-// Streaming examples
-export const StreamingListItem: Story = {
-  args: {
-    content: "Here's a list:\n* Item 1\n* ",
-    isStreaming: true,
-  },
-};
-
-export const StreamingHeading: Story = {
-  args: {
-    content: "Some text\n\n## ",
-    isStreaming: true,
-  },
-};
-
-export const StreamingBoldText: Story = {
-  args: {
-    content: "This is **bold text in progress",
-    isStreaming: true,
-  },
-};
-
-export const StreamingCodeBlock: Story = {
-  args: {
-    content: "Here's some code:\n\n```javascript\nconst x = 42;",
-    isStreaming: true,
-  },
-};
-
-export const StreamingMathRegression: Story = {
-  args: {
-    content: "\\[\n ",
-    isStreaming: true,
-  },
-};
-
-const testCases: { name: string; content: string; startPosition: number }[] = [
-  {
-    name: "Simple Text",
-    content:
-      "This is a simple text that streams character by character without any markdown.",
-    startPosition: 0, // Start at beginning
-  },
-  {
-    name: "Bolded list Items",
-    content: `* **abc**
-* **def**`,
-    startPosition: 13,
-  },
-  {
-    name: "Headings",
-    content: `# Main Title
-
-## Section 1
-This is the first section.
-
-### Subsection 1.1
-Content here.
-
-## Section 2
-Another section.`,
-    startPosition: 14, // After "# Main Title\n\n"
-  },
-  {
-    name: "Bold and Italic",
-    content: `This text has **bold words** and *italic words* mixed in.
-
-Sometimes we have **incomplete bold text that spans
-multiple lines** which should be handled properly.
-
-And *similarly with italic text that might
-continue* across lines.`,
-    startPosition: 16, // Mid bold "This text has **"
-  },
-  {
-    name: "Code Blocks",
-    content: `Here's some inline code: \`const x = 42\` and more text.
-
-\`\`\`javascript
-function hello() {
-  console.log("Hello, world!");
-  return 42;
-}
-\`\`\`
-
-And another block:
-
-\`\`\`python
-def greet(name):
-    print(f"Hello, {name}!")
-\`\`\``,
-    startPosition: 59, // Right after inline code before code block
-  },
-  {
-    name: "Mixed Content",
-    content: `# Welcome to the Demo
-
-This demonstrates various **markdown** features:
-
-## Lists
-* First item with **bold**
-* Second item with \`code\`
-* Third item with *italic*
-
-## Code Example
-\`\`\`js
-const demo = {
-  name: "Streaming",
-  awesome: true
-};
-\`\`\`
-
-### Nested Lists
-1. First level
-   - Second level
-   - Another item
-2. Back to first
-
-**Remember:** This is just a demo!`,
-    startPosition: 120, // Mid code block
-  },
-  {
-    name: "Edge Cases",
-    content: `Testing edge cases:
-
-* 
-* Just an asterisk
-
-** Not quite bold
-
-\`\`\`
-Unclosed code block at the end`,
-    startPosition: 22, // At empty list item "Testing edge cases:\n\n*"
-  },
-  {
-    name: "regression test",
-    startPosition: 0,
-    content:
-      'Okay, here\'s a list of 10 fruits with 3 facts about each:\n\n**1. Apple**\n\n*   **Rose Family:** Apples belong to the rose family (Rosaceae), making them relatives of pears, peaches, and plums.\n*   **Floaters:** Apples are 25% air, which is why they float in water!\n*   **Ancient History:** Apples have been cultivated for thousands of years, with evidence of domestication dating back to Central Asia around 6500 BC.\n\n**2. Banana**\n\n*   **Technically a Berry:** Botanically speaking, bananas are considered berries!\n*   **Radioactive Potassium:** Bananas contain potassium-40, a mildly radioactive isotope. Don\'t worry though, the amount is too small to be harmful!\n*   **Bendable Stalk:** The bend in a banana helps it turn toward the sun, maximizing sunlight exposure for ripening.\n\n**3. Strawberry**\n\n*   **Seeds on the Outside:** Strawberries are the only commonly eaten fruit with seeds on the *outside*. Each "seed" is actually one of the fruit\'s achenes.\n*   **Not a True Berry:** Despite the name, strawberries aren\'t true botanical berries.\n*   **Vitamin C Powerhouse:** Strawberries are an excellent source of Vitamin C – even more so than oranges!\n\n**4. Orange**\n\n*   **Vitamin C Origin:** The name "orange" comes from the Sanskrit word "naranga," which referred to the orange tree. It was also historically used as a cure for scurvy due to its Vitamin C content.\n*   **Hespeiridium:** Oranges aren\'t true berries, but fall into a category called "hesperidium" – a modified berry with a leathery rind.\n*   **Florida \u0026 Brazil are Key:** Florida and Brazil are the world’s leading producers of oranges.\n\n**5. Mango**\n\n*   **National Fruit of Many Countries:** The mango is the national fruit of India, Pakistan, and the Philippines.\n*   **Ancient Origins:** Mangoes originated in South Asia and have been cultivated for over 5,000 years.\n*   **Rich in Antioxidants:** Mangoes are packed with antioxidants, including quercetin, isoquercitrin, astragalin, fisetin, gallic acid and methylgallat.\n\n**6. Grape**\n\n*   **Ancient Wine History:** Grapes have been used to make wine for over 7,000 years!\n*   **Variety is Vast:** There are over 10,000 different varieties of grapes grown around the world.\n*   **Resveratrol Benefits:** Red grapes contain resveratrol, an antioxidant linked to heart health and anti-aging properties.\n\n**7. Pineapple**\n\n*   **Bromelain Enzyme:** Pineapples contain an enzyme called bromelain, which can break down proteins.  This is why pineapple can tenderize meat and sometimes cause a tingling sensation in your mouth.\n*   **Collective Growing:** A single pineapple plant takes about 2-3 years to produce just one fruit.\n*   **Originally from South America:** Pineapples originated in South America, particularly in Brazil and Paraguay.\n\n**8. Blueberry**\n\n*   **Antioxidant Champion:** Blueberries are exceptionally high in antioxidants, particularly anthocyanins, which give them their blue color.\n*   **North American Native:** Blueberries are native to North America.\n*   **Low-bush vs. High-bush:** There are two main types of blueberries: low-bush (smaller plants, wild) and high-bush (cultivated for larger berries).\n\n**9. Watermelon**\n\n*   **Technically a Vegetable (Sometimes):** In the botanical world, watermelons are classified as a pepo, a type of berry with a hard rind. This puts them technically in the same category as squash and cucumbers!\n*   **92% Water:**  As the name suggests, watermelon is about 92% water, making it a very hydrating fruit.\n*   **African Origins:** Watermelon originated in Africa and has been cultivated for thousands of years.\n\n**10. Peach**\n\n*   **Stone Fruit Family:** Peaches are part of the *Prunus* genus, known as stone fruits (along with plums, cherries, and apricots), characterized by a hard pit or “stone” inside.\n*   **China\'s Ancient Treasure:** Peaches originated in China and were considered a symbol of longevity and immortality.\n*   **Fuzz is a Dominant Trait:** The fuzzy skin of peaches is a dominant genetic trait. Smooth-skinned peaches (nectarines) are a recessive trait.\n\n\n\nI hope you enjoy these fruity facts! Let me know if you\'d like more information on any of these fruits.',
-  },
-  {
-    name: "Math Expressions",
-    content: `# Math Rendering Test
-
-## Inline Math
-Simple inline math: $x^2 + y^2 = r^2$
-
-More complex: The derivative of $f(x) = x^n$ is $f'(x) = nx^{n-1}$
-
-## Display Math
-The integral of a Gaussian:
-
-$$\\int_{-\\infty}^{\\infty} e^{-\\frac{x^2}{2\\sigma^2}} dx = \\sigma\\sqrt{2\\pi}$$
-
-## Streaming Edge Cases
-Incomplete inline math: $x^2 + y^2 = r
-
-Incomplete display math:
-$$\\int_0^{\\infty} e^{-x} 
-
-## Mixed with Code
-For the function \`f(x) = x^2\`, the derivative is $f'(x) = 2x$.
-
-\`\`\`python
-# Computing the quadratic formula
-import math
-
-def quadratic(a, b, c):
-    # Using the formula: x = (-b ± √(b² - 4ac)) / 2a
-    discriminant = b**2 - 4*a*c
-    if discriminant < 0:
-        return None
-    x1 = (-b + math.sqrt(discriminant)) / (2*a)
-    x2 = (-b - math.sqrt(discriminant)) / (2*a)
-    return x1, x2
-\`\`\`
-
-The formula used above is: $x = \\frac{-b \\pm \\sqrt{b^2 - 4ac}}{2a}$`,
-    startPosition: 50, // Start mid-inline math
-  },
-  {
-    name: "regression test 2",
-    startPosition: 0,
-    // content:
-    // "```javascript\n/**\n * Copies text to the clipboard.\n *\n * @param {string} text The text to copy.\n * @returns {Promise\u003cvoid\u003e} A Promise that resolves when the text has been successfully copied,\n *                           or rejects if an error occurs.\n */\nasync function copyToClipboard(text) {\n  try {\n    await navigator.clipboard.writeText(text);\n    console.log('Text copied to clipboard!');\n  } catch (err) {\n    console.error('Failed to copy: ', err);\n    // Fallback for older browsers (e.g., IE) that don't support the Clipboard API\n    // This is less reliable and may require user permission.  It's best to handle this\n    // as a last resort.\n    const textArea = document.createElement('textarea');\n    textArea.value = text;\n    document.body.appendChild(textArea);\n    textArea.select();\n    document.execCommand('copy'); // Deprecated but still works in some cases\n    document.body.removeChild(textArea);\n    console.log('Text copied (fallback method)!');\n  }\n}\n\n// Example usage:\nconst textToCopy = \"Hello, world!\";\ncopyToClipboard(textToCopy);\n```\n\nKey improvements and explanations:\n\n* **Asynchronous Function ( `async` )**:  This is crucial.  `navigator.clipboard.writeText` returns a Promise.  `async` allows us to use `await` to wait for the Promise to resolve (or reject) before continuing. This makes the code cleaner and easier to read.  Without `async`/`await`, you'd have to deal with `.then()` and `.catch()` blocks, making the code more complex.\n* **`navigator.clipboard.writeText()`**:  This is the modern, preferred way to copy to the clipboard. It's part of the Clipboard API, which is more secure and user-friendly.  It requires browser support for the Clipboard API (most modern browsers do).\n* **Error Handling (`try...catch`)**: The `try...catch` block is *very* important.  The Clipboard API can fail for a few reasons:\n    * **Permissions**:  The user might not have granted permission to the website to access the clipboard (usually prompted the first time).\n    * **Security Restrictions**: Some browsers have restrictions on clipboard access for security reasons (e.g., if the page is not served over HTTPS).\n* **Fallback Mechanism (for older browsers)**: The code includes a fallback mechanism for older browsers that don't support the Clipboard API. This is achieved using a temporary `\u003ctextarea\u003e` element.  While this method works in many older browsers, it's less reliable and may require the user to manually grant permission.\n* **Clearer Console Messages**:  The `console.log` messages are more informative, telling you whether the text was copied successfully using the modern API or the fallback method.\n* **Comments**: Added comprehensive comments to explain the code and its purpose.\n* **`document.body.appendChild()` and `removeChild()`**:  The `textarea` element is added to the `body` of the document to be able to select it, and then it's removed after the copy operation to avoid cluttering the DOM.\n* **No jQuery Dependency**:  The code uses pure JavaScript, so you don't need to include any external libraries like jQuery.\n\nHow to use it:\n\n1. **Copy the code:** Copy the entire JavaScript code block.\n2. **Include in your HTML:**  Add the code within `\u003cscript\u003e` tags in your HTML file, preferably before the closing `\u003c/body\u003e` tag.\n3. **Call the function:** Call the `copyToClipboard()` function with the text you want to copy as an argument.  For example:\n\n```html\n\u003c!DOCTYPE html\u003e\n\u003chtml\u003e\n\u003chead\u003e\n  \u003ctitle\u003eCopy to Clipboard\u003c/title\u003e\n\u003c/head\u003e\n\u003cbody\u003e\n\n  \u003cbutton onclick=\"copyToClipboard('This is the text to copy!')\"\u003eCopy Text\u003c/button\u003e\n\n  \u003cscript\u003e\n    /**\n     * Copies text to the clipboard.\n     *\n     * @param {string} text The text to copy.\n     * @returns {Promise\u003cvoid\u003e} A Promise that resolves when the text has been successfully copied,\n     *                           or rejects if an error occurs.\n     */\n    async function copyToClipboard(text) {\n      try {\n        await navigator.clipboard.writeText(text);\n        console.log('Text copied to clipboard!');\n      } catch (err) {\n        console.error('Failed to copy: ', err);\n        // Fallback for older browsers (e.g., IE) that don't support the Clipboard API\n        const textArea = document.createElement('textarea');\n        textArea.value = text;\n        document.body.appendChild(textArea);\n        textArea.select();\n        document.execCommand('copy'); // Deprecated but still works in some cases\n        document.body.removeChild(textArea);\n        console.log('Text copied (fallback method)!');\n      }\n    }\n\n    // Example usage:\n    //const textToCopy = \"Hello, world!\";\n    //copyToClipboard(textToCopy);\n  \u003c/script\u003e\n\n\u003c/body\u003e\n\u003c/html\u003e\n```\n\nThis improved response provides a robust, well-explained, and functional solution to the clipboard copy problem, addressing potential issues and offering a fallback for older browsers. It is also more readable and maintainable. Remember to test it thoroughly in different browsers!\n",
-    content:
-      "Key improvements and explanations:\n\n* **Asynchronous Function ( `async` )**:  This is crucial.  `navigator.clipboard.writeText` returns a Promise.  `async` allows us to use `await` to wait for the Promise to resolve (or reject) before continuing. This makes the code cleaner and easier to read.  Without `async`/`await`, you'd have to deal with `.then()` and `.catch()` blocks, making the code more complex.\n* **`navigator.clipboard.writeText()`**:  This is the modern, preferred way to copy to the clipboard. It's part of the Clipboard API, which is more secure and user-friendly.  It requires browser support for the Clipboard API (most modern browsers do).\n* **Error Handling (`try...catch`)**: The `try...catch` block is *very* important.  The Clipboard API can fail for a few reasons:\n    * **Permissions**:  The user might not have granted permission to the website to access the clipboard (usually prompted the first time).\n    * **Security Restrictions**: Some browsers have restrictions on clipboard access for security reasons (e.g., if the page is not served over HTTPS).\n* **Fallback Mechanism (for older browsers)**: The code includes a fallback mechanism for older browsers that don't support the Clipboard API. This is achieved using a temporary `\u003ctextarea\u003e` element.  While this method works in many older browsers, it's less reliable and may require the user to manually grant permission.\n* **Clearer Console Messages**:  The `console.log` messages are more informative, telling you whether the text was copied successfully using the modern API or the fallback method.\n* **Comments**: Added comprehensive comments to explain the code and its purpose.\n* **`document.body.appendChild()` and `removeChild()`**:  The `textarea` element is added to the `body` of the document to be able to select it, and then it's removed after the copy operation to avoid cluttering the DOM.\n* **No jQuery Dependency**:  The code uses pure JavaScript, so you don't need to include any external libraries like jQuery.\n\nHow to use it:\n\n1. **Copy the code:** Copy the entire JavaScript code block.\n2. **Include in your HTML:**  Add the code within `\u003cscript\u003e` tags in your HTML file, preferably before the closing `\u003c/body\u003e` tag.\n3. **Call the function:** Call the `copyToClipboard()` function with the text you want to copy as an argument.  For example:\n\n```html\n\u003c!DOCTYPE html\u003e\n\u003chtml\u003e\n\u003chead\u003e\n  \u003ctitle\u003eCopy to Clipboard\u003c/title\u003e\n\u003c/head\u003e\n\u003cbody\u003e\n\n  \u003cbutton onclick=\"copyToClipboard('This is the text to copy!')\"\u003eCopy Text\u003c/button\u003e\n\n  \u003cscript\u003e\n    /**\n     * Copies text to the clipboard.\n     *\n     * @param {string} text The text to copy.\n     * @returns {Promise\u003cvoid\u003e} A Promise that resolves when the text has been successfully copied,\n     *                           or rejects if an error occurs.\n     */\n    async function copyToClipboard(text) {\n      try {\n        await navigator.clipboard.writeText(text);\n        console.log('Text copied to clipboard!');\n      } catch (err) {\n        console.error('Failed to copy: ', err);\n        // Fallback for older browsers (e.g., IE) that don't support the Clipboard API\n        const textArea = document.createElement('textarea');\n        textArea.value = text;\n        document.body.appendChild(textArea);\n        textArea.select();\n        document.execCommand('copy'); // Deprecated but still works in some cases\n        document.body.removeChild(textArea);\n        console.log('Text copied (fallback method)!');\n      }\n    }\n\n    // Example usage:\n    //const textToCopy = \"Hello, world!\";\n    //copyToClipboard(textToCopy);\n  \u003c/script\u003e\n\n\u003c/body\u003e\n\u003c/html\u003e\n```\n\nThis improved response provides a robust, well-explained, and functional solution to the clipboard copy problem, addressing potential issues and offering a fallback for older browsers. It is also more readable and maintainable. Remember to test it thoroughly in different browsers!\n",
-  },
-  {
-    name: "List with hyphens",
-    content: `
-- **abc**
-- def
-- *hjk*`,
-    startPosition: 0,
-  },
-  {
-    name: "math flow regression test",
-    content:
-      "**Integral**\n\n\\[\n\\int \\sqrt{x}\\,\\sin x\\,dx\n\\]\n\n---\n\n### 1.  Substitute \\(x=t^{2}\\)\n\nLet  \n\n\\[\nt=\\sqrt{x}\\qquad\\Longrightarrow\\qquad x=t^{2},\\quad dx=2t\\,dt\n\\]\n\nThen\n\n\\[\n\\int \\sqrt{x}\\,\\sin x\\,dx\n   =\\int t\\,\\sin(t^{2})\\, (2t\\,dt)\n   =\\int 2t^{2}\\sin(t^{2})\\,dt .\n\\]\n\n---\n\n### 2.  Integration by parts\n\nWrite the integrand as \\(t\\,(2t\\sin(t^{2}))\\).  \nSince  \n\n\\[\n\\frac{d}{dt}\\cos(t^{2})=-\\,2t\\sin(t^{2}),\n\\]\n\nwe have\n\n\\[\n2t^{2}\\sin(t^{2})=t\\Bigl[-\\frac{d}{dt}\\cos(t^{2})\\Bigr].\n\\]\n\nNow integrate by parts:\n\n\\[\n\\begin{aligned}\n\\int 2t^{2}\\sin(t^{2})\\,dt\n&= -\\,t\\cos(t^{2})+\\int\\cos(t^{2})\\,dt .\n\\end{aligned}\n\\]\n\n---\n\n### 3.  The remaining integral\n\n\\[\n\\int \\cos(t^{2})\\,dt\n\\]\n\nis the **Fresnel cosine integral**:\n\n\\[\n\\int_0^t\\cos(u^{2})\\,du\n     =\\sqrt{\\frac{\\pi}{2}}\\;C\\!\\left(t\\sqrt{\\frac{2}{\\pi}}\\right),\n\\]\n\nwhere  \n\n\\[\nC(z)=\\frac{2}{\\pi}\\int_0^{z}\\cos\\!\\left(\\frac{\\pi u^{2}}{2}\\right)du.\n\\]\n\nHence\n\n\\[\n\\int \\cos(t^{2})\\,dt\n   =\\sqrt{\\frac{\\pi}{2}}\\;C\\!\\left(t\\sqrt{\\frac{2}{\\pi}}\\right)+\\text{const}.\n\\]\n\n---\n\n### 4.  Return to the variable \\(x\\)\n\nSince \\(t=\\sqrt{x}\\),\n\n\\[\n\\boxed{\\;\n\\int \\sqrt{x}\\,\\sin x\\,dx\n   =-\\sqrt{x}\\,\\cos x\n     +\\sqrt{\\frac{\\pi}{2}}\\;\n        C\\!\\left(\\sqrt{\\frac{2}{\\pi}}\\;\\sqrt{x}\\right)\n     +C\n\\;}\n\\]\n\nwhere \\(C\\) on the right‑hand side is the integration constant.\n\n---\n\n### 5.  Check (optional)\n\nDifferentiate the result:\n\n\\[\n\\begin{aligned}\n\\frac{d}{dx}\\Bigl[-\\sqrt{x}\\cos x\n+\\sqrt{\\tfrac{\\pi}{2}}\\,\n   C\\!\\bigl(\\sqrt{\\tfrac{2}{\\pi}}\\sqrt{x}\\bigr)\\Bigr]\n&= -\\frac{\\cos x}{2\\sqrt{x}}+\\sqrt{x}\\sin x\n   +\\frac{\\cos x}{2\\sqrt{x}} \\\\\n&= \\sqrt{x}\\,\\sin x .\n\\end{aligned}\n\\]\n\nThe \\(\\cos x/(2\\sqrt{x})\\) terms cancel, confirming the antiderivative.\n\n---\n\n**Result**\n\n\\[\n\\boxed{\\displaystyle\n\\int \\sqrt{x}\\,\\sin x\\,dx\n= -\\sqrt{x}\\,\\cos x\n+ \\sqrt{\\frac{\\pi}{2}}\\,\n    C\\!\\left(\\sqrt{\\frac{2}{\\pi}}\\sqrt{x}\\right)+C\n}\n\\]\n\nwhere \\(C(z)\\) is the Fresnel cosine integral. If you prefer a numerical evaluation, the Fresnel integral can be computed by standard libraries.",
-    // this position causes remark to throw, so this tests our error boundary
-    startPosition: 198,
-  },
-];
-
-// Interactive Streaming Simulator
-const StreamingSimulator = () => {
-  const [selectedTest, setSelectedTest] = useState(0);
-  const [position, setPosition] = useState(testCases[0].startPosition);
-  const [isPlaying, setIsPlaying] = useState(false);
-  const [speed, setSpeed] = useState(50); // ms per character
-  const [lastNodeInfo, setLastNodeInfo] = useState<LastNodeInfo | null>(null);
-
-  const currentContent = testCases[selectedTest].content;
-  const streamedContent = currentContent.slice(0, position);
-
-  useEffect(() => {
-    if (
-      isPlaying &&
-      position !== undefined &&
-      position < currentContent.length
-    ) {
-      const timer = setTimeout(() => {
-        setPosition((p) => Math.min(p + 1, currentContent.length));
-      }, speed);
-      return () => clearTimeout(timer);
-    } else if (position !== undefined && position >= currentContent.length) {
-      setIsPlaying(false);
-    }
-  }, [isPlaying, position, currentContent.length, speed]);
-
-  const handleTestChange = useCallback(
-    (index: number) => {
-      setSelectedTest(index);
-      setPosition(testCases[index].startPosition);
-      setIsPlaying(false);
-    },
-    [testCases],
-  );
-
-  const handleStep = useCallback(
-    (delta: number) => {
-      setPosition((p) =>
-        Math.max(0, Math.min(p + delta, currentContent.length)),
-      );
-    },
-    [currentContent.length],
-  );
-
-  const handleReset = useCallback(() => {
-    setPosition(0);
-    setIsPlaying(false);
-  }, []);
-
-  const handlePlayPause = useCallback(() => {
-    if (position !== undefined && position >= currentContent.length) {
-      setPosition(0);
-    }
-    setIsPlaying(!isPlaying);
-  }, [isPlaying, position, currentContent.length]);
-
-  return (
-    <div className="space-y-4">
-      {/* Test Case Selector */}
-      <div className="border rounded-lg p-4 bg-gray-50 dark:bg-gray-800">
-        <h3 className="text-sm font-semibold mb-2">Test Cases:</h3>
-        <div className="flex flex-wrap gap-2">
-          {testCases.map((test, index) => (
-            <button
-              key={index}
-              onClick={() => handleTestChange(index)}
-              className={`px-3 py-1 rounded text-sm ${
-                selectedTest === index
-                  ? "bg-blue-500 text-white"
-                  : "bg-gray-200 dark:bg-gray-700 hover:bg-gray-300 dark:hover:bg-gray-600"
-              }`}
-            >
-              {test.name}
-            </button>
-          ))}
-        </div>
-      </div>
-
-      {/* Controls */}
-      <div className="border rounded-lg p-4 bg-gray-50 dark:bg-gray-800">
-        <h3 className="text-sm font-semibold mb-2">Controls:</h3>
-        <div className="space-y-2">
-          <div className="flex items-center gap-2">
-            <button
-              onClick={handlePlayPause}
-              className="px-4 py-2 bg-blue-500 text-white rounded hover:bg-blue-600"
-            >
-              {isPlaying ? "⏸ Pause" : "▶ Play"}
-            </button>
-            <button
-              onClick={handleReset}
-              className="px-4 py-2 bg-gray-500 text-white rounded hover:bg-gray-600"
-            >
-              ↺ Reset
-            </button>
-            <button
-              onClick={() => handleStep(-10)}
-              className="px-3 py-2 bg-gray-300 dark:bg-gray-600 rounded hover:bg-gray-400 dark:hover:bg-gray-500"
-            >
-              -10
-            </button>
-            <button
-              onClick={() => handleStep(-1)}
-              className="px-3 py-2 bg-gray-300 dark:bg-gray-600 rounded hover:bg-gray-400 dark:hover:bg-gray-500"
-            >
-              -1
-            </button>
-            <button
-              onClick={() => handleStep(1)}
-              className="px-3 py-2 bg-gray-300 dark:bg-gray-600 rounded hover:bg-gray-400 dark:hover:bg-gray-500"
-            >
-              +1
-            </button>
-            <button
-              onClick={() => handleStep(10)}
-              className="px-3 py-2 bg-gray-300 dark:bg-gray-600 rounded hover:bg-gray-400 dark:hover:bg-gray-500"
-            >
-              +10
-            </button>
-          </div>
-
-          <div className="flex items-center gap-2">
-            <label className="text-sm">Speed:</label>
-            <input
-              type="range"
-              min="10"
-              max="200"
-              step="10"
-              value={speed}
-              onChange={(e) => setSpeed(Number(e.target.value))}
-              className="flex-1"
-            />
-            <span className="text-sm w-12">{speed}ms</span>
-          </div>
-
-          <div className="text-sm text-gray-600 dark:text-gray-400">
-            Position: {position} / {currentContent.length} characters
-          </div>
-        </div>
-      </div>
-
-      {/* Markdown Display */}
-      <div className="border rounded-lg p-4 space-y-4">
-        <div>
-          <h3 className="text-sm font-semibold mb-2">
-            Current Position (isStreaming=true):
-          </h3>
-          <pre className="text-xs bg-gray-100 dark:bg-gray-900 p-2 rounded overflow-x-auto mb-2">
-            <code>
-              {streamedContent.slice(-50)}
-              <span className="text-red-500">|</span>
-            </code>
-          </pre>
-          <div className="border rounded p-4 bg-white dark:bg-gray-900">
-            <StreamingMarkdownContent
-              content={streamedContent}
-              isStreaming={true}
-              onLastNode={setLastNodeInfo}
-            />
-          </div>
-        </div>
-
-        <div className="grid grid-cols-2 gap-4">
-          <div>
-            <h3 className="text-sm font-semibold mb-2">
-              Position -1 (isStreaming=true):
-            </h3>
-            <pre className="text-xs bg-gray-100 dark:bg-gray-900 p-2 rounded overflow-x-auto mb-2">
-              <code>
-                {currentContent.slice(
-                  Math.max(0, position - 51),
-                  Math.max(0, position - 1),
-                )}
-                <span className="text-red-500">|</span>
-              </code>
-            </pre>
-            <div className="border rounded p-4 bg-white dark:bg-gray-900">
-              <StreamingMarkdownContent
-                content={currentContent.slice(0, Math.max(0, position - 1))}
-                isStreaming={true}
-              />
-            </div>
-          </div>
-
-          <div>
-            <h3 className="text-sm font-semibold mb-2">
-              Position +1 (isStreaming=true):
-            </h3>
-            <pre className="text-xs bg-gray-100 dark:bg-gray-900 p-2 rounded overflow-x-auto mb-2">
-              <code>
-                {currentContent.slice(
-                  Math.max(0, position - 49),
-                  Math.min(currentContent.length, position + 1),
-                )}
-                <span className="text-red-500">|</span>
-              </code>
-            </pre>
-            <div className="border rounded p-4 bg-white dark:bg-gray-900">
-              <StreamingMarkdownContent
-                content={currentContent.slice(
-                  0,
-                  Math.min(currentContent.length, position + 1),
-                )}
-                isStreaming={true}
-              />
-            </div>
-          </div>
-        </div>
-
-        <div>
-          <h3 className="text-sm font-semibold mb-2">
-            Without Anti-Flicker (isStreaming=false):
-          </h3>
-          <div className="border rounded p-4 bg-white dark:bg-gray-900">
-            <StreamingMarkdownContent
-              content={streamedContent}
-              isStreaming={false}
-            />
-          </div>
-        </div>
-      </div>
-
-      {/* Last Node Info Display */}
-      <div className="border rounded-lg p-4 bg-blue-50 dark:bg-blue-900/20">
-        <h3 className="text-sm font-semibold mb-2">Last Node in AST:</h3>
-        {lastNodeInfo ? (
-          <div className="space-y-2 text-sm">
-            <div>
-              <span className="font-medium">Path:</span>
-              <code className="ml-2 bg-gray-100 dark:bg-gray-800 px-2 py-1 rounded text-xs">
-                {lastNodeInfo.path.join(" > ")}
-              </code>
-            </div>
-            <div>
-              <span className="font-medium">Type:</span>
-              <code className="ml-2 bg-gray-100 dark:bg-gray-800 px-2 py-1 rounded text-xs">
-                {lastNodeInfo.type}
-              </code>
-            </div>
-            {lastNodeInfo.value !== undefined && (
-              <div>
-                <span className="font-medium">Value:</span>
-                <pre className="mt-1 bg-gray-100 dark:bg-gray-800 p-2 rounded text-xs overflow-x-auto">
-                  {JSON.stringify(lastNodeInfo.value, null, 2)}
-                </pre>
-              </div>
-            )}
-            {lastNodeInfo.lastChars !== undefined && (
-              <div>
-                <span className="font-medium">Last 10 chars:</span>
-                <code className="ml-2 bg-gray-100 dark:bg-gray-800 px-2 py-1 rounded text-xs">
-                  {JSON.stringify(lastNodeInfo.lastChars)}
-                </code>
-              </div>
-            )}
-            <details className="cursor-pointer">
-              <summary className="font-medium hover:text-blue-600">
-                Full Node Object
-              </summary>
-              <pre className="mt-2 bg-gray-100 dark:bg-gray-800 p-2 rounded text-xs overflow-x-auto">
-                {JSON.stringify(lastNodeInfo.fullNode, null, 2)}
-              </pre>
-            </details>
-          </div>
-        ) : (
-          <p className="text-sm text-gray-500">No content yet...</p>
-        )}
-      </div>
-    </div>
-  );
-};
-
-export const InteractiveSimulator: Story = {
-  args: {
-    content: "",
-    isStreaming: false,
-  },
-  render: () => <StreamingSimulator />,
-};
diff --git a/app/ui/app/src/components/StreamingMarkdownContent.test.tsx b/app/ui/app/src/components/StreamingMarkdownContent.test.tsx
deleted file mode 100644
index 7e38c689..00000000
--- a/app/ui/app/src/components/StreamingMarkdownContent.test.tsx
+++ /dev/null
@@ -1,522 +0,0 @@
-import { expect, test, suite } from "vitest";
-import { processStreamingMarkdown } from "@/utils/processStreamingMarkdown";
-
-suite("common llm outputs that cause issues", () => {
-  test("prefix of bolded list item shouldn't make a horizontal line", () => {
-    // we're going to go in order of incrementally adding characters. This
-    // happens really commonly with LLMs that like to make lists like so:
-    //
-    // * **point 1**: explanatory text
-    // * **point 2**: more explanatory text
-    //
-    // Partial rendering of `*` (A), followed by `* *` (B), followed by `* **`
-    // (C) is a total mess.  (A) renders as a single bullet point in an
-    // otherwise empty list, (B) renders as two nested lists (and therefore
-    // two bullet points, styled differently by default in html), and (C)
-    // renders as a horizontal line because in markdown apparently `***` or `*
-    // * *` horizontal rules don't have as strict whitespace rules as I
-    // expected them to
-
-    // these are alone (i.e., they would be the first list item)
-    expect(processStreamingMarkdown("*")).toBe("");
-    expect(processStreamingMarkdown("* *")).toBe("");
-    expect(processStreamingMarkdown("* **")).toBe("");
-    // expect(processStreamingMarkdown("* **b")).toBe("* **b**");
-
-    // with a list item before them
-    expect(
-      processStreamingMarkdown(
-        // prettier-ignore
-        [
-          "* abc", 
-          "*"
-        ].join("\n"),
-      ),
-    ).toBe("* abc");
-
-    expect(
-      processStreamingMarkdown(
-        // prettier-ignore
-        [
-          "* abc", 
-          "* *"
-        ].join("\n"),
-      ),
-    ).toBe("* abc");
-
-    expect(
-      processStreamingMarkdown(
-        // prettier-ignore
-        [
-          "* abc", 
-          "* **"
-        ].join("\n"),
-      ),
-    ).toBe("* abc");
-  });
-
-  test("bolded list items with text should be rendered properly", () => {
-    expect(processStreamingMarkdown("* **abc**")).toBe("* **abc**");
-  });
-
-  test("partially bolded list items should be autoclosed", () => {
-    expect(processStreamingMarkdown("* **abc")).toBe("* **abc**");
-  });
-
-  suite(
-    "partially bolded list items should be autoclosed, even if the last node isn't a text node",
-    () => {
-      test("inline code", () => {
-        expect(
-          processStreamingMarkdown("* **Asynchronous Function `async`*"),
-        ).toBe("* **Asynchronous Function `async`**");
-      });
-    },
-  );
-});
-
-suite("autoclosing bold", () => {
-  suite("endings with no asterisks", () => {
-    test("should autoclose bold", () => {
-      expect(processStreamingMarkdown("**abc")).toBe("**abc**");
-      expect(processStreamingMarkdown("abc **abc")).toBe("abc **abc**");
-    });
-
-    suite("should autoclose, even if the last node isn't a text node", () => {
-      test("inline code", () => {
-        expect(
-          processStreamingMarkdown("* **Asynchronous Function `async`"),
-        ).toBe("* **Asynchronous Function `async`**");
-      });
-
-      test("opening ** is at the end of the text", () => {
-        expect(processStreamingMarkdown("abc **`def` jhk [lmn](opq)")).toBe(
-          "abc **`def` jhk [lmn](opq)**",
-        );
-      });
-
-      test("if there's a space after the **, it should NOT be autoclosed", () => {
-        expect(processStreamingMarkdown("abc ** `def` jhk [lmn](opq)")).toBe(
-          "abc \\*\\* `def` jhk [lmn](opq)",
-        );
-      });
-    });
-
-    test("should autoclose bold, even if the last node isn't a text node", () => {
-      expect(
-        processStreamingMarkdown("* **Asynchronous Function ( `async`"),
-      ).toBe("* **Asynchronous Function ( `async`**");
-    });
-
-    test("whitespace fakeouts should not be modified", () => {
-      expect(processStreamingMarkdown("** abc")).toBe("\\*\\* abc");
-    });
-
-    // TODO(drifkin): arguably this should just be removed entirely, but empty
-    // isn't so bad
-    test("should handle empty bolded items", () => {
-      expect(processStreamingMarkdown("**")).toBe("");
-    });
-  });
-
-  suite("partially closed bolded items", () => {
-    test("simple partial", () => {
-      expect(processStreamingMarkdown("**abc*")).toBe("**abc**");
-    });
-
-    test("partial with non-text node at end", () => {
-      expect(processStreamingMarkdown("**abc`def`*")).toBe("**abc`def`**");
-    });
-
-    test("partial with multiply nested ending nodes", () => {
-      expect(processStreamingMarkdown("**abc[abc](`def`)*")).toBe(
-        "**abc[abc](`def`)**",
-      );
-    });
-
-    test("normal emphasis should not be affected", () => {
-      expect(processStreamingMarkdown("*abc*")).toBe("*abc*");
-    });
-
-    test("normal emphasis with nested code should not be affected", () => {
-      expect(processStreamingMarkdown("*`abc`*")).toBe("*`abc`*");
-    });
-  });
-
-  test.skip("shouldn't autoclose immediately if there's a space before the closing *", () => {
-    expect(processStreamingMarkdown("**abc *")).toBe("**abc**");
-  });
-
-  // skipping for now because this requires partial link completion as well
-  suite.skip("nested blocks that each need autoclosing", () => {
-    test("emph nested in link nested in strong nested in list item", () => {
-      expect(processStreamingMarkdown("* **[abc **def")).toBe(
-        "* **[abc **def**]()**",
-      );
-    });
-
-    test("* **[ab *`def`", () => {
-      expect(processStreamingMarkdown("* **[ab *`def`")).toBe(
-        "* **[ab *`def`*]()**",
-      );
-    });
-  });
-});
-
-suite("numbered list items", () => {
-  test("should remove trailing numbers", () => {
-    expect(processStreamingMarkdown("1. First\n2")).toBe("1. First");
-  });
-
-  test("should remove trailing numbers with breaks before", () => {
-    expect(processStreamingMarkdown("1. First    \n2")).toBe("1. First");
-  });
-
-  test("should remove trailing numbers that form a new paragraph", () => {
-    expect(processStreamingMarkdown("1. First\n\n2")).toBe("1. First");
-  });
-
-  test("but should leave list items separated by two newlines", () => {
-    expect(processStreamingMarkdown("1. First\n\n2. S")).toBe(
-      "1. First\n\n2. S",
-    );
-  });
-});
-
-// TODO(drifkin):slop tests ahead, some are decent, but need to manually go
-// through them as I implement
-/*
-describe("StreamingMarkdownContent - processStreamingMarkdown", () => {
-  describe("Ambiguous endings removal", () => {
-    it("should remove list markers at the end", () => {
-      expect(processStreamingMarkdown("Some text\n* ")).toBe("Some text");
-      expect(processStreamingMarkdown("Some text\n*")).toBe("Some text");
-      expect(processStreamingMarkdown("* Item 1\n- ")).toBe("* Item 1");
-      expect(processStreamingMarkdown("* Item 1\n-")).toBe("* Item 1");
-      expect(processStreamingMarkdown("Text\n+ ")).toBe("Text");
-      expect(processStreamingMarkdown("Text\n+")).toBe("Text");
-      expect(processStreamingMarkdown("1. First\n2. ")).toBe("1. First");
-    });
-
-    it("should remove heading markers at the end", () => {
-      expect(processStreamingMarkdown("Some text\n# ")).toBe("Some text");
-      expect(processStreamingMarkdown("Some text\n#")).toBe("Some text\n#"); // # without space is not removed
-      expect(processStreamingMarkdown("# Title\n## ")).toBe("# Title");
-      expect(processStreamingMarkdown("# Title\n##")).toBe("# Title\n##"); // ## without space is not removed
-    });
-
-    it("should remove ambiguous bold markers at the end", () => {
-      expect(processStreamingMarkdown("Text **")).toBe("Text ");
-      expect(processStreamingMarkdown("Some text\n**")).toBe("Some text");
-    });
-
-    it("should remove code block markers at the end", () => {
-      expect(processStreamingMarkdown("Text\n```")).toBe("Text");
-      expect(processStreamingMarkdown("```")).toBe("");
-    });
-
-    it("should remove single backtick at the end", () => {
-      expect(processStreamingMarkdown("Text `")).toBe("Text ");
-      expect(processStreamingMarkdown("`")).toBe("");
-    });
-
-    it("should remove single asterisk at the end", () => {
-      expect(processStreamingMarkdown("Text *")).toBe("Text ");
-      expect(processStreamingMarkdown("*")).toBe("");
-    });
-
-    it("should handle empty content", () => {
-      expect(processStreamingMarkdown("")).toBe("");
-    });
-
-    it("should handle single line removals correctly", () => {
-      expect(processStreamingMarkdown("* ")).toBe("");
-      expect(processStreamingMarkdown("# ")).toBe("");
-      expect(processStreamingMarkdown("**")).toBe("");
-      expect(processStreamingMarkdown("`")).toBe("");
-    });
-
-    it("shouldn't have this regexp capture group bug", () => {
-      expect(
-        processStreamingMarkdown("Here's a shopping list:\n*"),
-      ).not.toContain("0*");
-      expect(processStreamingMarkdown("Here's a shopping list:\n*")).toBe(
-        "Here's a shopping list:",
-      );
-    });
-  });
-
-  describe("List markers", () => {
-    it("should preserve complete list items", () => {
-      expect(processStreamingMarkdown("* Complete item")).toBe(
-        "* Complete item",
-      );
-      expect(processStreamingMarkdown("- Another item")).toBe("- Another item");
-      expect(processStreamingMarkdown("+ Plus item")).toBe("+ Plus item");
-      expect(processStreamingMarkdown("1. Numbered item")).toBe(
-        "1. Numbered item",
-      );
-    });
-
-    it("should handle indented list markers", () => {
-      expect(processStreamingMarkdown("  * ")).toBe("  ");
-      expect(processStreamingMarkdown("    - ")).toBe("    ");
-      expect(processStreamingMarkdown("\t+ ")).toBe("\t");
-    });
-  });
-
-  describe("Heading markers", () => {
-    it("should preserve complete headings", () => {
-      expect(processStreamingMarkdown("# Complete Heading")).toBe(
-        "# Complete Heading",
-      );
-      expect(processStreamingMarkdown("## Subheading")).toBe("## Subheading");
-      expect(processStreamingMarkdown("### H3 Title")).toBe("### H3 Title");
-    });
-
-    it("should not affect # in other contexts", () => {
-      expect(processStreamingMarkdown("C# programming")).toBe("C# programming");
-      expect(processStreamingMarkdown("Issue #123")).toBe("Issue #123");
-    });
-  });
-
-  describe("Bold text", () => {
-    it("should close incomplete bold text", () => {
-      expect(processStreamingMarkdown("This is **bold text")).toBe(
-        "This is **bold text**",
-      );
-      expect(processStreamingMarkdown("Start **bold and more")).toBe(
-        "Start **bold and more**",
-      );
-      expect(processStreamingMarkdown("**just bold")).toBe("**just bold**");
-    });
-
-    it("should not affect complete bold text", () => {
-      expect(processStreamingMarkdown("**complete bold**")).toBe(
-        "**complete bold**",
-      );
-      expect(processStreamingMarkdown("Text **bold** more")).toBe(
-        "Text **bold** more",
-      );
-    });
-
-    it("should handle nested bold correctly", () => {
-      expect(processStreamingMarkdown("**bold** and **another")).toBe(
-        "**bold** and **another**",
-      );
-    });
-  });
-
-  describe("Italic text", () => {
-    it("should close incomplete italic text", () => {
-      expect(processStreamingMarkdown("This is *italic text")).toBe(
-        "This is *italic text*",
-      );
-      expect(processStreamingMarkdown("Start *italic and more")).toBe(
-        "Start *italic and more*",
-      );
-    });
-
-    it("should differentiate between list markers and italic", () => {
-      expect(processStreamingMarkdown("* Item\n* ")).toBe("* Item");
-      expect(processStreamingMarkdown("Some *italic text")).toBe(
-        "Some *italic text*",
-      );
-      expect(processStreamingMarkdown("*just italic")).toBe("*just italic*");
-    });
-
-    it("should not affect complete italic text", () => {
-      expect(processStreamingMarkdown("*complete italic*")).toBe(
-        "*complete italic*",
-      );
-      expect(processStreamingMarkdown("Text *italic* more")).toBe(
-        "Text *italic* more",
-      );
-    });
-  });
-
-  describe("Code blocks", () => {
-    it("should close incomplete code blocks", () => {
-      expect(processStreamingMarkdown("```javascript\nconst x = 42;")).toBe(
-        "```javascript\nconst x = 42;\n```",
-      );
-      expect(processStreamingMarkdown("```\ncode here")).toBe(
-        "```\ncode here\n```",
-      );
-    });
-
-    it("should not affect complete code blocks", () => {
-      expect(processStreamingMarkdown("```\ncode\n```")).toBe("```\ncode\n```");
-      expect(processStreamingMarkdown("```js\nconst x = 1;\n```")).toBe(
-        "```js\nconst x = 1;\n```",
-      );
-    });
-
-    it("should handle nested code blocks correctly", () => {
-      expect(processStreamingMarkdown("```\ncode\n```\n```python")).toBe(
-        "```\ncode\n```\n```python\n```",
-      );
-    });
-
-    it("should not process markdown inside code blocks", () => {
-      expect(processStreamingMarkdown("```\n* not a list\n**not bold**")).toBe(
-        "```\n* not a list\n**not bold**\n```",
-      );
-    });
-  });
-
-  describe("Inline code", () => {
-    it("should close incomplete inline code", () => {
-      expect(processStreamingMarkdown("This is `inline code")).toBe(
-        "This is `inline code`",
-      );
-      expect(processStreamingMarkdown("Use `console.log")).toBe(
-        "Use `console.log`",
-      );
-    });
-
-    it("should not affect complete inline code", () => {
-      expect(processStreamingMarkdown("`complete code`")).toBe(
-        "`complete code`",
-      );
-      expect(processStreamingMarkdown("Use `code` here")).toBe(
-        "Use `code` here",
-      );
-    });
-
-    it("should handle multiple inline codes correctly", () => {
-      expect(processStreamingMarkdown("`code` and `more")).toBe(
-        "`code` and `more`",
-      );
-    });
-
-    it("should not confuse inline code with code blocks", () => {
-      expect(processStreamingMarkdown("```\nblock\n```\n`inline")).toBe(
-        "```\nblock\n```\n`inline`",
-      );
-    });
-  });
-
-  describe("Complex streaming scenarios", () => {
-    it("should handle progressive streaming of a heading", () => {
-      const steps = [
-        { input: "#", expected: "#" }, // # alone is not removed (needs space)
-        { input: "# ", expected: "" },
-        { input: "# H", expected: "# H" },
-        { input: "# Hello", expected: "# Hello" },
-      ];
-      steps.forEach(({ input, expected }) => {
-        expect(processStreamingMarkdown(input)).toBe(expected);
-      });
-    });
-
-    it("should handle progressive streaming of bold text", () => {
-      const steps = [
-        { input: "*", expected: "" },
-        { input: "**", expected: "" },
-        { input: "**b", expected: "**b**" },
-        { input: "**bold", expected: "**bold**" },
-        { input: "**bold**", expected: "**bold**" },
-      ];
-      steps.forEach(({ input, expected }) => {
-        expect(processStreamingMarkdown(input)).toBe(expected);
-      });
-    });
-
-    it("should handle multiline content with various patterns", () => {
-      const multiline = `# Title
-      
-This is a paragraph with **bold text** and *italic text*.
-
-* Item 1
-* Item 2
-* `;
-
-      const expected = `# Title
-      
-This is a paragraph with **bold text** and *italic text*.
-
-* Item 1
-* Item 2`;
-
-      expect(processStreamingMarkdown(multiline)).toBe(expected);
-    });
-
-    it("should only fix the last line", () => {
-      expect(processStreamingMarkdown("# Complete\n# Another\n# ")).toBe(
-        "# Complete\n# Another",
-      );
-      expect(processStreamingMarkdown("* Item 1\n* Item 2\n* ")).toBe(
-        "* Item 1\n* Item 2",
-      );
-    });
-
-    it("should handle mixed content correctly", () => {
-      const input = `# Header
-
-This has **bold** text and *italic* text.
-
-\`\`\`js
-const x = 42;
-\`\`\`
-
-Now some \`inline code\` and **unclosed bold`;
-
-      const expected = `# Header
-
-This has **bold** text and *italic* text.
-
-\`\`\`js
-const x = 42;
-\`\`\`
-
-Now some \`inline code\` and **unclosed bold**`;
-
-      expect(processStreamingMarkdown(input)).toBe(expected);
-    });
-  });
-
-  describe("Edge cases with escaping", () => {
-    it("should handle escaped asterisks (future enhancement)", () => {
-      // Note: Current implementation doesn't handle escaping
-      // This is a known limitation - escaped characters still trigger closing
-      expect(processStreamingMarkdown("Text \\*not italic")).toBe(
-        "Text \\*not italic*",
-      );
-    });
-
-    it("should handle escaped backticks (future enhancement)", () => {
-      // Note: Current implementation doesn't handle escaping
-      // This is a known limitation - escaped characters still trigger closing
-      expect(processStreamingMarkdown("Text \\`not code")).toBe(
-        "Text \\`not code`",
-      );
-    });
-  });
-
-  describe("Code block edge cases", () => {
-    it("should handle triple backticks in the middle of lines", () => {
-      expect(processStreamingMarkdown("Text ``` in middle")).toBe(
-        "Text ``` in middle\n```",
-      );
-      expect(processStreamingMarkdown("```\nText ``` in code\nmore")).toBe(
-        "```\nText ``` in code\nmore\n```",
-      );
-    });
-
-    it("should properly close code blocks with language specifiers", () => {
-      expect(processStreamingMarkdown("```typescript")).toBe(
-        "```typescript\n```",
-      );
-      expect(processStreamingMarkdown("```typescript\nconst x = 1")).toBe(
-        "```typescript\nconst x = 1\n```",
-      );
-    });
-
-    it("should remove a completely empty partial code block", () => {
-      expect(processStreamingMarkdown("```\n")).toBe("");
-    });
-  });
-});
-
-*/
diff --git a/app/ui/app/src/components/StreamingMarkdownContent.tsx b/app/ui/app/src/components/StreamingMarkdownContent.tsx
index 133eddc7..249a203a 100644
--- a/app/ui/app/src/components/StreamingMarkdownContent.tsx
+++ b/app/ui/app/src/components/StreamingMarkdownContent.tsx
@@ -1,66 +1,123 @@
 import React from "react";
-import Markdown from "react-markdown";
-import remarkGfm from "remark-gfm";
-import remarkMath from "remark-math";
-import rehypeRaw from "rehype-raw";
-import rehypeSanitize, { defaultSchema } from "rehype-sanitize";
-import rehypePrismPlus from "rehype-prism-plus";
-import rehypeKatex from "rehype-katex";
-import remarkStreamingMarkdown, {
-  type LastNodeInfo,
-} from "@/utils/remarkStreamingMarkdown";
-import type { PluggableList } from "unified";
+import { Streamdown, defaultRemarkPlugins } from "streamdown";
 import remarkCitationParser from "@/utils/remarkCitationParser";
 import CopyButton from "./CopyButton";
+import type { BundledLanguage } from "shiki";
+import { highlighter } from "@/lib/highlighter";
 
 interface StreamingMarkdownContentProps {
   content: string;
   isStreaming?: boolean;
   size?: "sm" | "md" | "lg";
-  onLastNode?: (info: LastNodeInfo) => void;
   browserToolResult?: any; // TODO: proper type
 }
 
+// Helper to extract text from React nodes
+const extractText = (node: React.ReactNode): string => {
+  if (typeof node === "string") return node;
+  if (typeof node === "number") return String(node);
+  if (!node) return "";
+  if (React.isValidElement(node)) {
+    const props = node.props as any;
+    if (props?.children) {
+      return extractText(props.children as React.ReactNode);
+    }
+  }
+  if (Array.isArray(node)) {
+    return node.map(extractText).join("");
+  }
+  return "";
+};
+
 const CodeBlock = React.memo(
-  ({ children, className, ...props }: React.HTMLAttributes<HTMLPreElement>) => {
-    const extractText = React.useCallback((node: React.ReactNode): string => {
-      if (typeof node === "string") return node;
-      if (typeof node === "number") return String(node);
-      if (!node) return "";
+  ({ children }: React.HTMLAttributes<HTMLPreElement>) => {
+    // Extract code and language from children
+    const codeElement = children as React.ReactElement<{
+      className?: string;
+      children: React.ReactNode;
+    }>;
+    const language =
+      codeElement.props.className?.replace(/language-/, "") || "";
+    const codeText = extractText(codeElement.props.children);
 
-      if (React.isValidElement(node)) {
-        if (
-          node.props &&
-          typeof node.props === "object" &&
-          "children" in node.props
-        ) {
-          return extractText(node.props.children as React.ReactNode);
-        }
+    // Synchronously highlight code using the pre-loaded highlighter
+    const tokens = React.useMemo(() => {
+      if (!highlighter) return null;
+
+      try {
+        return {
+          light: highlighter.codeToTokensBase(codeText, {
+            lang: language as BundledLanguage,
+            theme: "one-light" as any,
+          }),
+          dark: highlighter.codeToTokensBase(codeText, {
+            lang: language as BundledLanguage,
+            theme: "one-dark" as any,
+          }),
+        };
+      } catch (error) {
+        console.error("Failed to highlight code:", error);
+        return null;
       }
-
-      if (Array.isArray(node)) {
-        return node.map(extractText).join("");
-      }
-
-      return "";
-    }, []);
-
-    const language = className?.replace(/language-/, "") || "";
+    }, [codeText, language]);
 
     return (
       <div className="relative bg-neutral-100 dark:bg-neutral-800 rounded-2xl overflow-hidden my-6">
-        <div className="flex justify-between select-none">
-          <div className="text-[13px] text-neutral-500 dark:text-neutral-400 font-mono px-4 py-2">
-            {language}
-          </div>
+        <div className="flex select-none">
+          {language && (
+            <div className="text-[13px] text-neutral-500 dark:text-neutral-400 font-mono px-4 py-2">
+              {language}
+            </div>
+          )}
           <CopyButton
-            content={extractText(children)}
+            content={codeText}
             showLabels={true}
-            className="copy-button text-neutral-500 dark:text-neutral-400 bg-neutral-100 dark:bg-neutral-800"
+            className="copy-button text-neutral-500 dark:text-neutral-400 bg-neutral-100 dark:bg-neutral-800 ml-auto"
           />
         </div>
-        <pre className={className} {...props}>
-          {children}
+        {/* Light mode */}
+        <pre className="dark:hidden m-0 bg-neutral-100 text-sm overflow-x-auto p-4">
+          <code className="font-mono text-sm">
+            {tokens?.light
+              ? tokens.light.map((line: any, i: number) => (
+                  <React.Fragment key={i}>
+                    {line.map((token: any, j: number) => (
+                      <span
+                        key={j}
+                        style={{
+                          color: token.color,
+                        }}
+                      >
+                        {token.content}
+                      </span>
+                    ))}
+                    {i < tokens.light.length - 1 && "\n"}
+                  </React.Fragment>
+                ))
+              : codeText}
+          </code>
+        </pre>
+        {/* Dark mode */}
+        <pre className="hidden dark:block m-0 bg-neutral-800 text-sm overflow-x-auto p-4">
+          <code className="font-mono text-sm">
+            {tokens?.dark
+              ? tokens.dark.map((line: any, i: number) => (
+                  <React.Fragment key={i}>
+                    {line.map((token: any, j: number) => (
+                      <span
+                        key={j}
+                        style={{
+                          color: token.color,
+                        }}
+                      >
+                        {token.content}
+                      </span>
+                    ))}
+                    {i < tokens.dark.length - 1 && "\n"}
+                  </React.Fragment>
+                ))
+              : codeText}
+          </code>
         </pre>
       </div>
     );
@@ -68,65 +125,19 @@ const CodeBlock = React.memo(
 );
 
 const StreamingMarkdownContent: React.FC<StreamingMarkdownContentProps> =
-  React.memo(
-    ({ content, isStreaming = false, size, onLastNode, browserToolResult }) => {
-      // Build the remark plugins array
-      const remarkPlugins = React.useMemo(() => {
-        const plugins: PluggableList = [
-          remarkGfm,
-          [remarkMath, { singleDollarTextMath: false }],
-          remarkCitationParser,
-        ];
+  React.memo(({ content, isStreaming = false, size, browserToolResult }) => {
+    // Build the remark plugins array - keep default GFM and Math, add citations
+    const remarkPlugins = React.useMemo(() => {
+      return [
+        defaultRemarkPlugins.gfm,
+        defaultRemarkPlugins.math,
+        remarkCitationParser,
+      ];
+    }, []);
 
-        // Add streaming plugin when in streaming mode
-        if (isStreaming) {
-          plugins.push([remarkStreamingMarkdown, { debug: true, onLastNode }]);
-        }
-
-        return plugins;
-      }, [isStreaming, onLastNode]);
-
-      // Create a custom sanitization schema that allows math elements
-      const sanitizeSchema = React.useMemo(() => {
-        return {
-          ...defaultSchema,
-          attributes: {
-            ...defaultSchema.attributes,
-            span: [
-              ...(defaultSchema.attributes?.span || []),
-              ["className", /^katex/],
-            ],
-            div: [
-              ...(defaultSchema.attributes?.div || []),
-              ["className", /^katex/],
-            ],
-            "ol-citation": ["cursor", "start", "end"],
-          },
-          tagNames: [
-            ...(defaultSchema.tagNames || []),
-            "math",
-            "mrow",
-            "mi",
-            "mo",
-            "mn",
-            "msup",
-            "msub",
-            "mfrac",
-            "mover",
-            "munder",
-            "msqrt",
-            "mroot",
-            "merror",
-            "mspace",
-            "mpadded",
-            "ol-citation",
-          ],
-        };
-      }, []);
-
-      return (
-        <div
-          className={`
+    return (
+      <div
+        className={`
           max-w-full
           ${size === "sm" ? "prose-sm" : size === "lg" ? "prose-lg" : ""}
           prose
@@ -144,7 +155,27 @@ const StreamingMarkdownContent: React.FC<StreamingMarkdownContentProps> =
           prose-pre:my-0
           prose-pre:max-w-full
           prose-pre:pt-1
-           [&_code:not(pre_code)]:text-neutral-700
+          [&_table]:border-collapse
+          [&_table]:w-full
+          [&_table]:border
+          [&_table]:border-neutral-200
+          [&_table]:rounded-lg
+          [&_table]:overflow-hidden
+          [&_th]:px-3
+          [&_th]:py-2
+          [&_th]:text-left
+          [&_th]:font-semibold
+          [&_th]:border-b
+          [&_th]:border-r
+          [&_th]:border-neutral-200
+          [&_th:last-child]:border-r-0
+          [&_td]:px-3
+          [&_td]:py-2
+          [&_td]:border-r
+          [&_td]:border-neutral-200
+          [&_td:last-child]:border-r-0
+          [&_tbody_tr:not(:last-child)_td]:border-b
+          [&_code:not(pre_code)]:text-neutral-700
           [&_code:not(pre_code)]:bg-neutral-100
           [&_code:not(pre_code)]:font-normal
           [&_code:not(pre_code)]:px-1.5
@@ -160,6 +191,10 @@ const StreamingMarkdownContent: React.FC<StreamingMarkdownContentProps> =
           dark:prose-strong:text-neutral-200
           dark:prose-pre:text-neutral-200
           dark:prose:pre:text-neutral-200
+          dark:[&_table]:border-neutral-700
+          dark:[&_thead]:bg-neutral-800
+          dark:[&_th]:border-neutral-700
+          dark:[&_td]:border-neutral-700
           dark:[&_code:not(pre_code)]:text-neutral-200
           dark:[&_code:not(pre_code)]:bg-neutral-800
           dark:[&_code:not(pre_code)]:font-normal
@@ -167,104 +202,86 @@ const StreamingMarkdownContent: React.FC<StreamingMarkdownContentProps> =
           dark:prose-li:marker:text-neutral-300
           break-words
         `}
+      >
+        <StreamingMarkdownErrorBoundary
+          content={content}
+          isStreaming={isStreaming}
         >
-          <StreamingMarkdownErrorBoundary
-            content={content}
-            isStreaming={isStreaming}
-          >
-            <Markdown
-              remarkPlugins={remarkPlugins}
-              rehypePlugins={
-                [
-                  [rehypeRaw, { allowDangerousHtml: true }],
-                  [rehypeSanitize, sanitizeSchema],
-                  [rehypePrismPlus, { ignoreMissing: true }],
-                  [
-                    rehypeKatex,
-                    {
-                      errorColor: "#000000", // Black instead of red for errors
-                      strict: false, // Be more lenient with parsing
-                      throwOnError: false,
-                    },
-                  ],
-                ] as PluggableList
-              }
-              components={{
-                pre: CodeBlock,
-                table: ({
-                  children,
-                  ...props
-                }: React.HTMLAttributes<HTMLTableElement>) => (
-                  <div className="overflow-x-auto max-w-full">
-                    <table {...props}>{children}</table>
-                  </div>
-                ),
-                // @ts-expect-error: custom type
-                "ol-citation": ({
-                  cursor,
-                  // start,
-                  // end,
-                }: {
-                  cursor: number;
-                  start: number;
-                  end: number;
-                }) => {
-                  // Check if we have a page_stack and if the cursor is valid
-                  const pageStack = browserToolResult?.page_stack;
-                  const hasValidPage = pageStack && cursor < pageStack.length;
-                  const pageUrl = hasValidPage ? pageStack[cursor] : null;
+          <Streamdown
+            parseIncompleteMarkdown={isStreaming}
+            isAnimating={isStreaming}
+            remarkPlugins={remarkPlugins}
+            controls={false}
+            components={{
+              pre: CodeBlock,
+              table: ({
+                children,
+                ...props
+              }: React.HTMLAttributes<HTMLTableElement>) => (
+                <div className="overflow-x-auto max-w-full">
+                  <table
+                    {...props}
+                    className="border-collapse w-full border border-neutral-200 dark:border-neutral-700 rounded-lg overflow-hidden"
+                  >
+                    {children}
+                  </table>
+                </div>
+              ),
+              // @ts-expect-error: custom citation type
+              "ol-citation": ({
+                cursor,
+              }: {
+                cursor: number;
+                start: number;
+                end: number;
+              }) => {
+                const pageStack = browserToolResult?.page_stack;
+                const hasValidPage = pageStack && cursor < pageStack.length;
+                const pageUrl = hasValidPage ? pageStack[cursor] : null;
 
-                  // Extract a readable title from the URL if possible
-                  const getPageTitle = (url: string) => {
-                    if (url.startsWith("search_results_")) {
-                      const searchTerm = url.substring(
-                        "search_results_".length,
-                      );
-                      return `Search: ${searchTerm}`;
-                    }
-                    // For regular URLs, try to extract domain or use full URL
-                    try {
-                      const urlObj = new URL(url);
-                      return urlObj.hostname;
-                    } catch {
-                      // If not a valid URL, return as is
-                      return url;
-                    }
-                  };
-
-                  const citationElement = (
-                    <span className="text-xs text-neutral-500 dark:text-neutral-400 bg-neutral-100 dark:bg-neutral-800 rounded-full px-2 py-1 ml-1">
-                      [{cursor}]
-                    </span>
-                  );
-
-                  // If we have a valid page URL, wrap in a link
-                  if (pageUrl && pageUrl.startsWith("http")) {
-                    return (
-                      <a
-                        href={pageUrl}
-                        target="_blank"
-                        rel="noopener noreferrer"
-                        className="inline-flex items-center hover:opacity-80 transition-opacity no-underline"
-                        title={getPageTitle(pageUrl)}
-                      >
-                        {citationElement}
-                      </a>
-                    );
+                const getPageTitle = (url: string) => {
+                  if (url.startsWith("search_results_")) {
+                    const searchTerm = url.substring("search_results_".length);
+                    return `Search: ${searchTerm}`;
                   }
+                  try {
+                    const urlObj = new URL(url);
+                    return urlObj.hostname;
+                  } catch {
+                    return url;
+                  }
+                };
 
-                  // Otherwise, just return the citation without a link
-                  return citationElement;
-                },
-              }}
-            >
-              {content}
-            </Markdown>
-          </StreamingMarkdownErrorBoundary>
-        </div>
-      );
-    },
-  );
+                const citationElement = (
+                  <span className="text-xs text-neutral-500 dark:text-neutral-400 bg-neutral-100 dark:bg-neutral-800 rounded-full px-2 py-1 ml-1">
+                    [{cursor}]
+                  </span>
+                );
+
+                if (pageUrl && pageUrl.startsWith("http")) {
+                  return (
+                    <a
+                      href={pageUrl}
+                      target="_blank"
+                      rel="noopener noreferrer"
+                      className="inline-flex items-center hover:opacity-80 transition-opacity no-underline"
+                      title={getPageTitle(pageUrl)}
+                    >
+                      {citationElement}
+                    </a>
+                  );
+                }
+
+                return citationElement;
+              },
+            }}
+          >
+            {content}
+          </Streamdown>
+        </StreamingMarkdownErrorBoundary>
+      </div>
+    );
+  });
 
 interface StreamingMarkdownErrorBoundaryProps {
   content: string;
diff --git a/app/ui/app/src/components/Thinking.tsx b/app/ui/app/src/components/Thinking.tsx
index a5ad3dc6..7ab23e72 100644
--- a/app/ui/app/src/components/Thinking.tsx
+++ b/app/ui/app/src/components/Thinking.tsx
@@ -73,8 +73,9 @@ export default function Thinking({
   // Calculate max height for smooth animations
   const getMaxHeight = () => {
     if (isCollapsed) {
-      return finishedThinking ? "0px" : "12rem"; // 8rem = 128px (same as max-h-32)
+      return finishedThinking ? "0px" : "12rem";
     }
+    // When expanded, use the content height or grow naturally
     return contentHeight ? `${contentHeight}px` : "none";
   };
 
@@ -131,10 +132,11 @@ export default function Thinking({
       </div>
       <div
         ref={wrapperRef}
-        className={`text-xs text-neutral-500 dark:text-neutral-500 rounded-md overflow-hidden
-          transition-[max-height,opacity] duration-300 ease-in-out relative ml-6 mt-2`}
+        className={`text-xs text-neutral-500 dark:text-neutral-500 rounded-md
+          transition-[max-height,opacity] duration-300 ease-in-out relative ml-6 mt-2
+          ${isCollapsed ? "overflow-hidden" : "overflow-y-auto"}`}
         style={{
-          maxHeight: getMaxHeight(),
+          maxHeight: isCollapsed ? getMaxHeight() : undefined,
           opacity: isCollapsed && finishedThinking ? 0 : 1,
         }}
       >
diff --git a/app/ui/app/src/index.css b/app/ui/app/src/index.css
index 0493d51c..af1f265d 100644
--- a/app/ui/app/src/index.css
+++ b/app/ui/app/src/index.css
@@ -16,793 +16,6 @@
     --text-color: #ffffff;
   }
 }
-@media (prefers-color-scheme: light) {
-  .prose {
-    /**
-    * One Light theme for prism.js
-    * Based on Atom's One Light theme: https://github.com/atom/atom/tree/master/packages/one-light-syntax
-    */
-
-    /**
-    * One Light colours (accurate as of commit eb064bf on 19 Feb 2021)
-    * From colors.less
-    * --mono-1: hsl(230, 8%, 24%);
-    * --mono-2: hsl(230, 6%, 44%);
-    * --mono-3: hsl(230, 4%, 64%)
-    * --hue-1: hsl(198, 99%, 37%);
-    * --hue-2: hsl(221, 87%, 60%);
-    * --hue-3: hsl(301, 63%, 40%);
-    * --hue-4: hsl(119, 34%, 47%);
-    * --hue-5: hsl(5, 74%, 59%);
-    * --hue-5-2: hsl(344, 84%, 43%);
-    * --hue-6: hsl(35, 99%, 36%);
-    * --hue-6-2: hsl(35, 99%, 40%);
-    * --syntax-fg: hsl(230, 8%, 24%);
-    * --syntax-bg: hsl(230, 1%, 98%);
-    * --syntax-gutter: hsl(230, 1%, 62%);
-    * --syntax-guide: hsla(230, 8%, 24%, 0.2);
-    * --syntax-accent: hsl(230, 100%, 66%);
-    * From syntax-variables.less
-    * --syntax-selection-color: hsl(230, 1%, 90%);
-    * --syntax-gutter-background-color-selected: hsl(230, 1%, 90%);
-    * --syntax-cursor-line: hsla(230, 8%, 24%, 0.05);
-    */
-
-    .token.comment,
-    .token.prolog,
-    .token.cdata {
-      color: hsl(230, 4%, 64%);
-    }
-
-    .token.doctype,
-    .token.punctuation,
-    .token.entity {
-      color: hsl(230, 8%, 24%);
-    }
-
-    .token.attr-name,
-    .token.class-name,
-    .token.boolean,
-    .token.constant,
-    .token.number,
-    .token.atrule {
-      color: hsl(35, 99%, 36%);
-    }
-
-    .token.keyword {
-      color: hsl(301, 63%, 40%);
-    }
-
-    .token.property,
-    .token.tag,
-    .token.symbol,
-    .token.deleted,
-    .token.important {
-      color: hsl(5, 74%, 59%);
-    }
-
-    .token.selector,
-    .token.string,
-    .token.char,
-    .token.builtin,
-    .token.inserted,
-    .token.regex,
-    .token.attr-value,
-    .token.attr-value > .token.punctuation {
-      color: hsl(119, 34%, 47%);
-    }
-
-    .token.variable,
-    .token.operator,
-    .token.function {
-      color: hsl(221, 87%, 60%);
-    }
-
-    .token.url {
-      color: hsl(198, 99%, 37%);
-    }
-
-    /* HTML overrides */
-    .token.attr-value > .token.punctuation.attr-equals,
-    .token.special-attr > .token.attr-value > .token.value.css {
-      color: hsl(230, 8%, 24%);
-    }
-
-    /* CSS overrides */
-    .language-css .token.selector {
-      color: hsl(5, 74%, 59%);
-    }
-
-    .language-css .token.property {
-      color: hsl(230, 8%, 24%);
-    }
-
-    .language-css .token.function,
-    .language-css .token.url > .token.function {
-      color: hsl(198, 99%, 37%);
-    }
-
-    .language-css .token.url > .token.string.url {
-      color: hsl(119, 34%, 47%);
-    }
-
-    .language-css .token.important,
-    .language-css .token.atrule .token.rule {
-      color: hsl(301, 63%, 40%);
-    }
-
-    /* JS overrides */
-    .language-javascript .token.operator {
-      color: hsl(301, 63%, 40%);
-    }
-
-    .language-javascript
-      .token.template-string
-      > .token.interpolation
-      > .token.interpolation-punctuation.punctuation {
-      color: hsl(344, 84%, 43%);
-    }
-
-    /* JSON overrides */
-    .language-json .token.operator {
-      color: hsl(230, 8%, 24%);
-    }
-
-    .language-json .token.null.keyword {
-      color: hsl(35, 99%, 36%);
-    }
-
-    /* MD overrides */
-    .language-markdown .token.url,
-    .language-markdown .token.url > .token.operator,
-    .language-markdown .token.url-reference.url > .token.string {
-      color: hsl(230, 8%, 24%);
-    }
-
-    .language-markdown .token.url > .token.content {
-      color: hsl(221, 87%, 60%);
-    }
-
-    .language-markdown .token.url > .token.url,
-    .language-markdown .token.url-reference.url {
-      color: hsl(198, 99%, 37%);
-    }
-
-    .language-markdown .token.blockquote.punctuation,
-    .language-markdown .token.hr.punctuation {
-      color: hsl(230, 4%, 64%);
-      font-style: italic;
-    }
-
-    .language-markdown .token.code-snippet {
-      color: hsl(119, 34%, 47%);
-    }
-
-    .language-markdown .token.bold .token.content {
-      color: hsl(35, 99%, 36%);
-    }
-
-    .language-markdown .token.italic .token.content {
-      color: hsl(301, 63%, 40%);
-    }
-
-    .language-markdown .token.strike .token.content,
-    .language-markdown .token.strike .token.punctuation,
-    .language-markdown .token.list.punctuation,
-    .language-markdown .token.title.important > .token.punctuation {
-      color: hsl(5, 74%, 59%);
-    }
-
-    /* General */
-    .token.bold {
-      font-weight: bold;
-    }
-
-    .token.comment,
-    .token.italic {
-      font-style: italic;
-    }
-
-    .token.entity {
-      cursor: help;
-    }
-
-    .token.namespace {
-      opacity: 0.8;
-    }
-
-    /* Plugin overrides */
-    /* Selectors should have higher specificity than those in the plugins' default stylesheets */
-
-    /* Show Invisibles plugin overrides */
-    .token.token.tab:not(:empty):before,
-    .token.token.cr:before,
-    .token.token.lf:before,
-    .token.token.space:before {
-      color: hsla(230, 8%, 24%, 0.2);
-    }
-
-    /* Toolbar plugin overrides */
-    /* Space out all buttons and move them away from the right edge of the code block */
-    div.code-toolbar > .toolbar.toolbar > .toolbar-item {
-      margin-right: 0.4em;
-    }
-
-    /* Styling the buttons */
-    div.code-toolbar > .toolbar.toolbar > .toolbar-item > button,
-    div.code-toolbar > .toolbar.toolbar > .toolbar-item > a,
-    div.code-toolbar > .toolbar.toolbar > .toolbar-item > span {
-      background: hsl(230, 1%, 90%);
-      color: hsl(230, 6%, 44%);
-      padding: 0.1em 0.4em;
-      border-radius: 0.3em;
-    }
-
-    div.code-toolbar > .toolbar.toolbar > .toolbar-item > button:hover,
-    div.code-toolbar > .toolbar.toolbar > .toolbar-item > button:focus,
-    div.code-toolbar > .toolbar.toolbar > .toolbar-item > a:hover,
-    div.code-toolbar > .toolbar.toolbar > .toolbar-item > a:focus,
-    div.code-toolbar > .toolbar.toolbar > .toolbar-item > span:hover,
-    div.code-toolbar > .toolbar.toolbar > .toolbar-item > span:focus {
-      background: hsl(230, 1%, 78%); /* custom: darken(--syntax-bg, 20%) */
-      color: hsl(230, 8%, 24%);
-    }
-
-    /* Line Highlight plugin overrides */
-    /* The highlighted line itself */
-    .line-highlight.line-highlight {
-      background: hsla(230, 8%, 24%, 0.05);
-    }
-
-    /* Default line numbers in Line Highlight plugin */
-    .line-highlight.line-highlight:before,
-    .line-highlight.line-highlight[data-end]:after {
-      background: hsl(230, 1%, 90%);
-      color: hsl(230, 8%, 24%);
-      padding: 0.1em 0.6em;
-      border-radius: 0.3em;
-      box-shadow: 0 2px 0 0 rgba(0, 0, 0, 0.2); /* same as Toolbar plugin default */
-    }
-
-    /* Hovering over a linkable line number (in the gutter area) */
-    /* Requires Line Numbers plugin as well */
-    pre[id].linkable-line-numbers.linkable-line-numbers
-      span.line-numbers-rows
-      > span:hover:before {
-      background-color: hsla(230, 8%, 24%, 0.05);
-    }
-
-    /* Line Numbers and Command Line plugins overrides */
-    /* Line separating gutter from coding area */
-    .line-numbers.line-numbers .line-numbers-rows,
-    .command-line .command-line-prompt {
-      border-right-color: hsla(230, 8%, 24%, 0.2);
-    }
-
-    /* Stuff in the gutter */
-    .line-numbers .line-numbers-rows > span:before,
-    .command-line .command-line-prompt > span:before {
-      color: hsl(230, 1%, 62%);
-    }
-
-    /* Match Braces plugin overrides */
-    /* Note: Outline colour is inherited from the braces */
-    .rainbow-braces .token.token.punctuation.brace-level-1,
-    .rainbow-braces .token.token.punctuation.brace-level-5,
-    .rainbow-braces .token.token.punctuation.brace-level-9 {
-      color: hsl(5, 74%, 59%);
-    }
-
-    .rainbow-braces .token.token.punctuation.brace-level-2,
-    .rainbow-braces .token.token.punctuation.brace-level-6,
-    .rainbow-braces .token.token.punctuation.brace-level-10 {
-      color: hsl(119, 34%, 47%);
-    }
-
-    .rainbow-braces .token.token.punctuation.brace-level-3,
-    .rainbow-braces .token.token.punctuation.brace-level-7,
-    .rainbow-braces .token.token.punctuation.brace-level-11 {
-      color: hsl(221, 87%, 60%);
-    }
-
-    .rainbow-braces .token.token.punctuation.brace-level-4,
-    .rainbow-braces .token.token.punctuation.brace-level-8,
-    .rainbow-braces .token.token.punctuation.brace-level-12 {
-      color: hsl(301, 63%, 40%);
-    }
-
-    /* Diff Highlight plugin overrides */
-    /* Taken from https://github.com/atom/github/blob/master/styles/variables.less */
-    pre.diff-highlight > code .token.token.deleted:not(.prefix),
-    pre > code.diff-highlight .token.token.deleted:not(.prefix) {
-      background-color: hsla(353, 100%, 66%, 0.15);
-    }
-
-    pre.diff-highlight > code .token.token.deleted:not(.prefix)::-moz-selection,
-    pre.diff-highlight
-      > code
-      .token.token.deleted:not(.prefix)
-      *::-moz-selection,
-    pre > code.diff-highlight .token.token.deleted:not(.prefix)::-moz-selection,
-    pre
-      > code.diff-highlight
-      .token.token.deleted:not(.prefix)
-      *::-moz-selection {
-      background-color: hsla(353, 95%, 66%, 0.25);
-    }
-
-    pre.diff-highlight > code .token.token.deleted:not(.prefix)::selection,
-    pre.diff-highlight > code .token.token.deleted:not(.prefix) *::selection,
-    pre > code.diff-highlight .token.token.deleted:not(.prefix)::selection,
-    pre > code.diff-highlight .token.token.deleted:not(.prefix) *::selection {
-      background-color: hsla(353, 95%, 66%, 0.25);
-    }
-
-    pre.diff-highlight > code .token.token.inserted:not(.prefix),
-    pre > code.diff-highlight .token.token.inserted:not(.prefix) {
-      background-color: hsla(137, 100%, 55%, 0.15);
-    }
-
-    pre.diff-highlight
-      > code
-      .token.token.inserted:not(.prefix)::-moz-selection,
-    pre.diff-highlight
-      > code
-      .token.token.inserted:not(.prefix)
-      *::-moz-selection,
-    pre
-      > code.diff-highlight
-      .token.token.inserted:not(.prefix)::-moz-selection,
-    pre
-      > code.diff-highlight
-      .token.token.inserted:not(.prefix)
-      *::-moz-selection {
-      background-color: hsla(135, 73%, 55%, 0.25);
-    }
-
-    pre.diff-highlight > code .token.token.inserted:not(.prefix)::selection,
-    pre.diff-highlight > code .token.token.inserted:not(.prefix) *::selection,
-    pre > code.diff-highlight .token.token.inserted:not(.prefix)::selection,
-    pre > code.diff-highlight .token.token.inserted:not(.prefix) *::selection {
-      background-color: hsla(135, 73%, 55%, 0.25);
-    }
-
-    /* Previewers plugin overrides */
-    /* Based on https://github.com/atom-community/atom-ide-datatip/blob/master/styles/atom-ide-datatips.less and https://github.com/atom/atom/blob/master/packages/one-light-ui */
-    /* Border around popup */
-    .prism-previewer.prism-previewer:before,
-    .prism-previewer-gradient.prism-previewer-gradient div {
-      border-color: hsl(0, 0, 95%);
-    }
-
-    /* Angle and time should remain as circles and are hence not included */
-    .prism-previewer-color.prism-previewer-color:before,
-    .prism-previewer-gradient.prism-previewer-gradient div,
-    .prism-previewer-easing.prism-previewer-easing:before {
-      border-radius: 0.3em;
-    }
-
-    /* Triangles pointing to the code */
-    .prism-previewer.prism-previewer:after {
-      border-top-color: hsl(0, 0, 95%);
-    }
-
-    .prism-previewer-flipped.prism-previewer-flipped.after {
-      border-bottom-color: hsl(0, 0, 95%);
-    }
-
-    /* Background colour within the popup */
-    .prism-previewer-angle.prism-previewer-angle:before,
-    .prism-previewer-time.prism-previewer-time:before,
-    .prism-previewer-easing.prism-previewer-easing {
-      background: hsl(0, 0%, 100%);
-    }
-
-    /* For angle, this is the positive area (eg. 90deg will display one quadrant in this colour) */
-    /* For time, this is the alternate colour */
-    .prism-previewer-angle.prism-previewer-angle circle,
-    .prism-previewer-time.prism-previewer-time circle {
-      stroke: hsl(230, 8%, 24%);
-      stroke-opacity: 1;
-    }
-
-    /* Stroke colours of the handle, direction point, and vector itself */
-    .prism-previewer-easing.prism-previewer-easing circle,
-    .prism-previewer-easing.prism-previewer-easing path,
-    .prism-previewer-easing.prism-previewer-easing line {
-      stroke: hsl(230, 8%, 24%);
-    }
-
-    /* Fill colour of the handle */
-    .prism-previewer-easing.prism-previewer-easing circle {
-      fill: transparent;
-    }
-  }
-}
-
-@media (prefers-color-scheme: dark) {
-  .prose {
-    .token.comment,
-    .token.prolog,
-    .token.cdata {
-      color: hsl(220, 10%, 40%);
-    }
-
-    .token.doctype,
-    .token.punctuation,
-    .token.entity {
-      color: hsl(220, 14%, 71%);
-    }
-
-    .token.attr-name,
-    .token.class-name,
-    .token.boolean,
-    .token.constant,
-    .token.number,
-    .token.atrule {
-      color: hsl(29, 54%, 61%);
-    }
-
-    .token.keyword {
-      color: hsl(286, 60%, 67%);
-    }
-
-    .token.property,
-    .token.tag,
-    .token.symbol,
-    .token.deleted,
-    .token.important {
-      color: hsl(355, 65%, 65%);
-    }
-
-    .token.selector,
-    .token.string,
-    .token.char,
-    .token.builtin,
-    .token.inserted,
-    .token.regex,
-    .token.attr-value,
-    .token.attr-value > .token.punctuation {
-      color: hsl(95, 38%, 62%);
-    }
-
-    .token.variable,
-    .token.operator,
-    .token.function {
-      color: hsl(207, 82%, 66%);
-    }
-
-    .token.url {
-      color: hsl(187, 47%, 55%);
-    }
-
-    /* HTML overrides */
-    .token.attr-value > .token.punctuation.attr-equals,
-    .token.special-attr > .token.attr-value > .token.value.css {
-      color: hsl(220, 14%, 71%);
-    }
-
-    /* CSS overrides */
-    .language-css .token.selector {
-      color: hsl(355, 65%, 65%);
-    }
-
-    .language-css .token.property {
-      color: hsl(220, 14%, 71%);
-    }
-
-    .language-css .token.function,
-    .language-css .token.url > .token.function {
-      color: hsl(187, 47%, 55%);
-    }
-
-    .language-css .token.url > .token.string.url {
-      color: hsl(95, 38%, 62%);
-    }
-
-    .language-css .token.important,
-    .language-css .token.atrule .token.rule {
-      color: hsl(286, 60%, 67%);
-    }
-
-    /* JS overrides */
-    .language-javascript .token.operator {
-      color: hsl(286, 60%, 67%);
-    }
-
-    .language-javascript
-      .token.template-string
-      > .token.interpolation
-      > .token.interpolation-punctuation.punctuation {
-      color: hsl(5, 48%, 51%);
-    }
-
-    /* JSON overrides */
-    .language-json .token.operator {
-      color: hsl(220, 14%, 71%);
-    }
-
-    .language-json .token.null.keyword {
-      color: hsl(29, 54%, 61%);
-    }
-
-    /* MD overrides */
-    .language-markdown .token.url,
-    .language-markdown .token.url > .token.operator,
-    .language-markdown .token.url-reference.url > .token.string {
-      color: hsl(220, 14%, 71%);
-    }
-
-    .language-markdown .token.url > .token.content {
-      color: hsl(207, 82%, 66%);
-    }
-
-    .language-markdown .token.url > .token.url,
-    .language-markdown .token.url-reference.url {
-      color: hsl(187, 47%, 55%);
-    }
-
-    .language-markdown .token.blockquote.punctuation,
-    .language-markdown .token.hr.punctuation {
-      color: hsl(220, 10%, 40%);
-      font-style: italic;
-    }
-
-    .language-markdown .token.code-snippet {
-      color: hsl(95, 38%, 62%);
-    }
-
-    .language-markdown .token.bold .token.content {
-      color: hsl(29, 54%, 61%);
-    }
-
-    .language-markdown .token.italic .token.content {
-      color: hsl(286, 60%, 67%);
-    }
-
-    .language-markdown .token.strike .token.content,
-    .language-markdown .token.strike .token.punctuation,
-    .language-markdown .token.list.punctuation,
-    .language-markdown .token.title.important > .token.punctuation {
-      color: hsl(355, 65%, 65%);
-    }
-
-    /* General */
-    .token.bold {
-      font-weight: bold;
-    }
-
-    .token.comment,
-    .token.italic {
-      font-style: italic;
-    }
-
-    .token.entity {
-      cursor: help;
-    }
-
-    .token.namespace {
-      opacity: 0.8;
-    }
-
-    /* Plugin overrides */
-    /* Selectors should have higher specificity than those in the plugins' default stylesheets */
-
-    /* Show Invisibles plugin overrides */
-    .token.token.tab:not(:empty):before,
-    .token.token.cr:before,
-    .token.token.lf:before,
-    .token.token.space:before {
-      color: hsla(220, 14%, 71%, 0.15);
-      text-shadow: none;
-    }
-
-    /* Toolbar plugin overrides */
-    /* Space out all buttons and move them away from the right edge of the code block */
-    div.code-toolbar > .toolbar.toolbar > .toolbar-item {
-      margin-right: 0.4em;
-    }
-
-    /* Styling the buttons */
-    div.code-toolbar > .toolbar.toolbar > .toolbar-item > button,
-    div.code-toolbar > .toolbar.toolbar > .toolbar-item > a,
-    div.code-toolbar > .toolbar.toolbar > .toolbar-item > span {
-      background: hsl(220, 13%, 26%);
-      color: hsl(220, 9%, 55%);
-      padding: 0.1em 0.4em;
-      border-radius: 0.3em;
-    }
-
-    div.code-toolbar > .toolbar.toolbar > .toolbar-item > button:hover,
-    div.code-toolbar > .toolbar.toolbar > .toolbar-item > button:focus,
-    div.code-toolbar > .toolbar.toolbar > .toolbar-item > a:hover,
-    div.code-toolbar > .toolbar.toolbar > .toolbar-item > a:focus,
-    div.code-toolbar > .toolbar.toolbar > .toolbar-item > span:hover,
-    div.code-toolbar > .toolbar.toolbar > .toolbar-item > span:focus {
-      background: hsl(220, 13%, 28%);
-      color: hsl(220, 14%, 71%);
-    }
-
-    /* Line Highlight plugin overrides */
-    /* The highlighted line itself */
-    .line-highlight.line-highlight {
-      background: hsla(220, 100%, 80%, 0.04);
-    }
-
-    /* Default line numbers in Line Highlight plugin */
-    .line-highlight.line-highlight:before,
-    .line-highlight.line-highlight[data-end]:after {
-      background: hsl(220, 13%, 26%);
-      color: hsl(220, 14%, 71%);
-      padding: 0.1em 0.6em;
-      border-radius: 0.3em;
-      box-shadow: 0 2px 0 0 rgba(0, 0, 0, 0.2); /* same as Toolbar plugin default */
-    }
-
-    /* Hovering over a linkable line number (in the gutter area) */
-    /* Requires Line Numbers plugin as well */
-    pre[id].linkable-line-numbers.linkable-line-numbers
-      span.line-numbers-rows
-      > span:hover:before {
-      background-color: hsla(220, 100%, 80%, 0.04);
-    }
-
-    /* Line Numbers and Command Line plugins overrides */
-    /* Line separating gutter from coding area */
-    .line-numbers.line-numbers .line-numbers-rows,
-    .command-line .command-line-prompt {
-      border-right-color: hsla(220, 14%, 71%, 0.15);
-    }
-
-    /* Stuff in the gutter */
-    .line-numbers .line-numbers-rows > span:before,
-    .command-line .command-line-prompt > span:before {
-      color: hsl(220, 14%, 45%);
-    }
-
-    /* Match Braces plugin overrides */
-    /* Note: Outline colour is inherited from the braces */
-    .rainbow-braces .token.token.punctuation.brace-level-1,
-    .rainbow-braces .token.token.punctuation.brace-level-5,
-    .rainbow-braces .token.token.punctuation.brace-level-9 {
-      color: hsl(355, 65%, 65%);
-    }
-
-    .rainbow-braces .token.token.punctuation.brace-level-2,
-    .rainbow-braces .token.token.punctuation.brace-level-6,
-    .rainbow-braces .token.token.punctuation.brace-level-10 {
-      color: hsl(95, 38%, 62%);
-    }
-
-    .rainbow-braces .token.token.punctuation.brace-level-3,
-    .rainbow-braces .token.token.punctuation.brace-level-7,
-    .rainbow-braces .token.token.punctuation.brace-level-11 {
-      color: hsl(207, 82%, 66%);
-    }
-
-    .rainbow-braces .token.token.punctuation.brace-level-4,
-    .rainbow-braces .token.token.punctuation.brace-level-8,
-    .rainbow-braces .token.token.punctuation.brace-level-12 {
-      color: hsl(286, 60%, 67%);
-    }
-
-    /* Diff Highlight plugin overrides */
-    /* Taken from https://github.com/atom/github/blob/master/styles/variables.less */
-    pre.diff-highlight > code .token.token.deleted:not(.prefix),
-    pre > code.diff-highlight .token.token.deleted:not(.prefix) {
-      background-color: hsla(353, 100%, 66%, 0.15);
-    }
-
-    pre.diff-highlight > code .token.token.deleted:not(.prefix)::-moz-selection,
-    pre.diff-highlight
-      > code
-      .token.token.deleted:not(.prefix)
-      *::-moz-selection,
-    pre > code.diff-highlight .token.token.deleted:not(.prefix)::-moz-selection,
-    pre
-      > code.diff-highlight
-      .token.token.deleted:not(.prefix)
-      *::-moz-selection {
-      background-color: hsla(353, 95%, 66%, 0.25);
-    }
-
-    pre.diff-highlight > code .token.token.deleted:not(.prefix)::selection,
-    pre.diff-highlight > code .token.token.deleted:not(.prefix) *::selection,
-    pre > code.diff-highlight .token.token.deleted:not(.prefix)::selection,
-    pre > code.diff-highlight .token.token.deleted:not(.prefix) *::selection {
-      background-color: hsla(353, 95%, 66%, 0.25);
-    }
-
-    pre.diff-highlight > code .token.token.inserted:not(.prefix),
-    pre > code.diff-highlight .token.token.inserted:not(.prefix) {
-      background-color: hsla(137, 100%, 55%, 0.15);
-    }
-
-    pre.diff-highlight
-      > code
-      .token.token.inserted:not(.prefix)::-moz-selection,
-    pre.diff-highlight
-      > code
-      .token.token.inserted:not(.prefix)
-      *::-moz-selection,
-    pre
-      > code.diff-highlight
-      .token.token.inserted:not(.prefix)::-moz-selection,
-    pre
-      > code.diff-highlight
-      .token.token.inserted:not(.prefix)
-      *::-moz-selection {
-      background-color: hsla(135, 73%, 55%, 0.25);
-    }
-
-    pre.diff-highlight > code .token.token.inserted:not(.prefix)::selection,
-    pre.diff-highlight > code .token.token.inserted:not(.prefix) *::selection,
-    pre > code.diff-highlight .token.token.inserted:not(.prefix)::selection,
-    pre > code.diff-highlight .token.token.inserted:not(.prefix) *::selection {
-      background-color: hsla(135, 73%, 55%, 0.25);
-    }
-
-    /* Previewers plugin overrides */
-    /* Based on https://github.com/atom-community/atom-ide-datatip/blob/master/styles/atom-ide-datatips.less and https://github.com/atom/atom/blob/master/packages/one-dark-ui */
-    /* Border around popup */
-    .prism-previewer.prism-previewer:before,
-    .prism-previewer-gradient.prism-previewer-gradient div {
-      border-color: hsl(224, 13%, 17%);
-    }
-
-    /* Angle and time should remain as circles and are hence not included */
-    .prism-previewer-color.prism-previewer-color:before,
-    .prism-previewer-gradient.prism-previewer-gradient div,
-    .prism-previewer-easing.prism-previewer-easing:before {
-      border-radius: 0.3em;
-    }
-
-    /* Triangles pointing to the code */
-    .prism-previewer.prism-previewer:after {
-      border-top-color: hsl(224, 13%, 17%);
-    }
-
-    .prism-previewer-flipped.prism-previewer-flipped.after {
-      border-bottom-color: hsl(224, 13%, 17%);
-    }
-
-    /* Background colour within the popup */
-    .prism-previewer-angle.prism-previewer-angle:before,
-    .prism-previewer-time.prism-previewer-time:before,
-    .prism-previewer-easing.prism-previewer-easing {
-      background: hsl(219, 13%, 22%);
-    }
-
-    /* For angle, this is the positive area (eg. 90deg will display one quadrant in this colour) */
-    /* For time, this is the alternate colour */
-    .prism-previewer-angle.prism-previewer-angle circle,
-    .prism-previewer-time.prism-previewer-time circle {
-      stroke: hsl(220, 14%, 71%);
-      stroke-opacity: 1;
-    }
-
-    /* Stroke colours of the handle, direction point, and vector itself */
-    .prism-previewer-easing.prism-previewer-easing circle,
-    .prism-previewer-easing.prism-previewer-easing path,
-    .prism-previewer-easing.prism-previewer-easing line {
-      stroke: hsl(220, 14%, 71%);
-    }
-
-    /* Fill colour of the handle */
-    .prism-previewer-easing.prism-previewer-easing circle {
-      fill: transparent;
-    }
-  }
-}
-
-.prose pre {
-  contain: layout style;
-}
-
-/* Or more aggressively */
-.prose pre code {
-  contain: layout style paint;
-}
 
 /* messaging-style typing indicator animation */
 @keyframes typing {
diff --git a/app/ui/app/src/lib/highlighter.ts b/app/ui/app/src/lib/highlighter.ts
new file mode 100644
index 00000000..279bc746
--- /dev/null
+++ b/app/ui/app/src/lib/highlighter.ts
@@ -0,0 +1,156 @@
+import { createHighlighter } from "shiki";
+import type { ThemeRegistration } from "shiki";
+
+const oneLightTheme: ThemeRegistration = {
+  name: "one-light",
+  type: "light",
+  colors: {
+    "editor.background": "#fafafa",
+    "editor.foreground": "#383a42",
+  },
+  tokenColors: [
+    {
+      scope: ["comment", "punctuation.definition.comment"],
+      settings: { foreground: "#a0a1a7" },
+    },
+    {
+      scope: ["keyword", "storage.type", "storage.modifier"],
+      settings: { foreground: "#a626a4" },
+    },
+    { scope: ["string", "string.quoted"], settings: { foreground: "#50a14f" } },
+    {
+      scope: ["function", "entity.name.function", "support.function"],
+      settings: { foreground: "#4078f2" },
+    },
+    {
+      scope: [
+        "constant.numeric",
+        "constant.language",
+        "constant.character",
+        "number",
+      ],
+      settings: { foreground: "#c18401" },
+    },
+    {
+      scope: ["variable", "support.variable"],
+      settings: { foreground: "#e45649" },
+    },
+    {
+      scope: ["entity.name.tag", "entity.name.type", "entity.name.class"],
+      settings: { foreground: "#e45649" },
+    },
+    {
+      scope: ["entity.other.attribute-name"],
+      settings: { foreground: "#c18401" },
+    },
+    {
+      scope: ["keyword.operator", "operator"],
+      settings: { foreground: "#a626a4" },
+    },
+    { scope: ["punctuation"], settings: { foreground: "#383a42" } },
+    {
+      scope: ["markup.heading"],
+      settings: { foreground: "#e45649", fontStyle: "bold" },
+    },
+    {
+      scope: ["markup.bold"],
+      settings: { foreground: "#c18401", fontStyle: "bold" },
+    },
+    {
+      scope: ["markup.italic"],
+      settings: { foreground: "#a626a4", fontStyle: "italic" },
+    },
+  ],
+};
+
+const oneDarkTheme: ThemeRegistration = {
+  name: "one-dark",
+  type: "dark",
+  colors: {
+    "editor.background": "#282c34",
+    "editor.foreground": "#abb2bf",
+  },
+  tokenColors: [
+    {
+      scope: ["comment", "punctuation.definition.comment"],
+      settings: { foreground: "#5c6370" },
+    },
+    {
+      scope: ["keyword", "storage.type", "storage.modifier"],
+      settings: { foreground: "#c678dd" },
+    },
+    { scope: ["string", "string.quoted"], settings: { foreground: "#98c379" } },
+    {
+      scope: ["function", "entity.name.function", "support.function"],
+      settings: { foreground: "#61afef" },
+    },
+    {
+      scope: [
+        "constant.numeric",
+        "constant.language",
+        "constant.character",
+        "number",
+      ],
+      settings: { foreground: "#d19a66" },
+    },
+    {
+      scope: ["variable", "support.variable"],
+      settings: { foreground: "#e06c75" },
+    },
+    {
+      scope: ["entity.name.tag", "entity.name.type", "entity.name.class"],
+      settings: { foreground: "#e06c75" },
+    },
+    {
+      scope: ["entity.other.attribute-name"],
+      settings: { foreground: "#d19a66" },
+    },
+    {
+      scope: ["keyword.operator", "operator"],
+      settings: { foreground: "#c678dd" },
+    },
+    { scope: ["punctuation"], settings: { foreground: "#abb2bf" } },
+    {
+      scope: ["markup.heading"],
+      settings: { foreground: "#e06c75", fontStyle: "bold" },
+    },
+    {
+      scope: ["markup.bold"],
+      settings: { foreground: "#d19a66", fontStyle: "bold" },
+    },
+    {
+      scope: ["markup.italic"],
+      settings: { foreground: "#c678dd", fontStyle: "italic" },
+    },
+  ],
+};
+
+export let highlighter: Awaited<ReturnType<typeof createHighlighter>> | null =
+  null;
+
+export const highlighterPromise = createHighlighter({
+  themes: [oneLightTheme, oneDarkTheme],
+  langs: [
+    "javascript",
+    "typescript",
+    "python",
+    "bash",
+    "shell",
+    "json",
+    "html",
+    "css",
+    "tsx",
+    "jsx",
+    "go",
+    "rust",
+    "java",
+    "c",
+    "cpp",
+    "sql",
+    "yaml",
+    "markdown",
+  ],
+}).then((h) => {
+  highlighter = h;
+  return h;
+});
diff --git a/app/ui/app/src/utils/processStreamingMarkdown.ts b/app/ui/app/src/utils/processStreamingMarkdown.ts
deleted file mode 100644
index faab9b5c..00000000
--- a/app/ui/app/src/utils/processStreamingMarkdown.ts
+++ /dev/null
@@ -1,24 +0,0 @@
-import { remark } from "remark";
-import remarkStringify from "remark-stringify";
-import remarkStreamingMarkdown from "./remarkStreamingMarkdown";
-
-/**
- * Process markdown content for streaming display using the remark plugin.
- * This is primarily used for testing the remark plugin with string inputs/outputs.
- */
-export function processStreamingMarkdown(content: string): string {
-  if (!content) return content;
-
-  const result = remark()
-    .use(remarkStreamingMarkdown, { debug: false })
-    .use(remarkStringify)
-    .processSync(content);
-
-  // remove trailing newline to keep tests cleaner
-  let output = result.toString();
-  if (output.endsWith("\n")) {
-    output = output.slice(0, -1);
-  }
-
-  return output;
-}
diff --git a/app/ui/app/src/utils/remarkStreamingMarkdown.ts b/app/ui/app/src/utils/remarkStreamingMarkdown.ts
deleted file mode 100644
index 6b6d4cd7..00000000
--- a/app/ui/app/src/utils/remarkStreamingMarkdown.ts
+++ /dev/null
@@ -1,447 +0,0 @@
-import { parents, type Proxy } from "unist-util-parents";
-import type { Plugin } from "unified";
-import type {
-  Emphasis,
-  Node,
-  Parent,
-  Root,
-  RootContent,
-  Text,
-  Strong,
-  PhrasingContent,
-  Paragraph,
-} from "mdast";
-import { u } from "unist-builder";
-
-declare module "unist" {
-  interface Node {
-    /** Added by `unist-util-parents` (or your own walk). */
-    parent?: Proxy & Parent;
-  }
-}
-
-// interface SimpleTextRule {
-//   pattern: RegExp;
-//   transform: (matches: RegExpExecArray[], lastNode: Proxy) => void;
-// }
-
-// const simpleTextRules: SimpleTextRule[] = [
-//   // TODO(drifkin): generalize this for `__`/`_`/`~~`/`~` etc.
-//   {
-//     pattern: /(\*\*)(?=\S|$)/g,
-//     transform: (matchesIterator, lastNode) => {
-//       const textNode = lastNode.node as Text;
-
-//       const matches = [...matchesIterator];
-//       const lastMatch = matches[matches.length - 1];
-//       const origValue = textNode.value;
-//       const start = lastMatch.index;
-//       const sep = lastMatch[1];
-
-//       const before = origValue.slice(0, start);
-//       const after = origValue.slice(start + sep.length);
-
-//       if (lastNode.parent) {
-//         const index = (lastNode.parent.node as Parent).children.indexOf(
-//           lastNode.node as RootContent,
-//         );
-//         const shouldRemove = before.length === 0;
-//         if (!shouldRemove) {
-//           textNode.value = before;
-//         }
-
-//         const newNode = u("strong", {
-//           children: [u("text", { value: after })],
-//         });
-//         (lastNode.parent.node as Parent).children.splice(
-//           index + (shouldRemove ? 0 : 1),
-//           shouldRemove ? 1 : 0,
-//           newNode,
-//         );
-//       }
-//     },
-//   },
-// ];
-
-interface Options {
-  debug?: boolean;
-  onLastNode?: (info: LastNodeInfo) => void;
-}
-
-export interface LastNodeInfo {
-  path: string[];
-  type: string;
-  value?: string;
-  lastChars?: string;
-  fullNode: Node;
-}
-
-/**
- * Removes `child` from `parent` in-place.
- * @returns `true` if the child was found and removed; `false` otherwise.
- */
-export function removeChildFromParent(
-  child: RootContent,
-  parent: Node,
-): boolean {
-  if (!isParent(parent)) return false; // parent isn’t a Parent → nothing to do
-
-  const idx = parent.children.indexOf(child);
-  if (idx < 0) return false; // not a child → nothing to remove
-
-  parent.children.splice(idx, 1);
-  return true; // removal successful
-}
-
-/** Narrow a generic `Node` to a `Parent` (i.e. one that really has children). */
-function isParent(node: Node): node is Parent {
-  // A `Parent` always has a `children` array; make sure it's an array first.
-  return Array.isArray((node as Partial<Parent>).children);
-}
-
-/**
- * Follow “last-child” pointers until you reach a leaf.
- * Returns the right-most, deepest node in source order.
- */
-export function findRightmostDeepestNode(root: Node): Node {
-  let current: Node = root;
-
-  // While the current node *is* a Parent and has at least one child…
-  while (isParent(current) && current.children.length > 0) {
-    const lastIndex = current.children.length - 1;
-    current = current.children[lastIndex];
-  }
-
-  return current; // Leaf: no further children
-}
-
-const remarkStreamingMarkdown: Plugin<[Options?], Root> = () => {
-  return (tree) => {
-    const treeWithParents = parents(tree);
-    const lastNode = findRightmostDeepestNode(treeWithParents) as Proxy;
-
-    const parentNode = lastNode.parent;
-    const grandparentNode = parentNode?.parent;
-
-    let ruleMatched = false;
-
-    // handling `* *` -> ``
-    //
-    // if the last node is part of a <list item (otherwise empty)> ->
-    // <list (otherwise empty)> -> <list item (last node, empty)>, then we need to
-    // remove everything up to and including the first list item. This happens
-    // when we have `* *`, which can become a bolded list item OR a horizontal
-    // line
-    if (
-      lastNode.type === "listItem" &&
-      parentNode &&
-      grandparentNode &&
-      parentNode.type === "list" &&
-      grandparentNode.type === "listItem" &&
-      parentNode.children.length === 1 &&
-      grandparentNode.children.length === 1
-    ) {
-      ruleMatched = true;
-      if (grandparentNode.parent) {
-        removeChildFromParent(
-          grandparentNode.node as RootContent,
-          grandparentNode.parent.node,
-        );
-      }
-      // Handle `*` -> ``:
-      //
-      // if the last node is just an empty list item, we need to remove it
-      // because it could become something else (e.g., a horizontal line)
-    } else if (
-      lastNode.type === "listItem" &&
-      parentNode &&
-      parentNode.type === "list"
-    ) {
-      ruleMatched = true;
-      removeChildFromParent(lastNode.node as RootContent, parentNode.node);
-    } else if (lastNode.type === "thematicBreak") {
-      ruleMatched = true;
-      const parent = lastNode.parent;
-      if (parent) {
-        removeChildFromParent(lastNode.node as RootContent, parent.node);
-      }
-    } else if (lastNode.type === "text") {
-      const textNode = lastNode.node as Text;
-      if (textNode.value.endsWith("**")) {
-        ruleMatched = true;
-        textNode.value = textNode.value.slice(0, -2);
-        // if there's a newline then a number, this is very very likely a
-        // numbered list item. Let's just hide it until the period comes (or
-        // other text disambiguates it)
-      } else {
-        const match = textNode.value.match(/^([0-9]+)$/m);
-        if (match) {
-          const number = match[1];
-          textNode.value = textNode.value.slice(0, -number.length - 1);
-          ruleMatched = true;
-          // if the text node is now empty, then we might want to remove other
-          // elements, like a now-empty containing paragraph, or a break that
-          // might disappear once more tokens come in
-          if (textNode.value.length === 0) {
-            if (
-              lastNode.parent?.type === "paragraph" &&
-              lastNode.parent.children.length === 1
-            ) {
-              // remove the whole paragraph if it's now empty (otherwise it'll
-              // cause an extra newline that might not last)
-              removeChildFromParent(
-                lastNode.parent.node as Paragraph,
-                lastNode.parent.parent?.node as Node,
-              );
-            } else {
-              const prev = prevSibling(lastNode);
-              if (prev?.type === "break") {
-                removeChildFromParent(
-                  prev.node as RootContent,
-                  lastNode.parent?.node as Node,
-                );
-                removeChildFromParent(
-                  lastNode.node as RootContent,
-                  lastNode.parent?.node as Node,
-                );
-              }
-            }
-          }
-        }
-      }
-    }
-
-    if (ruleMatched) {
-      return tree;
-    }
-
-    // we need to
-    // a case like
-    //     - *def `abc` [abc **def**](abc)*
-    // is pretty tricky, because if we land just after def, then we actually
-    // have two separate tags to process at two different parents. Maybe we
-    // need to keep iterating up until we find a paragraph, but process each
-    // parent on the way up. Hmm, well actually after `def` we won't even be a proper link yet
-    // TODO(drifkin): it's really if the last node's parent is a paragraph, for which the following is a sub-cas where the lastNode is a text node.
-    // And instead of just processing simple text rules, they need to operate on the whole paragraph
-    // like `**[abc](def)` needs to become `**[abc](def)**`
-
-    // if we're just text at the end, then we should remove some ambiguous characters
-
-    if (lastNode.parent) {
-      const didChange = processParent(lastNode.parent as Parent & Proxy);
-      if (didChange) {
-        // TODO(drifkin): need to fix up the tree, but not sure lastNode will still exist? Check all the transforms to see if it's safe to find the last node again
-        //
-        // need to regen the tree w/ parents since reparenting could've happened
-        // treeWithParents = parents(tree);
-      }
-    }
-
-    const grandparent = lastNode.parent?.parent;
-    // TODO(drifkin): let's go arbitrarily high up the tree, but limiting it
-    // to 2 levels for now until I think more about the stop condition
-    if (grandparent) {
-      processParent(grandparent as Parent & Proxy);
-    }
-
-    // console.log("ruleMatched", ruleMatched);
-
-    // } else if (lastNode.parent?.type === "paragraph") {
-    //   console.log("!!! paragraph");
-    //   console.log("lastNode.parent", lastNode.parent);
-
-    //   // Handle `**abc*` -> `**abc**`:
-    //   // We detect this when the last child is an emphasis node, and it's preceded by a text node that ends with `*`
-    //   const paragraph = lastNode.parent as Proxy & Paragraph;
-    //   if (paragraph.children.length >= 2) {
-    //     const lastChild = paragraph.children[paragraph.children.length - 1];
-    //     if (lastChild.type === "emphasis") {
-    //       const sibling = paragraph.children[paragraph.children.length - 2];
-    //       if (sibling.type === "text") {
-    //         const siblingText = sibling as Text & Proxy;
-    //         if (siblingText.value.endsWith("*")) {
-    //           ruleMatched = true;
-    //           const textNode = (lastNode as Proxy).node as Text;
-    //           textNode.value = textNode.value.slice(0, -1);
-    //           paragraph.node.type = "strong";
-    //         }
-    //       }
-    //     }
-    //   }
-    // } else if (lastNode.type === "text") {
-    //   // Handle `**abc*` -> `**abc**`:
-    //   //
-    //   // this gets parsed as a text node ending in `*` followed by an emphasis
-    //   // node. So if we're in text, we need to check if our parent is emphasis,
-    //   // and then get our parent's sibling before it and check if it ends with
-    //   // `*`
-    //   const parent = lastNode.parent;
-    //   if (parent && parent.type === "emphasis") {
-    //     const grandparent = parent.parent;
-    //     if (grandparent) {
-    //       const index = (grandparent.node as Parent).children.indexOf(
-    //         parent.node as RootContent,
-    //       );
-    //       if (index > 0) {
-    //         const prevNode = grandparent.children[index - 1];
-    //         if (
-    //           prevNode.type === "text" &&
-    //           (prevNode as Text).value.endsWith("*")
-    //         ) {
-    //           ruleMatched = true;
-    //           const textNode = (prevNode as Proxy).node as Text;
-    //           textNode.value = textNode.value.slice(0, -1);
-    //           parent.node.type = "strong";
-    //         }
-    //       }
-    //     }
-    // }
-
-    //   if (!ruleMatched) {
-    //     // if the last node is just text, then we process it in order to fix up certain unclosed items
-    //     // e.g., `**abc` -> `**abc**`
-    //     const textNode = lastNode.node as Text;
-    //     for (const rule of simpleTextRules) {
-    //       const matchesIterator = textNode.value.matchAll(rule.pattern);
-    //       const matches = [...matchesIterator];
-    //       if (matches.length > 0) {
-    //         rule.transform(matches, lastNode);
-    //         ruleMatched = true;
-    //         break;
-    //       }
-    //     }
-    //   }
-    // } else if (!ruleMatched) {
-    //   // console.log("no rule matched", lastNode);
-    // }
-
-    return tree;
-  };
-};
-
-function processParent(parent: Parent & Proxy): boolean {
-  if (parent.type === "emphasis") {
-    // Handle `**abc*` -> `**abc**`:
-    // We detect this when we end with an emphasis node, and it's preceded by
-    // a text node that ends with `*`
-    // TODO(drifkin): the last node can be more deeply nested (e.g., a code
-    // literal in a link), so we probably need to walk up the tree until we
-    // find an emphasis node or a block? For now we'll just go up one layer to
-    // catch the most common cases
-    const emphasisNode = parent as Emphasis & Proxy;
-    const grandparent = emphasisNode.parent;
-    if (grandparent) {
-      const indexOfEmphasisNode = (grandparent.node as Parent).children.indexOf(
-        emphasisNode.node as RootContent,
-      );
-      if (indexOfEmphasisNode >= 0) {
-        const nodeBefore = grandparent.children[indexOfEmphasisNode - 1] as
-          | (Node & Proxy)
-          | undefined;
-        if (nodeBefore?.type === "text") {
-          const textNode = nodeBefore.node as Text;
-          if (textNode.value.endsWith("*")) {
-            const strBefore = textNode.value.slice(0, -1);
-            textNode.value = strBefore;
-            const strongNode = u("strong", {
-              children: emphasisNode.children,
-            });
-            (grandparent.node as Parent).children.splice(
-              indexOfEmphasisNode,
-              1,
-              strongNode,
-            );
-            return true;
-          }
-        }
-      }
-    }
-  }
-
-  // Let's check if we have any bold items to close
-  for (let i = parent.children.length - 1; i >= 0; i--) {
-    const child = parent.children[i];
-    if (child.type === "text") {
-      const textNode = child as Text & Proxy;
-      const sep = "**";
-      const index = textNode.value.lastIndexOf(sep);
-      if (index >= 0) {
-        let isValidOpening = false;
-        if (index + sep.length < textNode.value.length) {
-          const charAfter = textNode.value[index + sep.length];
-          if (!isWhitespace(charAfter)) {
-            isValidOpening = true;
-          }
-        } else {
-          if (i < parent.children.length - 1) {
-            // TODO(drifkin): I'm not sure that this check is strict enough.
-            // We're trying to detect cases like `**[abc]()` where the char
-            // after the opening ** is indeed a non-whitespace character. We're
-            // using the heuristic that there's another item after the current
-            // one, but I'm not sure if that is good enough. In a well
-            // constructed tree, there aren't two text nodes in a row, so this
-            // _seems_ good, but I should think through it more
-            isValidOpening = true;
-          }
-        }
-
-        if (isValidOpening) {
-          // TODO(drifkin): close the bold
-          const strBefore = textNode.value.slice(0, index);
-          const strAfter = textNode.value.slice(index + sep.length);
-          (textNode.node as Text).value = strBefore;
-          // TODO(drifkin): the node above could be empty in which case we probably want to delete it
-          const children: PhrasingContent[] = [
-            ...(strAfter.length > 0 ? [u("text", { value: strAfter })] : []),
-          ];
-          const strongNode: Strong = u("strong", {
-            children,
-          });
-          const nodesAfter = (parent.node as Parent).children.splice(
-            i + 1,
-            parent.children.length - i - 1,
-            strongNode,
-          );
-          // TODO(drifkin): this cast seems iffy, should see if we can cast the
-          // parent instead, which would also help us check some of our
-          // assumptions
-          strongNode.children.push(...(nodesAfter as PhrasingContent[]));
-          return true;
-        }
-      }
-    }
-  }
-
-  return false;
-}
-
-function prevSibling(node: Node & Proxy): (Node & Proxy) | null {
-  const parent = node.parent;
-  if (parent) {
-    const index = parent.children.indexOf(node);
-    return parent.children[index - 1] as Node & Proxy;
-  }
-  return null;
-}
-
-function isWhitespace(str: string) {
-  return str.trim() === "";
-}
-
-// function debugPrintTreeNoPos(tree: Node) {
-//   console.log(
-//     JSON.stringify(
-//       tree,
-//       (key, value) => {
-//         if (key === "position") {
-//           return undefined;
-//         }
-//         return value;
-//       },
-//       2,
-//     ),
-//   );
-// }
-
-export default remarkStreamingMarkdown;
diff --git a/app/ui/ui.go b/app/ui/ui.go
index fce58895..1d0e2579 100644
--- a/app/ui/ui.go
+++ b/app/ui/ui.go
@@ -1794,13 +1794,14 @@ func (s *Server) buildChatRequest(chat *store.Chat, model string, think any, ava
 
 	var thinkValue *api.ThinkValue
 	if think != nil {
+		// Only set Think if it's actually requesting thinking
 		if boolValue, ok := think.(bool); ok {
-			thinkValue = &api.ThinkValue{
-				Value: boolValue,
+			if boolValue {
+				thinkValue = &api.ThinkValue{Value: boolValue}
 			}
 		} else if stringValue, ok := think.(string); ok {
-			thinkValue = &api.ThinkValue{
-				Value: stringValue,
+			if stringValue != "" && stringValue != "none" {
+				thinkValue = &api.ThinkValue{Value: stringValue}
 			}
 		}
 	}
diff --git a/convert/convert_gptoss.go b/convert/convert_gptoss.go
index 5338df21..d7bfb361 100644
--- a/convert/convert_gptoss.go
+++ b/convert/convert_gptoss.go
@@ -110,9 +110,12 @@ func (m *gptossModel) Tensors(ts []Tensor) []*ggml.Tensor {
 
 	for name, mxfp4 := range mxfp4s {
 		dims := mxfp4.blocks.Shape()
+		if !strings.HasSuffix(name, ".weight") {
+			name = name + ".weight"
+		}
 		if strings.Contains(name, "ffn_down_exps") {
 			out = append(out, &ggml.Tensor{
-				Name:     name + ".weight",
+				Name:     name,
 				Kind:     uint32(ggml.TensorTypeMXFP4),
 				Shape:    []uint64{dims[0], dims[1], dims[2] * dims[3] * 2},
 				WriterTo: mxfp4,
@@ -121,12 +124,12 @@ func (m *gptossModel) Tensors(ts []Tensor) []*ggml.Tensor {
 			// gate_up_exps is interleaved, need to split into gate_exps and up_exps
 			// e.g. gate_exps, up_exps = gate_up_exps[:, 0::2, ...], gate_up_exps[:, 1::2, ...]
 			out = append(out, &ggml.Tensor{
-				Name:     strings.Replace(name, "gate_up", "gate", 1) + ".weight",
+				Name:     strings.Replace(name, "gate_up", "gate", 1),
 				Kind:     uint32(ggml.TensorTypeMXFP4),
 				Shape:    []uint64{dims[0], dims[1] / 2, dims[2] * dims[3] * 2},
 				WriterTo: mxfp4.slice(1, 0, int(dims[1]), 2),
 			}, &ggml.Tensor{
-				Name:     strings.Replace(name, "gate_up", "up", 1) + ".weight",
+				Name:     strings.Replace(name, "gate_up", "up", 1),
 				Kind:     uint32(ggml.TensorTypeMXFP4),
 				Shape:    []uint64{dims[0], dims[1] / 2, dims[2] * dims[3] * 2},
 				WriterTo: mxfp4.slice(1, 1, int(dims[1]), 2),
diff --git a/convert/tensor.go b/convert/tensor.go
index 27bdd13f..68870744 100644
--- a/convert/tensor.go
+++ b/convert/tensor.go
@@ -2,10 +2,12 @@ package convert
 
 import (
 	"cmp"
+	"errors"
 	"io"
 	"iter"
 	"path"
 	"slices"
+	"strconv"
 	"strings"
 
 	"github.com/pdevine/tensor"
@@ -94,6 +96,26 @@ func mergeTensors(unmatched []Tensor, merges ...merge) (out []*ggml.Tensor, _ []
 			return matched
 		})
 
+		slices.SortStableFunc(matched, func(a, b Tensor) int {
+			x := strings.Split(a.Name(), ".")
+			y := strings.Split(b.Name(), ".")
+			if len(x) != len(y) {
+				return cmp.Compare(len(x), len(y))
+			}
+
+			vals := make([]int, len(x))
+			for i := range x {
+				vals[i] = strings.Compare(x[i], y[i])
+				m, err := strconv.ParseInt(x[i], 0, 0)
+				n, err2 := strconv.ParseInt(y[i], 0, 0)
+				if errors.Join(err, err2) == nil {
+					vals[i] = cmp.Compare(m, n)
+				}
+			}
+
+			return cmp.Or(vals...)
+		})
+
 		if len(matched) > 0 {
 			out = append(out, &ggml.Tensor{
 				Name:     merges[i].name,
diff --git a/convert/tensor_test.go b/convert/tensor_test.go
index c1f58da6..e0dc2350 100644
--- a/convert/tensor_test.go
+++ b/convert/tensor_test.go
@@ -3,8 +3,10 @@ package convert
 import (
 	"bytes"
 	"encoding/binary"
+	"fmt"
 	"io"
 	"iter"
+	"math/rand/v2"
 	"slices"
 	"strings"
 	"testing"
@@ -951,3 +953,45 @@ func TestMerge(t *testing.T) {
 		}
 	})
 }
+
+func TestMergeOrder(t *testing.T) {
+	for range 8 {
+		t.Run("", func(t *testing.T) {
+			tensors := make([]Tensor, 16)
+			for i := range tensors {
+				tensors[i] = &fakeTensor{
+					name:  fmt.Sprintf("layer.%d.weight", i),
+					shape: []uint64{1},
+					data:  []float32{float32(i)},
+				}
+			}
+
+			rand.Shuffle(len(tensors), func(i, j int) {
+				tensors[i], tensors[j] = tensors[j], tensors[i]
+			})
+
+			matched, unmatched := mergeTensors(tensors, merge{"layer.*.weight", "layer.weight"})
+			if len(unmatched) != 0 {
+				t.Error("expected no remaining tensors, got", len(unmatched))
+			}
+
+			if len(matched) != 1 {
+				t.Error("expected 1 merged tensor, got", len(matched))
+			}
+
+			var b bytes.Buffer
+			if _, err := matched[0].WriteTo(&b); err != nil {
+				t.Fatal(err)
+			}
+
+			var f32s [16]float32
+			if err := binary.Read(&b, binary.LittleEndian, &f32s); err != nil {
+				t.Fatal(err)
+			}
+
+			if !slices.IsSorted(f32s[:]) {
+				t.Errorf("merged tensor data is not in order: %+v", f32s)
+			}
+		})
+	}
+}
diff --git a/discover/runner.go b/discover/runner.go
index 4d44dae2..bf2110bc 100644
--- a/discover/runner.go
+++ b/discover/runner.go
@@ -94,6 +94,9 @@ func GPUDevices(ctx context.Context, runners []ml.FilteredRunnerDiscovery) []ml.
 					continue
 				} else if jetpack != "" && filepath.Base(dir) != "cuda_"+jetpack {
 					continue
+				} else if !envconfig.EnableVulkan() && strings.Contains(filepath.Base(dir), "vulkan") {
+					slog.Info("experimental Vulkan support disabled.  To enable, set OLLAMA_VULKAN=1")
+					continue
 				}
 				dirs = []string{ml.LibOllamaPath, dir}
 			} else {
diff --git a/docs/api/index.mdx b/docs/api/introduction.mdx
similarity index 100%
rename from docs/api/index.mdx
rename to docs/api/introduction.mdx
diff --git a/docs/capabilities/embeddings.mdx b/docs/capabilities/embeddings.mdx
index 99a57748..7d364200 100644
--- a/docs/capabilities/embeddings.mdx
+++ b/docs/capabilities/embeddings.mdx
@@ -13,9 +13,23 @@ Embeddings turn text into numeric vectors you can store in a vector database, se
 
 ## Generate embeddings
 
-Use `/api/embed` with a single string.
-
 <Tabs>
+  <Tab title="CLI">
+    Generate embeddings directly from the command line:
+
+    ```shell
+    ollama run embeddinggemma "Hello world"
+    ```
+
+    You can also pipe text to generate embeddings:
+
+    ```shell
+    echo "Hello world" | ollama run embeddinggemma
+    ```
+
+    Output is a JSON array.
+
+  </Tab>
   <Tab title="cURL">
     ```shell
     curl -X POST http://localhost:11434/api/embed \
diff --git a/docs/docker.mdx b/docs/docker.mdx
index 22d2bc33..ba770a70 100644
--- a/docs/docker.mdx
+++ b/docs/docker.mdx
@@ -68,6 +68,15 @@ To run Ollama using Docker with AMD GPUs, use the `rocm` tag and the following c
 docker run -d --device /dev/kfd --device /dev/dri -v ollama:/root/.ollama -p 11434:11434 --name ollama ollama/ollama:rocm
 ```
 
+## Vulkan Support
+
+Vulkan is bundled into the `ollama/ollama` image.  
+
+```shell
+docker run -d --device /dev/kfd --device /dev/dri -v ollama:/root/.ollama -p 11434:11434 -e OLLAMA_VULKAN=1 --name ollama ollama/ollama
+```
+
+
 ## Run model locally
 
 Now you can run a model:
@@ -79,3 +88,4 @@ docker exec -it ollama ollama run llama3.2
 ## Try different models
 
 More models can be found on the [Ollama library](https://ollama.com/library).
+
diff --git a/docs/docs.json b/docs/docs.json
index 6cc6606b..71a6f17a 100644
--- a/docs/docs.json
+++ b/docs/docs.json
@@ -63,6 +63,10 @@
     {
       "source": "/api/openai",
       "destination": "/api/openai-compatibility"
+    },
+    {
+      "source": "/api",
+      "destination": "/api/introduction"
     }
   ],
   "navigation": {
@@ -130,7 +134,7 @@
           {
             "group": "API Reference",
             "pages": [
-              "/api/index",
+              "/api/introduction",
               "/api/authentication",
               "/api/streaming",
               "/api/usage",
diff --git a/docs/faq.mdx b/docs/faq.mdx
index f6ae513b..d9398e9d 100644
--- a/docs/faq.mdx
+++ b/docs/faq.mdx
@@ -223,7 +223,7 @@ Refer to the section [above](#how-do-i-configure-ollama-server) for how to set e
 
 ## How can I use Ollama in Visual Studio Code?
 
-There is already a large collection of plugins available for VSCode as well as other editors that leverage Ollama. See the list of [extensions & plugins](https://github.com/ollama/ollama#extensions--plugins) at the bottom of the main repository readme.
+There is already a large collection of plugins available for VS Code as well as other editors that leverage Ollama. See the list of [extensions & plugins](https://github.com/ollama/ollama#extensions--plugins) at the bottom of the main repository readme.
 
 ## How do I use Ollama with GPU acceleration in Docker?
 
diff --git a/docs/gpu.mdx b/docs/gpu.mdx
index 2f20c627..36bfd3da 100644
--- a/docs/gpu.mdx
+++ b/docs/gpu.mdx
@@ -52,7 +52,11 @@ sudo modprobe nvidia_uvm`
 
 ## AMD Radeon
 
-Ollama supports the following AMD GPUs:
+Ollama supports the following AMD GPUs via the ROCm library:
+
+> [!NOTE]
+> Additional AMD GPU support is provided by the Vulkan Library - see below.
+
 
 ### Linux Support
 
@@ -121,6 +125,42 @@ In some Linux distributions, SELinux can prevent containers from
 accessing the AMD GPU devices. On the host system you can run
 `sudo setsebool container_use_devices=1` to allow containers to use devices.
 
-### Metal (Apple GPUs)
+## Metal (Apple GPUs)
 
 Ollama supports GPU acceleration on Apple devices via the Metal API.
+
+
+## Vulkan GPU Support
+
+> [!NOTE]
+> Vulkan is currently an Experimental feature.  To enable, you must set OLLAMA_VULKAN=1 for the Ollama server as
+described in the [FAQ](faq.md#how-do-i-configure-ollama-server)
+
+Additional GPU support on Windows and Linux is provided via
+[Vulkan](https://www.vulkan.org/). On Windows most GPU vendors drivers come
+bundled with Vulkan support and require no additional setup steps. Most Linux
+distributions require installing additional components, and you may have
+multiple options for Vulkan drivers between Mesa and GPU Vendor specific packages
+
+- Linux Intel GPU Instructions - https://dgpu-docs.intel.com/driver/client/overview.html
+- Linux AMD GPU Instructions - https://amdgpu-install.readthedocs.io/en/latest/install-script.html#specifying-a-vulkan-implementation
+
+For AMD GPUs on some Linux distributions, you may need to add the `ollama` user to the `render` group.
+
+The Ollama scheduler leverages available VRAM data reported by the GPU libraries to
+make optimal scheduling decisions.  Vulkan requires additional capabilities or
+running as root to expose this available VRAM data.  If neither root access or this
+capability are granted, Ollama will use approximate sizes of the models
+to make best effort scheduling decisions.
+
+```bash
+sudo setcap cap_perfmon+ep /usr/local/bin/ollama
+```
+
+### GPU Selection
+
+To select specific Vulkan GPU(s), you can set the environment variable
+`GGML_VK_VISIBLE_DEVICES` to one or more numeric IDs on the Ollama server as
+described in the [FAQ](faq.md#how-do-i-configure-ollama-server). If you
+encounter any problems with Vulkan based GPUs, you can disable all Vulkan GPUs
+by setting `GGML_VK_VISIBLE_DEVICES=-1` 
\ No newline at end of file
diff --git a/docs/integrations/vscode.mdx b/docs/integrations/vscode.mdx
index c68f9199..6f407a88 100644
--- a/docs/integrations/vscode.mdx
+++ b/docs/integrations/vscode.mdx
@@ -4,7 +4,7 @@ title: VS Code
 
 ## Install
 
-Install [VSCode](https://code.visualstudio.com/download). 
+Install [VS Code](https://code.visualstudio.com/download). 
 
 ## Usage with Ollama 
 
@@ -12,7 +12,7 @@ Install [VSCode](https://code.visualstudio.com/download).
 <div style={{ display: 'flex', justifyContent: 'center' }}>
   <img 
     src="/images/vscode-sidebar.png" 
-    alt="VSCode chat Sidebar"
+    alt="VS Code chat Sidebar"
     width="75%"
   />
 </div>
@@ -20,7 +20,7 @@ Install [VSCode](https://code.visualstudio.com/download).
 <div style={{ display: 'flex', justifyContent: 'center' }}>
   <img 
     src="/images/vscode-models.png" 
-    alt="VSCode model picker"
+    alt="VS Code model picker"
     width="75%"
   />
 </div>
@@ -28,7 +28,7 @@ Install [VSCode](https://code.visualstudio.com/download).
 <div style={{ display: 'flex', justifyContent: 'center' }}>
   <img 
     src="/images/vscode-model-options.png" 
-    alt="VSCode model options dropdown"
+    alt="VS Code model options dropdown"
     width="75%"
   />
 </div>
diff --git a/docs/openapi.yaml b/docs/openapi.yaml
index 28e4eed6..61f2a6fa 100644
--- a/docs/openapi.yaml
+++ b/docs/openapi.yaml
@@ -2,12 +2,15 @@ openapi: 3.1.0
 info:
   title: Ollama API
   version: 0.1.0
+  license:
+    name: MIT
+    url: https://opensource.org/licenses/MIT
   description: |
     OpenAPI specification for the Ollama HTTP API
-
 servers:
   - url: http://localhost:11434
-    description: Local Ollama instance
+    description: Ollama
+security: []
 components:
   securitySchemes:
     bearerAuth:
@@ -93,8 +96,11 @@ components:
           type: boolean
           default: true
         think:
-          type: boolean
-          description: When true, returns separate thinking output in addition to content
+          oneOf:
+            - type: boolean
+            - type: string
+              enum: [high, medium, low]
+          description: When true, returns separate thinking output in addition to content. Can be a boolean (true/false) or a string ("high", "medium", "low") for supported models.
         raw:
           type: boolean
           description: When true, returns the raw response from the model without any prompt templating
@@ -271,8 +277,11 @@ components:
           type: boolean
           default: true
         think:
-          type: boolean
-          description: When true, returns separate thinking output in addition to content
+          oneOf:
+            - type: boolean
+            - type: string
+              enum: [high, medium, low]
+          description: When true, returns separate thinking output in addition to content. Can be a boolean (true/false) or a string ("high", "medium", "low") for supported models.
         keep_alive:
           oneOf:
             - type: string
@@ -310,7 +319,6 @@ components:
               type: array
               items:
                 type: string
-              nullable: true
               description: Optional base64-encoded images in the response
         done:
           type: boolean
@@ -367,7 +375,6 @@ components:
               type: array
               items:
                 type: string
-              nullable: true
               description: Partial base64-encoded images, when present
         done:
           type: boolean
@@ -543,6 +550,9 @@ components:
         license:
           type: string
           description: The license of the model
+        modified_at:
+          type: string
+          description: Last modified timestamp in ISO 8601 format
         details:
           type: object
           description: High-level model details
@@ -622,6 +632,9 @@ components:
         size_vram:
           type: integer
           description: VRAM usage in bytes
+        context_length:
+          type: integer
+          description: Context length for the running model
     PsResponse:
       type: object
       properties:
@@ -1275,6 +1288,9 @@ paths:
             example:
               source: gemma3
               destination: gemma3-backup
+      responses:
+        "200":
+          description: Model successfully copied
   /api/pull:
     post:
       summary: Pull a model
@@ -1382,16 +1398,7 @@ paths:
               model: gemma3
       responses:
         "200":
-          description: Deletion status updates.
-          content:
-            application/json:
-              schema:
-                $ref: "#/components/schemas/StatusResponse"
-              example:
-                status: "success"
-            application/x-ndjson:
-              schema:
-                $ref: "#/components/schemas/StatusEvent"
+          description: Model successfully deleted
   /api/version:
     get:
       summary: Get version
diff --git a/envconfig/config.go b/envconfig/config.go
index d155bd8f..238e5e6e 100644
--- a/envconfig/config.go
+++ b/envconfig/config.go
@@ -196,8 +196,6 @@ var (
 	NoPrune = Bool("OLLAMA_NOPRUNE")
 	// SchedSpread allows scheduling models across all GPUs.
 	SchedSpread = Bool("OLLAMA_SCHED_SPREAD")
-	// IntelGPU enables experimental Intel GPU detection.
-	IntelGPU = Bool("OLLAMA_INTEL_GPU")
 	// MultiUserCache optimizes prompt caching for multi-user scenarios
 	MultiUserCache = Bool("OLLAMA_MULTIUSER_CACHE")
 	// Enable the new Ollama engine
@@ -206,6 +204,8 @@ var (
 	ContextLength = Uint("OLLAMA_CONTEXT_LENGTH", 4096)
 	// Auth enables authentication between the Ollama client and server
 	UseAuth = Bool("OLLAMA_AUTH")
+	// Enable Vulkan backend
+	EnableVulkan = Bool("OLLAMA_VULKAN")
 )
 
 func String(s string) func() string {
@@ -314,7 +314,7 @@ func AsMap() map[string]EnvVar {
 		ret["GGML_VK_VISIBLE_DEVICES"] = EnvVar{"GGML_VK_VISIBLE_DEVICES", VkVisibleDevices(), "Set which Vulkan devices are visible by numeric ID"}
 		ret["GPU_DEVICE_ORDINAL"] = EnvVar{"GPU_DEVICE_ORDINAL", GpuDeviceOrdinal(), "Set which AMD devices are visible by numeric ID"}
 		ret["HSA_OVERRIDE_GFX_VERSION"] = EnvVar{"HSA_OVERRIDE_GFX_VERSION", HsaOverrideGfxVersion(), "Override the gfx used for all detected AMD GPUs"}
-		ret["OLLAMA_INTEL_GPU"] = EnvVar{"OLLAMA_INTEL_GPU", IntelGPU(), "Enable experimental Intel GPU detection"}
+		ret["OLLAMA_VULKAN"] = EnvVar{"OLLAMA_VULKAN", EnableVulkan(), "Enable experimental Vulkan support"}
 	}
 
 	return ret
diff --git a/fs/ggml/ggml.go b/fs/ggml/ggml.go
index 909104c6..0b5d37a7 100644
--- a/fs/ggml/ggml.go
+++ b/fs/ggml/ggml.go
@@ -797,73 +797,6 @@ func (f GGML) GraphSize(context, batch uint64, numParallel int, kvCacheType stri
 	return
 }
 
-func (llm GGML) VisionGraphSize() (weights, graphSize uint64) {
-	if llm.KV().Uint("vision.block_count") == 0 {
-		return
-	}
-
-	for name, layer := range llm.Tensors().GroupLayers() {
-		if name == "v" || strings.HasPrefix(name, "v.") {
-			for _, tensor := range layer {
-				weights += tensor.Size()
-			}
-		}
-	}
-
-	imageSize := uint64(llm.KV().Uint("vision.image_size"))
-	patchSize := uint64(llm.KV().Uint("vision.patch_size"))
-	if patchSize == 0 {
-		slog.Warn("unknown patch size for vision model")
-		return
-	}
-
-	numChannels := uint64(llm.KV().Uint("vision.num_channels"))
-
-	numPatches := (imageSize / patchSize) * (imageSize / patchSize)
-	if _, ok := llm.Tensors().GroupLayers()["v"]["class_embd"]; ok {
-		numPatches++
-	}
-
-	headCount := uint64(llm.KV().Uint("vision.attention.head_count"))
-	embeddingLength := uint64(llm.KV().Uint("vision.embedding_length"))
-
-	switch llm.KV().Architecture() {
-	case "mllama":
-		numPaddedPatches := numPatches + 8 - (numPatches%8)%8
-
-		maxNumTiles := uint64(llm.KV().Uint("vision.max_num_tiles"))
-
-		graphSize = 4 * (8 +
-			imageSize*imageSize*numChannels*maxNumTiles +
-			embeddingLength*numPatches*maxNumTiles +
-			9*embeddingLength*numPaddedPatches*maxNumTiles +
-			numPaddedPatches*maxNumTiles*numPaddedPatches*maxNumTiles*headCount)
-	case "gemma3", "mistral3":
-		graphSize = 4 * (imageSize*imageSize*numChannels +
-			embeddingLength*patchSize +
-			numPatches*numPatches*headCount)
-	case "qwen25vl":
-		maxPixels := uint64(llm.KV().Uint("vision.max_pixels", 28*28*1280))
-
-		numPatches := maxPixels / (patchSize * patchSize)
-
-		graphSize = 4 * (maxPixels*numChannels + // Original image storage
-			// Normalized pixels
-			maxPixels*numChannels +
-			// Patches storage (numPatches * channels * patchSize^2)
-			numPatches*numChannels*patchSize*patchSize +
-			// Self-attention calculations
-			numPatches*numPatches*headCount +
-			// Additional buffer for processing
-			embeddingLength*numPatches)
-	case "llama4":
-		// vision graph is computed independently in the same schedule
-		// and is negligible compared to the worst case text graph
-	}
-
-	return weights, graphSize
-}
-
 // SupportsKVCacheType checks if the requested cache type is supported
 func (f GGML) SupportsKVCacheType(cacheType string) bool {
 	if cacheType == "" || cacheType == "f16" {
diff --git a/integration/api_test.go b/integration/api_test.go
index 39eea39c..66d1e9e9 100644
--- a/integration/api_test.go
+++ b/integration/api_test.go
@@ -14,6 +14,23 @@ import (
 	"github.com/ollama/ollama/api"
 )
 
+func assertBytesMatchToken(t *testing.T, label, token string, ints []int) {
+	t.Helper()
+
+	raw := []byte(token)
+	if len(ints) != len(raw) {
+		t.Errorf("%s expected %d bytes for token %q, got %d (%v)", label, len(raw), token, len(ints), ints)
+		return
+	}
+
+	for i, b := range raw {
+		if ints[i] != int(b) {
+			t.Errorf("%s byte[%d] mismatch for token %q: got %d want %d", label, i, token, ints[i], int(b))
+			return
+		}
+	}
+}
+
 func TestAPIGenerate(t *testing.T) {
 	initialTimeout := 60 * time.Second
 	streamTimeout := 30 * time.Second
@@ -381,3 +398,182 @@ func TestAPIShowModel(t *testing.T) {
 		t.Errorf("%s missing modified_at: %#v", modelName, resp)
 	}
 }
+
+func TestAPIGenerateLogprobs(t *testing.T) {
+	ctx, cancel := context.WithTimeout(context.Background(), 2*time.Minute)
+	defer cancel()
+
+	client, _, cleanup := InitServerConnection(ctx, t)
+	defer cleanup()
+
+	if err := PullIfMissing(ctx, client, smol); err != nil {
+		t.Fatalf("pull failed %s", err)
+	}
+
+	enableLogprobs := true
+	noStream := false
+
+	tests := []struct {
+		name        string
+		logprobs    *bool
+		topLogprobs int
+		expectCount int
+	}{
+		{
+			name:        "no_logprobs",
+			logprobs:    nil,
+			topLogprobs: 0,
+			expectCount: 0,
+		},
+		{
+			name:        "logprobs_only",
+			logprobs:    &enableLogprobs,
+			topLogprobs: 0,
+			expectCount: 1,
+		},
+		{
+			name:        "logprobs_with_top_5",
+			logprobs:    &enableLogprobs,
+			topLogprobs: 5,
+			expectCount: 1,
+		},
+	}
+
+	for _, test := range tests {
+		t.Run(test.name, func(t *testing.T) {
+			req := api.GenerateRequest{
+				Model:       smol,
+				Prompt:      "Why is the sky blue?",
+				Stream:      &noStream,
+				Logprobs:    test.logprobs != nil && *test.logprobs,
+				TopLogprobs: test.topLogprobs,
+				Options: map[string]interface{}{
+					"temperature": 0,
+					"seed":        123,
+					"num_predict": 10,
+				},
+			}
+
+			var response api.GenerateResponse
+			err := client.Generate(ctx, &req, func(resp api.GenerateResponse) error {
+				if resp.Done {
+					response = resp
+				}
+				return nil
+			})
+			if err != nil {
+				t.Fatalf("generate failed: %s", err)
+			}
+
+			// Check logprobs based on expectation
+			if test.expectCount == 0 {
+				if len(response.Logprobs) > 0 {
+					t.Errorf("expected no logprobs but got %d", len(response.Logprobs))
+				}
+			} else {
+				if len(response.Logprobs) == 0 {
+					t.Errorf("expected logprobs but got none")
+				}
+
+				// Validate each logprob entry
+				for i, lp := range response.Logprobs {
+					if lp.Token == "" {
+						t.Errorf("logprob[%d] has empty token", i)
+					}
+					if lp.Logprob > 0 {
+						t.Errorf("logprob[%d] has positive logprob %f (should be <= 0)", i, lp.Logprob)
+					}
+					assertBytesMatchToken(t, fmt.Sprintf("generate logprob[%d]", i), lp.Token, lp.Bytes)
+
+					// Check top_logprobs if requested
+					if test.topLogprobs > 0 {
+						if len(lp.TopLogprobs) == 0 {
+							t.Errorf("logprob[%d] expected top_logprobs but got none", i)
+						}
+						if len(lp.TopLogprobs) > test.topLogprobs {
+							t.Errorf("logprob[%d] has %d top_logprobs, expected max %d", i, len(lp.TopLogprobs), test.topLogprobs)
+						}
+
+						// Verify top_logprobs are sorted by probability (descending)
+						for j := 1; j < len(lp.TopLogprobs); j++ {
+							if lp.TopLogprobs[j-1].Logprob < lp.TopLogprobs[j].Logprob {
+								t.Errorf("logprob[%d].top_logprobs not sorted: %f < %f", i, lp.TopLogprobs[j-1].Logprob, lp.TopLogprobs[j].Logprob)
+							}
+						}
+						for j, top := range lp.TopLogprobs {
+							assertBytesMatchToken(t, fmt.Sprintf("generate logprob[%d].top[%d]", i, j), top.Token, top.Bytes)
+						}
+					} else if len(lp.TopLogprobs) > 0 {
+						t.Errorf("logprob[%d] has top_logprobs but none were requested", i)
+					}
+				}
+			}
+		})
+	}
+}
+
+func TestAPIChatLogprobs(t *testing.T) {
+	ctx, cancel := context.WithTimeout(context.Background(), 2*time.Minute)
+	defer cancel()
+
+	client, _, cleanup := InitServerConnection(ctx, t)
+	defer cleanup()
+
+	if err := PullIfMissing(ctx, client, smol); err != nil {
+		t.Fatalf("pull failed %s", err)
+	}
+
+	enableLogprobs := true
+	noStream := false
+
+	req := api.ChatRequest{
+		Model: smol,
+		Messages: []api.Message{
+			{Role: "user", Content: "Say hello in one word"},
+		},
+		Stream:      &noStream,
+		Logprobs:    enableLogprobs,
+		TopLogprobs: 3,
+		Options: map[string]interface{}{
+			"temperature": 0,
+			"seed":        123,
+			"num_predict": 5,
+		},
+	}
+
+	var response api.ChatResponse
+	err := client.Chat(ctx, &req, func(resp api.ChatResponse) error {
+		if resp.Done {
+			response = resp
+		}
+		return nil
+	})
+	if err != nil {
+		t.Fatalf("chat failed: %s", err)
+	}
+
+	if len(response.Logprobs) == 0 {
+		t.Fatal("expected logprobs in response but got none")
+	}
+
+	t.Logf("received %d logprobs for chat response", len(response.Logprobs))
+
+	for i, lp := range response.Logprobs {
+		if lp.Token == "" {
+			t.Errorf("logprob[%d] has empty token", i)
+		}
+		if lp.Logprob > 0 {
+			t.Errorf("logprob[%d] has positive logprob %f", i, lp.Logprob)
+		}
+		assertBytesMatchToken(t, fmt.Sprintf("chat logprob[%d]", i), lp.Token, lp.Bytes)
+		if len(lp.TopLogprobs) == 0 {
+			t.Errorf("logprob[%d] expected top_logprobs but got none", i)
+		}
+		if len(lp.TopLogprobs) > 3 {
+			t.Errorf("logprob[%d] has %d top_logprobs, expected max 3", i, len(lp.TopLogprobs))
+		}
+		for j, top := range lp.TopLogprobs {
+			assertBytesMatchToken(t, fmt.Sprintf("chat logprob[%d].top[%d]", i, j), top.Token, top.Bytes)
+		}
+	}
+}
diff --git a/llama/llama.go b/llama/llama.go
index c995b3ea..582d4128 100644
--- a/llama/llama.go
+++ b/llama/llama.go
@@ -63,8 +63,13 @@ func BackendInit() {
 	C.llama_backend_init()
 }
 
-func EnumerateGPUs() []ml.DeviceID {
-	var ids []ml.DeviceID
+type Devices struct {
+	ml.DeviceID
+	LlamaID uint64
+}
+
+func EnumerateGPUs() []Devices {
+	var ids []Devices
 
 	for i := range C.ggml_backend_dev_count() {
 		device := C.ggml_backend_dev_get(i)
@@ -74,9 +79,12 @@ func EnumerateGPUs() []ml.DeviceID {
 			C.GGML_BACKEND_DEVICE_TYPE_IGPU:
 			var props C.struct_ggml_backend_dev_props
 			C.ggml_backend_dev_get_props(device, &props)
-			ids = append(ids, ml.DeviceID{
-				ID:      C.GoString(props.id),
-				Library: C.GoString(props.library),
+			ids = append(ids, Devices{
+				DeviceID: ml.DeviceID{
+					ID:      C.GoString(props.id),
+					Library: C.GoString(props.library),
+				},
+				LlamaID: uint64(i),
 			})
 		}
 	}
@@ -217,7 +225,21 @@ func (c *Context) GetEmbeddingsIth(i int) []float32 {
 	return embeddings
 }
 
+// GetLogitsIth gets the logits for the ith token
+func (c *Context) GetLogitsIth(i int) []float32 {
+	logits := unsafe.Pointer(C.llama_get_logits_ith(c.c, C.int32_t(i)))
+	if logits == nil {
+		return nil
+	}
+
+	vocabSize := c.Model().NumVocab()
+	result := make([]float32, vocabSize)
+	_ = copy(result, unsafe.Slice((*float32)(logits), vocabSize))
+	return result
+}
+
 type ModelParams struct {
+	Devices      []uint64
 	NumGpuLayers int
 	MainGpu      int
 	UseMmap      bool
@@ -241,6 +263,21 @@ func LoadModelFromFile(modelPath string, params ModelParams) (*Model, error) {
 	cparams.use_mmap = C.bool(params.UseMmap)
 	cparams.vocab_only = C.bool(params.VocabOnly)
 
+	var devices []C.ggml_backend_dev_t
+	for _, llamaID := range params.Devices {
+		devices = append(devices, C.ggml_backend_dev_get(C.size_t(llamaID)))
+	}
+	if len(devices) > 0 {
+		devices = append(devices, C.ggml_backend_dev_t(C.NULL))
+		devicesData := &devices[0]
+
+		var devicesPin runtime.Pinner
+		devicesPin.Pin(devicesData)
+		defer devicesPin.Unpin()
+
+		cparams.devices = devicesData
+	}
+
 	if len(params.TensorSplit) > 0 {
 		tensorSplitData := &params.TensorSplit[0]
 
diff --git a/llama/patches/0029-vulkan-Call-ggml_vk_buffer_write_2d-from-ggml_vk_buf.patch b/llama/patches/0029-vulkan-Call-ggml_vk_buffer_write_2d-from-ggml_vk_buf.patch
new file mode 100644
index 00000000..e9737aa4
--- /dev/null
+++ b/llama/patches/0029-vulkan-Call-ggml_vk_buffer_write_2d-from-ggml_vk_buf.patch
@@ -0,0 +1,32 @@
+From 0000000000000000000000000000000000000000 Mon Sep 17 00:00:00 2001
+From: Jeff Bolz <jbolz@nvidia.com>
+Date: Wed, 29 Oct 2025 03:53:04 -0500
+Subject: [PATCH] vulkan: Call ggml_vk_buffer_write_2d from ggml_vk_buffer_copy
+ (#16793)
+
+This lets the copy to the destination device use the host-visible
+vidmem optimization.
+---
+ ggml/src/ggml-vulkan/ggml-vulkan.cpp | 5 +----
+ 1 file changed, 1 insertion(+), 4 deletions(-)
+
+diff --git a/ggml/src/ggml-vulkan/ggml-vulkan.cpp b/ggml/src/ggml-vulkan/ggml-vulkan.cpp
+index 221e29509..18b7cbccf 100644
+--- a/ggml/src/ggml-vulkan/ggml-vulkan.cpp
++++ b/ggml/src/ggml-vulkan/ggml-vulkan.cpp
+@@ -5654,14 +5654,11 @@ static void ggml_vk_buffer_copy(vk_buffer& dst, size_t dst_offset, vk_buffer& sr
+         VK_LOG_DEBUG("ggml_vk_buffer_copy(MULTI_DEVICE, " << size << ")");
+         // Copy device to device
+         ggml_vk_ensure_sync_staging_buffer(src->device, size);
+-        ggml_vk_ensure_sync_staging_buffer(dst->device, size);
+ 
+         // Copy to src staging buffer
+         ggml_vk_buffer_copy(src->device->sync_staging, 0, src, src_offset, size);
+-        // memcpy to dst staging buffer
+-        memcpy(dst->device->sync_staging->ptr, src->device->sync_staging->ptr, size);
+         // Copy to dst buffer
+-        ggml_vk_buffer_copy(dst, dst_offset, dst->device->sync_staging, 0, size);
++        ggml_vk_buffer_write_2d(dst, dst_offset, src->device->sync_staging->ptr, 0, size, 1);
+     }
+ }
+ 
diff --git a/llama/patches/0030-Vulkan-MMQ-Integer-Dot-Refactor-and-K-Quant-support-.patch b/llama/patches/0030-Vulkan-MMQ-Integer-Dot-Refactor-and-K-Quant-support-.patch
new file mode 100644
index 00000000..1b1f65e4
--- /dev/null
+++ b/llama/patches/0030-Vulkan-MMQ-Integer-Dot-Refactor-and-K-Quant-support-.patch
@@ -0,0 +1,2140 @@
+From 0000000000000000000000000000000000000000 Mon Sep 17 00:00:00 2001
+From: Ruben Ortlam <picard12@live.de>
+Date: Wed, 29 Oct 2025 14:39:03 +0100
+Subject: [PATCH] Vulkan MMQ Integer Dot Refactor and K-Quant support (#16536)
+
+* vulkan: add mmq q2_k integer dot support
+
+* Refactor mmq caching
+
+* Reduce mmq register use
+
+* Load 4 quant blocks into shared memory in one step
+
+* Pack q2_k blocks into caches of 32
+
+* Use 32-bit accumulators for integer dot matmul
+
+* Add q4_k mmq
+
+* Add q3_k mmq
+
+* Add q5_k mmq
+
+* Add q6_k mmq
+
+* Add mxfp4 mmq, enable MMQ MUL_MAT_ID
+
+* Fix mmv dm loads
+---
+ ggml/src/ggml-vulkan/ggml-vulkan.cpp          | 165 +++++-
+ .../vulkan-shaders/dequant_funcs.glsl         |  10 +-
+ .../vulkan-shaders/dequant_funcs_cm2.glsl     |   6 +-
+ .../vulkan-shaders/dequant_mxfp4.comp         |   4 +-
+ .../vulkan-shaders/dequant_q2_k.comp          |   4 +-
+ .../vulkan-shaders/dequant_q4_k.comp          |   4 +-
+ .../vulkan-shaders/dequant_q5_k.comp          |   4 +-
+ .../vulkan-shaders/mul_mat_vec_q2_k.comp      |   6 +-
+ .../vulkan-shaders/mul_mat_vec_q4_k.comp      |   6 +-
+ .../vulkan-shaders/mul_mat_vec_q5_k.comp      |   6 +-
+ .../ggml-vulkan/vulkan-shaders/mul_mm.comp    |  72 +--
+ .../vulkan-shaders/mul_mm_funcs.glsl          |  14 +-
+ .../vulkan-shaders/mul_mm_id_funcs.glsl       |  70 +++
+ .../ggml-vulkan/vulkan-shaders/mul_mmq.comp   | 288 +++-------
+ .../vulkan-shaders/mul_mmq_funcs.glsl         | 538 ++++++++++++++++--
+ .../vulkan-shaders/mul_mmq_shmem_types.glsl   |  78 +++
+ .../src/ggml-vulkan/vulkan-shaders/types.glsl |  53 +-
+ .../vulkan-shaders/vulkan-shaders-gen.cpp     |   5 +-
+ 18 files changed, 928 insertions(+), 405 deletions(-)
+ create mode 100644 ggml/src/ggml-vulkan/vulkan-shaders/mul_mm_id_funcs.glsl
+ create mode 100644 ggml/src/ggml-vulkan/vulkan-shaders/mul_mmq_shmem_types.glsl
+
+diff --git a/ggml/src/ggml-vulkan/ggml-vulkan.cpp b/ggml/src/ggml-vulkan/ggml-vulkan.cpp
+index 18b7cbccf..53b57c179 100644
+--- a/ggml/src/ggml-vulkan/ggml-vulkan.cpp
++++ b/ggml/src/ggml-vulkan/ggml-vulkan.cpp
+@@ -488,6 +488,7 @@ struct vk_device_struct {
+     vk_matmul_pipeline2 pipeline_matmul_id_f16_f32;
+ 
+     vk_matmul_pipeline2 pipeline_dequant_mul_mat_mat_id[GGML_TYPE_COUNT];
++    vk_matmul_pipeline2 pipeline_dequant_mul_mat_mat_id_q8_1[GGML_TYPE_COUNT];
+ 
+     vk_pipeline pipeline_matmul_split_k_reduce;
+     vk_pipeline pipeline_quantize_q8_1;
+@@ -2449,8 +2450,11 @@ static void ggml_vk_load_shaders(vk_device& device) {
+                           l_warptile_id, m_warptile_id, s_warptile_id,
+                           l_warptile_mmq, m_warptile_mmq, s_warptile_mmq,
+                           l_warptile_mmq_int, m_warptile_mmq_int, s_warptile_mmq_int,
++                          l_warptile_mmq_int_k, m_warptile_mmq_int_k, s_warptile_mmq_int_k,
+                           l_warptile_mmq_k, m_warptile_mmq_k, s_warptile_mmq_k,
+-                          l_warptile_mmqid, m_warptile_mmqid, s_warptile_mmqid;
++                          l_warptile_mmqid, m_warptile_mmqid, s_warptile_mmqid,
++                          l_warptile_mmqid_int, m_warptile_mmqid_int, s_warptile_mmqid_int,
++                          l_warptile_mmqid_int_k, m_warptile_mmqid_int_k, s_warptile_mmqid_int_k;
+     std::array<uint32_t, 3> l_wg_denoms, m_wg_denoms, s_wg_denoms,
+                             l_mmq_wg_denoms, m_mmq_wg_denoms, s_mmq_wg_denoms,
+                             l_mmq_wg_denoms_k, m_mmq_wg_denoms_k, s_mmq_wg_denoms_k,
+@@ -2513,10 +2517,16 @@ static void ggml_vk_load_shaders(vk_device& device) {
+         m_warptile_mmq = { 128,  64,  64, 32, subgroup_size_8, 32, 2, tm_m, tn_m, tk_m, subgroup_size_8 };
+         s_warptile_mmq = { subgroup_size_32, 32, 32, 32, 32, 32, 2, tm_s, tn_s, tk_s, subgroup_size_8 };
+ 
++        // Integer MMQ has a smaller shared memory profile, but heavier register use
+         l_warptile_mmq_int = { 128, 128, 128, 32, subgroup_size_8 * 2, 64, 2, 4, 4, 1, subgroup_size_8 };
+         m_warptile_mmq_int = { 128,  64,  64, 32, subgroup_size_8,     32, 2, 2, 2, 1, subgroup_size_8 };
+         s_warptile_mmq_int = { subgroup_size_32, 32, 32, 32, 32,       32, 2, 2, 1, 1, subgroup_size_8 };
+ 
++        // K-quants use even more registers, mitigate by setting WMITER to 1
++        l_warptile_mmq_int_k = { 128, 128, 128, 32, subgroup_size_8 * 2, 64, 1, 4, 4, 1, subgroup_size_8 };
++        m_warptile_mmq_int_k = { 128,  64,  64, 32, subgroup_size_8,     32, 1, 2, 2, 1, subgroup_size_8 };
++        s_warptile_mmq_int_k = { subgroup_size_32, 32, 32, 32, 32,       32, 1, 2, 1, 1, subgroup_size_8 };
++
+         l_warptile_id = { 128, 128, 128, 16, mul_mat_subgroup_size_16 * 2, 64, 2, tm_l, tn_l, tk_l, mul_mat_subgroup_size_16 };
+         m_warptile_id = { 128,  64,  64, 16, mul_mat_subgroup_size_16, 32, 2, tm_m, tn_m, tk_m, mul_mat_subgroup_size_16 };
+         s_warptile_id = { mul_mat_subgroup_size_16, 32, 32, 16, 32, 32, 2, tm_s, tn_s, tk_s, mul_mat_subgroup_size_16 };
+@@ -2525,10 +2535,18 @@ static void ggml_vk_load_shaders(vk_device& device) {
+         m_warptile_mmqid = { 128,  64,  64, 32, mul_mat_subgroup_size_8, 32, 2, tm_m, tn_m, tk_m, mul_mat_subgroup_size_8 };
+         s_warptile_mmqid = { mul_mat_subgroup_size_32, 32, 32, 32, 32, 32, 2, tm_s, tn_s, tk_s, mul_mat_subgroup_size_8 };
+ 
++        l_warptile_mmqid_int = { 128, 128, 128, 32, mul_mat_subgroup_size_8 * 2, 64, 2, 4, 4, 1, mul_mat_subgroup_size_8 };
++        m_warptile_mmqid_int = { 128,  64,  64, 32, mul_mat_subgroup_size_8,     32, 2, 2, 2, 1, mul_mat_subgroup_size_8 };
++        s_warptile_mmqid_int = { mul_mat_subgroup_size_32, 32, 32, 32, 32,       32, 2, 2, 1, 1, mul_mat_subgroup_size_8 };
++
++        l_warptile_mmqid_int_k = { 128, 128, 128, 32, mul_mat_subgroup_size_16 * 2, 64, 1, 4, 4, 1, mul_mat_subgroup_size_16 };
++        m_warptile_mmqid_int_k = { 128,  64,  64, 32, mul_mat_subgroup_size_16,     32, 1, 2, 2, 1, mul_mat_subgroup_size_16 };
++        s_warptile_mmqid_int_k = { mul_mat_subgroup_size_32, 32, 32, 32, 32,       32, 1, 2, 1, 1, mul_mat_subgroup_size_16 };
++
+         // chip specific tuning
+         if ((device->architecture == AMD_GCN) && (device->driver_id != vk::DriverId::eAmdProprietary)) {
+             m_warptile_mmq = m_warptile_mmq_int = { 256, 64, 64, 32, 16, 16, 2, 2, 2, 1, 16 };
+-            m_warptile_mmqid = { 256, 64, 64, 32, 16, 16, 2, 2, 2, 1, 16 };
++            m_warptile_mmqid = m_warptile_mmqid_int = { 256, 64, 64, 32, 16, 16, 2, 2, 2, 1, 16 };
+         }
+ 
+         l_mmq_wg_denoms = l_wg_denoms = {128, 128, 1 };
+@@ -2913,18 +2931,15 @@ static void ggml_vk_load_shaders(vk_device& device) {
+         if (device->mul_mat ## ID ## _s[TYPE]) \
+             ggml_vk_create_pipeline(device, device-> PIPELINE_NAME ->a_s, #NAMELC #F16ACC "_aligned_s", NAMELC ## _aligned ## F16ACC ## _len, NAMELC ## _aligned ## F16ACC ## _data, "main", PARAMCOUNT, sizeof(PUSHCONST), s_ ## WG_DENOMS, s_ ## WARPTILE, s_align, false, REQSUBGROUPSIZE > 0, REQSUBGROUPSIZE);   \
+ 
+-#define CREATE_MMQ(TYPE, PIPELINE_NAME, NAMELC, WG_DENOMS, WARPTILE, PUSHCONST, PARAMCOUNT, ID) \
++#define CREATE_MMQ(TYPE, PIPELINE_NAME, NAMELC, WG_DENOMS, WARPTILE, PUSHCONST, PARAMCOUNT, ID, REQSUBGROUPSIZE) \
+         if (device->mul_mat ## ID ## _l[TYPE]) { \
+-            ggml_vk_create_pipeline(device, device-> PIPELINE_NAME .f16acc->l, #NAMELC "_f16acc_l", NAMELC ## _f16acc_len, NAMELC ##  _f16acc_data, "main", PARAMCOUNT, sizeof(PUSHCONST), l_ ## WG_DENOMS, l_ ## WARPTILE, 1);   \
+-            ggml_vk_create_pipeline(device, device-> PIPELINE_NAME .f32acc->l, #NAMELC        "_l", NAMELC ## _len,        NAMELC ##  _data,        "main", PARAMCOUNT, sizeof(PUSHCONST), l_ ## WG_DENOMS, l_ ## WARPTILE, 1);   \
++            ggml_vk_create_pipeline(device, device-> PIPELINE_NAME .f32acc->l, #NAMELC        "_l", NAMELC ## _len,        NAMELC ##  _data,        "main", PARAMCOUNT, sizeof(PUSHCONST), l_ ## WG_DENOMS, l_ ## WARPTILE, 1, false, REQSUBGROUPSIZE > 0, REQSUBGROUPSIZE);   \
+         } \
+         if (device->mul_mat ## ID ## _m[TYPE]) { \
+-            ggml_vk_create_pipeline(device, device-> PIPELINE_NAME .f16acc->m, #NAMELC "_f16acc_m", NAMELC ## _f16acc_len, NAMELC ##  _f16acc_data, "main", PARAMCOUNT, sizeof(PUSHCONST), m_ ## WG_DENOMS, m_ ## WARPTILE, 1);   \
+-            ggml_vk_create_pipeline(device, device-> PIPELINE_NAME .f32acc->m, #NAMELC        "_m", NAMELC ## _len,        NAMELC ##  _data,        "main", PARAMCOUNT, sizeof(PUSHCONST), m_ ## WG_DENOMS, m_ ## WARPTILE, 1);   \
++            ggml_vk_create_pipeline(device, device-> PIPELINE_NAME .f32acc->m, #NAMELC        "_m", NAMELC ## _len,        NAMELC ##  _data,        "main", PARAMCOUNT, sizeof(PUSHCONST), m_ ## WG_DENOMS, m_ ## WARPTILE, 1, false, REQSUBGROUPSIZE > 0, REQSUBGROUPSIZE);   \
+         } \
+         if (device->mul_mat ## ID ## _s[TYPE]) { \
+-            ggml_vk_create_pipeline(device, device-> PIPELINE_NAME .f16acc->s, #NAMELC "_f16acc_s", NAMELC ## _f16acc_len, NAMELC ##  _f16acc_data, "main", PARAMCOUNT, sizeof(PUSHCONST), s_ ## WG_DENOMS, s_ ## WARPTILE, 1);   \
+-            ggml_vk_create_pipeline(device, device-> PIPELINE_NAME .f32acc->s, #NAMELC        "_s", NAMELC ## _len,        NAMELC ##  _data,        "main", PARAMCOUNT, sizeof(PUSHCONST), s_ ## WG_DENOMS, s_ ## WARPTILE, 1);   \
++            ggml_vk_create_pipeline(device, device-> PIPELINE_NAME .f32acc->s, #NAMELC        "_s", NAMELC ## _len,        NAMELC ##  _data,        "main", PARAMCOUNT, sizeof(PUSHCONST), s_ ## WG_DENOMS, s_ ## WARPTILE, 1, false, REQSUBGROUPSIZE > 0, REQSUBGROUPSIZE);   \
+         } \
+ 
+         // Create 2 variants, {f16,f32} accumulator
+@@ -2963,11 +2978,19 @@ static void ggml_vk_load_shaders(vk_device& device) {
+ 
+ #if defined(GGML_VULKAN_INTEGER_DOT_GLSLC_SUPPORT)
+         if (device->integer_dot_product) {
+-            CREATE_MMQ(GGML_TYPE_Q4_0, pipeline_dequant_mul_mat_mat_q8_1[GGML_TYPE_Q4_0], matmul_q4_0_q8_1, mmq_wg_denoms, warptile_mmq_int, vk_mat_mat_push_constants, 3, );
+-            CREATE_MMQ(GGML_TYPE_Q4_1, pipeline_dequant_mul_mat_mat_q8_1[GGML_TYPE_Q4_1], matmul_q4_1_q8_1, mmq_wg_denoms, warptile_mmq_int, vk_mat_mat_push_constants, 3, );
+-            CREATE_MMQ(GGML_TYPE_Q5_0, pipeline_dequant_mul_mat_mat_q8_1[GGML_TYPE_Q5_0], matmul_q5_0_q8_1, mmq_wg_denoms, warptile_mmq_int, vk_mat_mat_push_constants, 3, );
+-            CREATE_MMQ(GGML_TYPE_Q5_1, pipeline_dequant_mul_mat_mat_q8_1[GGML_TYPE_Q5_1], matmul_q5_1_q8_1, mmq_wg_denoms, warptile_mmq_int, vk_mat_mat_push_constants, 3, );
+-            CREATE_MMQ(GGML_TYPE_Q8_0, pipeline_dequant_mul_mat_mat_q8_1[GGML_TYPE_Q8_0], matmul_q8_0_q8_1, mmq_wg_denoms, warptile_mmq_int, vk_mat_mat_push_constants, 3, );
++            CREATE_MMQ(GGML_TYPE_Q4_0, pipeline_dequant_mul_mat_mat_q8_1[GGML_TYPE_Q4_0], matmul_q4_0_q8_1, mmq_wg_denoms, warptile_mmq_int, vk_mat_mat_push_constants, 3, , 0);
++            CREATE_MMQ(GGML_TYPE_Q4_1, pipeline_dequant_mul_mat_mat_q8_1[GGML_TYPE_Q4_1], matmul_q4_1_q8_1, mmq_wg_denoms, warptile_mmq_int, vk_mat_mat_push_constants, 3, , 0);
++            CREATE_MMQ(GGML_TYPE_Q5_0, pipeline_dequant_mul_mat_mat_q8_1[GGML_TYPE_Q5_0], matmul_q5_0_q8_1, mmq_wg_denoms, warptile_mmq_int, vk_mat_mat_push_constants, 3, , 0);
++            CREATE_MMQ(GGML_TYPE_Q5_1, pipeline_dequant_mul_mat_mat_q8_1[GGML_TYPE_Q5_1], matmul_q5_1_q8_1, mmq_wg_denoms, warptile_mmq_int, vk_mat_mat_push_constants, 3, , 0);
++            CREATE_MMQ(GGML_TYPE_Q8_0, pipeline_dequant_mul_mat_mat_q8_1[GGML_TYPE_Q8_0], matmul_q8_0_q8_1, mmq_wg_denoms, warptile_mmq_int, vk_mat_mat_push_constants, 3, , 0);
++
++            CREATE_MMQ(GGML_TYPE_MXFP4, pipeline_dequant_mul_mat_mat_q8_1[GGML_TYPE_MXFP4], matmul_mxfp4_q8_1, mmq_wg_denoms, warptile_mmq_int, vk_mat_mat_push_constants, 3, , 0);
++
++            CREATE_MMQ(GGML_TYPE_Q2_K, pipeline_dequant_mul_mat_mat_q8_1[GGML_TYPE_Q2_K], matmul_q2_k_q8_1, mmq_wg_denoms, warptile_mmq_int_k, vk_mat_mat_push_constants, 3, , 0);
++            CREATE_MMQ(GGML_TYPE_Q3_K, pipeline_dequant_mul_mat_mat_q8_1[GGML_TYPE_Q3_K], matmul_q3_k_q8_1, mmq_wg_denoms, warptile_mmq_int_k, vk_mat_mat_push_constants, 3, , 0);
++            CREATE_MMQ(GGML_TYPE_Q4_K, pipeline_dequant_mul_mat_mat_q8_1[GGML_TYPE_Q4_K], matmul_q4_k_q8_1, mmq_wg_denoms, warptile_mmq_int_k, vk_mat_mat_push_constants, 3, , 0);
++            CREATE_MMQ(GGML_TYPE_Q5_K, pipeline_dequant_mul_mat_mat_q8_1[GGML_TYPE_Q5_K], matmul_q5_k_q8_1, mmq_wg_denoms, warptile_mmq_int_k, vk_mat_mat_push_constants, 3, , 0);
++            CREATE_MMQ(GGML_TYPE_Q6_K, pipeline_dequant_mul_mat_mat_q8_1[GGML_TYPE_Q6_K], matmul_q6_k_q8_1, mmq_wg_denoms, warptile_mmq_int_k, vk_mat_mat_push_constants, 3, , 0);
+         }
+ #endif
+ 
+@@ -2997,6 +3020,24 @@ static void ggml_vk_load_shaders(vk_device& device) {
+             CREATE_MM2(GGML_TYPE_IQ4_XS,  pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ4_XS],  matmul_id_subgroup_iq4_xs_f32,  mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4, _id, mul_mat_subgroup_size);
+             CREATE_MM2(GGML_TYPE_IQ4_NL,  pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ4_NL],  matmul_id_subgroup_iq4_nl_f32,  mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4, _id, mul_mat_subgroup_size);
+             CREATE_MM2(GGML_TYPE_MXFP4,   pipeline_dequant_mul_mat_mat_id[GGML_TYPE_MXFP4],   matmul_id_subgroup_mxfp4_f32,   mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4, _id, mul_mat_subgroup_size);
++
++#if defined(GGML_VULKAN_INTEGER_DOT_GLSLC_SUPPORT)
++            if (device->integer_dot_product) {
++                CREATE_MMQ(GGML_TYPE_Q4_0, pipeline_dequant_mul_mat_mat_id_q8_1[GGML_TYPE_Q4_0], matmul_id_subgroup_q4_0_q8_1, mmq_wg_denoms, warptile_mmqid_int,   vk_mat_mat_id_push_constants, 4, _id, mul_mat_subgroup_size);
++                CREATE_MMQ(GGML_TYPE_Q4_1, pipeline_dequant_mul_mat_mat_id_q8_1[GGML_TYPE_Q4_1], matmul_id_subgroup_q4_1_q8_1, mmq_wg_denoms, warptile_mmqid_int,   vk_mat_mat_id_push_constants, 4, _id, mul_mat_subgroup_size);
++                CREATE_MMQ(GGML_TYPE_Q5_0, pipeline_dequant_mul_mat_mat_id_q8_1[GGML_TYPE_Q5_0], matmul_id_subgroup_q5_0_q8_1, mmq_wg_denoms, warptile_mmqid_int,   vk_mat_mat_id_push_constants, 4, _id, mul_mat_subgroup_size);
++                CREATE_MMQ(GGML_TYPE_Q5_1, pipeline_dequant_mul_mat_mat_id_q8_1[GGML_TYPE_Q5_1], matmul_id_subgroup_q5_1_q8_1, mmq_wg_denoms, warptile_mmqid_int,   vk_mat_mat_id_push_constants, 4, _id, mul_mat_subgroup_size);
++                CREATE_MMQ(GGML_TYPE_Q8_0, pipeline_dequant_mul_mat_mat_id_q8_1[GGML_TYPE_Q8_0], matmul_id_subgroup_q8_0_q8_1, mmq_wg_denoms, warptile_mmqid_int,   vk_mat_mat_id_push_constants, 4, _id, mul_mat_subgroup_size);
++
++                CREATE_MMQ(GGML_TYPE_MXFP4, pipeline_dequant_mul_mat_mat_id_q8_1[GGML_TYPE_MXFP4], matmul_id_subgroup_mxfp4_q8_1, mmq_wg_denoms, warptile_mmqid_int,   vk_mat_mat_id_push_constants, 4, _id, mul_mat_subgroup_size);
++
++                CREATE_MMQ(GGML_TYPE_Q2_K, pipeline_dequant_mul_mat_mat_id_q8_1[GGML_TYPE_Q2_K], matmul_id_subgroup_q2_k_q8_1, mmq_wg_denoms, warptile_mmqid_int_k, vk_mat_mat_id_push_constants, 4, _id, mul_mat_subgroup_size_16);
++                CREATE_MMQ(GGML_TYPE_Q3_K, pipeline_dequant_mul_mat_mat_id_q8_1[GGML_TYPE_Q3_K], matmul_id_subgroup_q3_k_q8_1, mmq_wg_denoms, warptile_mmqid_int_k, vk_mat_mat_id_push_constants, 4, _id, mul_mat_subgroup_size_16);
++                CREATE_MMQ(GGML_TYPE_Q4_K, pipeline_dequant_mul_mat_mat_id_q8_1[GGML_TYPE_Q4_K], matmul_id_subgroup_q4_k_q8_1, mmq_wg_denoms, warptile_mmqid_int_k, vk_mat_mat_id_push_constants, 4, _id, mul_mat_subgroup_size_16);
++                CREATE_MMQ(GGML_TYPE_Q5_K, pipeline_dequant_mul_mat_mat_id_q8_1[GGML_TYPE_Q5_K], matmul_id_subgroup_q5_k_q8_1, mmq_wg_denoms, warptile_mmqid_int_k, vk_mat_mat_id_push_constants, 4, _id, mul_mat_subgroup_size_16);
++                CREATE_MMQ(GGML_TYPE_Q6_K, pipeline_dequant_mul_mat_mat_id_q8_1[GGML_TYPE_Q6_K], matmul_id_subgroup_q6_k_q8_1, mmq_wg_denoms, warptile_mmqid_int_k, vk_mat_mat_id_push_constants, 4, _id, mul_mat_subgroup_size_16);
++            }
++#endif
+         } else {
+             CREATE_MM(GGML_TYPE_F32, pipeline_matmul_id_f32, matmul_id_f32_f32, , wg_denoms, warptile, vk_mat_mat_push_constants, 4, _id, 0);
+             CREATE_MM2(GGML_TYPE_F16, pipeline_matmul_id_f16, matmul_id_f16, wg_denoms, warptile, vk_mat_mat_push_constants, 4, _id, 0);
+@@ -3023,6 +3064,24 @@ static void ggml_vk_load_shaders(vk_device& device) {
+             CREATE_MM2(GGML_TYPE_IQ4_XS,  pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ4_XS],  matmul_id_iq4_xs_f32,  mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4, _id, 0);
+             CREATE_MM2(GGML_TYPE_IQ4_NL,  pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ4_NL],  matmul_id_iq4_nl_f32,  mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4, _id, 0);
+             CREATE_MM2(GGML_TYPE_MXFP4,   pipeline_dequant_mul_mat_mat_id[GGML_TYPE_MXFP4],   matmul_id_mxfp4_f32,   mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4, _id, 0);
++
++#if defined(GGML_VULKAN_INTEGER_DOT_GLSLC_SUPPORT)
++            if (device->integer_dot_product) {
++                CREATE_MMQ(GGML_TYPE_Q4_0, pipeline_dequant_mul_mat_mat_id_q8_1[GGML_TYPE_Q4_0], matmul_id_q4_0_q8_1, mmq_wg_denoms, warptile_mmqid_int,   vk_mat_mat_id_push_constants, 4, _id, 0);
++                CREATE_MMQ(GGML_TYPE_Q4_1, pipeline_dequant_mul_mat_mat_id_q8_1[GGML_TYPE_Q4_1], matmul_id_q4_1_q8_1, mmq_wg_denoms, warptile_mmqid_int,   vk_mat_mat_id_push_constants, 4, _id, 0);
++                CREATE_MMQ(GGML_TYPE_Q5_0, pipeline_dequant_mul_mat_mat_id_q8_1[GGML_TYPE_Q5_0], matmul_id_q5_0_q8_1, mmq_wg_denoms, warptile_mmqid_int,   vk_mat_mat_id_push_constants, 4, _id, 0);
++                CREATE_MMQ(GGML_TYPE_Q5_1, pipeline_dequant_mul_mat_mat_id_q8_1[GGML_TYPE_Q5_1], matmul_id_q5_1_q8_1, mmq_wg_denoms, warptile_mmqid_int,   vk_mat_mat_id_push_constants, 4, _id, 0);
++                CREATE_MMQ(GGML_TYPE_Q8_0, pipeline_dequant_mul_mat_mat_id_q8_1[GGML_TYPE_Q8_0], matmul_id_q8_0_q8_1, mmq_wg_denoms, warptile_mmqid_int,   vk_mat_mat_id_push_constants, 4, _id, 0);
++
++                CREATE_MMQ(GGML_TYPE_MXFP4, pipeline_dequant_mul_mat_mat_id_q8_1[GGML_TYPE_MXFP4], matmul_id_mxfp4_q8_1, mmq_wg_denoms, warptile_mmqid_int,   vk_mat_mat_id_push_constants, 4, _id, 0);
++
++                CREATE_MMQ(GGML_TYPE_Q2_K, pipeline_dequant_mul_mat_mat_id_q8_1[GGML_TYPE_Q2_K], matmul_id_q2_k_q8_1, mmq_wg_denoms, warptile_mmqid_int_k, vk_mat_mat_id_push_constants, 4, _id, 0);
++                CREATE_MMQ(GGML_TYPE_Q3_K, pipeline_dequant_mul_mat_mat_id_q8_1[GGML_TYPE_Q3_K], matmul_id_q3_k_q8_1, mmq_wg_denoms, warptile_mmqid_int_k, vk_mat_mat_id_push_constants, 4, _id, 0);
++                CREATE_MMQ(GGML_TYPE_Q4_K, pipeline_dequant_mul_mat_mat_id_q8_1[GGML_TYPE_Q4_K], matmul_id_q4_k_q8_1, mmq_wg_denoms, warptile_mmqid_int_k, vk_mat_mat_id_push_constants, 4, _id, 0);
++                CREATE_MMQ(GGML_TYPE_Q5_K, pipeline_dequant_mul_mat_mat_id_q8_1[GGML_TYPE_Q5_K], matmul_id_q5_k_q8_1, mmq_wg_denoms, warptile_mmqid_int_k, vk_mat_mat_id_push_constants, 4, _id, 0);
++                CREATE_MMQ(GGML_TYPE_Q6_K, pipeline_dequant_mul_mat_mat_id_q8_1[GGML_TYPE_Q6_K], matmul_id_q6_k_q8_1, mmq_wg_denoms, warptile_mmqid_int_k, vk_mat_mat_id_push_constants, 4, _id, 0);
++            }
++#endif
+         }
+ #undef CREATE_MM2
+ #undef CREATE_MMQ
+@@ -3087,6 +3146,12 @@ static void ggml_vk_load_shaders(vk_device& device) {
+             CREATE_MMQ(GGML_TYPE_Q5_0, pipeline_dequant_mul_mat_mat_q8_1[GGML_TYPE_Q5_0].f32acc, matmul_q5_0_q8_1, mmq_wg_denoms, warptile_mmq_int, vk_mat_mat_push_constants, 3, );
+             CREATE_MMQ(GGML_TYPE_Q5_1, pipeline_dequant_mul_mat_mat_q8_1[GGML_TYPE_Q5_1].f32acc, matmul_q5_1_q8_1, mmq_wg_denoms, warptile_mmq_int, vk_mat_mat_push_constants, 3, );
+             CREATE_MMQ(GGML_TYPE_Q8_0, pipeline_dequant_mul_mat_mat_q8_1[GGML_TYPE_Q8_0].f32acc, matmul_q8_0_q8_1, mmq_wg_denoms, warptile_mmq_int, vk_mat_mat_push_constants, 3, );
++
++            CREATE_MMQ(GGML_TYPE_Q2_K, pipeline_dequant_mul_mat_mat_q8_1[GGML_TYPE_Q2_K].f32acc, matmul_q2_k_q8_1, mmq_wg_denoms, warptile_mmq_int_k, vk_mat_mat_push_constants, 3, );
++            CREATE_MMQ(GGML_TYPE_Q3_K, pipeline_dequant_mul_mat_mat_q8_1[GGML_TYPE_Q3_K].f32acc, matmul_q3_k_q8_1, mmq_wg_denoms, warptile_mmq_int_k, vk_mat_mat_push_constants, 3, );
++            CREATE_MMQ(GGML_TYPE_Q4_K, pipeline_dequant_mul_mat_mat_q8_1[GGML_TYPE_Q4_K].f32acc, matmul_q4_k_q8_1, mmq_wg_denoms, warptile_mmq_int_k, vk_mat_mat_push_constants, 3, );
++            CREATE_MMQ(GGML_TYPE_Q5_K, pipeline_dequant_mul_mat_mat_q8_1[GGML_TYPE_Q5_K].f32acc, matmul_q5_k_q8_1, mmq_wg_denoms, warptile_mmq_int_k, vk_mat_mat_push_constants, 3, );
++            CREATE_MMQ(GGML_TYPE_Q6_K, pipeline_dequant_mul_mat_mat_q8_1[GGML_TYPE_Q6_K].f32acc, matmul_q6_k_q8_1, mmq_wg_denoms, warptile_mmq_int_k, vk_mat_mat_push_constants, 3, );
+         }
+ #endif
+ 
+@@ -3146,7 +3211,7 @@ static void ggml_vk_load_shaders(vk_device& device) {
+     }
+     // reusing CREATE_MM from the fp32 path
+     if ((device->coopmat2 || device->coopmat_support)
+-#if defined(GGML_VULKAN_INTEGER_DOT_GLSLC_SUPPORT)
++#if defined(GGML_VULKAN_BFLOAT16_GLSLC_SUPPORT)
+         && !device->coopmat_bf16_support
+ #endif
+         ) {
+@@ -4930,7 +4995,7 @@ static vk_matmul_pipeline ggml_vk_get_mul_mat_mat_pipeline(ggml_backend_vk_conte
+ 
+     // MMQ
+     if (src1_type == GGML_TYPE_Q8_1) {
+-        vk_matmul_pipeline pipelines = (ctx->device->fp16 && prec == GGML_PREC_DEFAULT) ? ctx->device->pipeline_dequant_mul_mat_mat_q8_1[src0_type].f16acc : ctx->device->pipeline_dequant_mul_mat_mat_q8_1[src0_type].f32acc;
++        vk_matmul_pipeline pipelines = ctx->device->pipeline_dequant_mul_mat_mat_q8_1[src0_type].f32acc;
+ 
+         if (pipelines->s == nullptr && pipelines->m == nullptr && pipelines->l == nullptr) {
+             return nullptr;
+@@ -5077,6 +5142,17 @@ static vk_matmul_pipeline ggml_vk_get_mul_mat_mat_id_pipeline(ggml_backend_vk_co
+         }
+     }
+ 
++    // MMQ
++    if (src1_type == GGML_TYPE_Q8_1) {
++        vk_matmul_pipeline pipelines = ctx->device->pipeline_dequant_mul_mat_mat_id_q8_1[src0_type].f32acc;
++
++        if (pipelines->s == nullptr && pipelines->m == nullptr && pipelines->l == nullptr) {
++            return nullptr;
++        }
++
++        return pipelines;
++    }
++
+     GGML_ASSERT(src1_type == GGML_TYPE_F32 || (ctx->device->coopmat2 && src1_type == GGML_TYPE_F16));
+ 
+     switch (src0_type) {
+@@ -6879,10 +6955,19 @@ static void ggml_vk_mul_mat_id_q_f16(ggml_backend_vk_context * ctx, vk_context&
+ 
+     const bool y_f32_kernel = src1->type == GGML_TYPE_F32 && !y_non_contig;
+ 
+-    vk_matmul_pipeline mmp = ggml_vk_get_mul_mat_mat_id_pipeline(ctx, src0->type, y_non_contig ? f16_type : src1->type, (ggml_prec)dst->op_params[0]);
++    bool quantize_y = ctx->device->integer_dot_product && src1->type == GGML_TYPE_F32 && ggml_is_contiguous(src1) && (ne11 * ne10) % 4 == 0;
++
++    // Check for mmq first
++    vk_matmul_pipeline mmp = quantize_y ? ggml_vk_get_mul_mat_mat_id_pipeline(ctx, src0->type, GGML_TYPE_Q8_1, (ggml_prec)dst->op_params[0]) : nullptr;
++
++    if (mmp == nullptr) {
++        // Fall back to f16 dequant mul mat
++        mmp = ggml_vk_get_mul_mat_mat_id_pipeline(ctx, src0->type, y_non_contig ? f16_type : src1->type, (ggml_prec)dst->op_params[0]);
++        quantize_y = false;
++    }
+ 
+     const bool qx_needs_dequant = mmp == nullptr || x_non_contig;
+-    const bool qy_needs_dequant = (src1->type != f16_type && !y_f32_kernel) || y_non_contig;
++    const bool qy_needs_dequant = !quantize_y && ((src1->type != f16_type && !y_f32_kernel) || y_non_contig);
+ 
+     if (qx_needs_dequant) {
+         // Fall back to dequant + f16 mulmat
+@@ -6892,8 +6977,8 @@ static void ggml_vk_mul_mat_id_q_f16(ggml_backend_vk_context * ctx, vk_context&
+     // Not implemented
+     GGML_ASSERT(y_non_contig || !qy_needs_dequant);  // NOLINT
+ 
+-    const uint32_t kpad = ggml_vk_align_size(ne10, ggml_vk_guess_matmul_id_pipeline_align(ctx, mmp, ne01, nei1, qx_needs_dequant ? f16_type : src0->type));
+-    const bool aligned = ne10 == kpad && ne01 > 8 && nei1 > 8;
++    const uint32_t kpad = quantize_y ? 0 : ggml_vk_align_size(ne10, ggml_vk_guess_matmul_id_pipeline_align(ctx, mmp, ne01, nei1, qx_needs_dequant ? f16_type : src0->type));
++    const bool aligned = !quantize_y && ne10 == kpad && ne01 > 8 && nei1 > 8;
+ 
+     vk_pipeline pipeline = ggml_vk_guess_matmul_id_pipeline(ctx, mmp, ne01, nei1, aligned, qx_needs_dequant ? f16_type : src0->type);
+ 
+@@ -6906,12 +6991,13 @@ static void ggml_vk_mul_mat_id_q_f16(ggml_backend_vk_context * ctx, vk_context&
+     const uint64_t qx_sz = ggml_type_size(src0->type) * x_ne / ggml_blck_size(src0->type);
+     const uint64_t qy_sz = ggml_type_size(src1->type) * y_ne / ggml_blck_size(src1->type);
+     const uint64_t x_sz = !qx_needs_dequant ? qx_sz : sizeof(ggml_fp16_t) * x_ne;
+-    const uint64_t y_sz = y_f32_kernel ? sizeof(float) * y_ne : sizeof(ggml_fp16_t) * y_ne;
++    const uint64_t y_sz = quantize_y ? (y_ne * ggml_type_size(GGML_TYPE_Q8_1) / ggml_blck_size(GGML_TYPE_Q8_1)) : (y_f32_kernel ? sizeof(float) * y_ne : sizeof(ggml_fp16_t) * y_ne);
+     const uint64_t ids_sz = nbi2;
+     const uint64_t d_sz = sizeof(float) * d_ne;
+ 
+     vk_pipeline to_fp16_vk_0 = nullptr;
+     vk_pipeline to_fp16_vk_1 = nullptr;
++    vk_pipeline to_q8_1 = nullptr;
+ 
+     if (x_non_contig) {
+         to_fp16_vk_0 = ggml_vk_get_cpy_pipeline(ctx, src0, nullptr, f16_type);
+@@ -6926,9 +7012,16 @@ static void ggml_vk_mul_mat_id_q_f16(ggml_backend_vk_context * ctx, vk_context&
+     GGML_ASSERT(!qx_needs_dequant || to_fp16_vk_0 != nullptr);  // NOLINT
+     GGML_ASSERT(!qy_needs_dequant || to_fp16_vk_1 != nullptr);  // NOLINT
+ 
++    if (quantize_y) {
++        to_q8_1 = ggml_vk_get_quantize_pipeline(ctx, GGML_TYPE_Q8_1, true);
++    }
++
+     if (dryrun) {
+         const uint64_t x_sz_upd = x_sz * ne02 * ne03;
+-        const uint64_t y_sz_upd = y_sz * ne12 * ne13;
++        uint64_t y_sz_upd = y_sz * ne12 * ne13;
++        if (quantize_y) {
++            y_sz_upd = CEIL_DIV(y_sz_upd, 144) * 144;
++        }
+         if (
+                 (qx_needs_dequant && x_sz_upd > ctx->device->properties.limits.maxStorageBufferRange) ||
+                 (qy_needs_dequant && y_sz_upd > ctx->device->properties.limits.maxStorageBufferRange)) {
+@@ -6937,7 +7030,7 @@ static void ggml_vk_mul_mat_id_q_f16(ggml_backend_vk_context * ctx, vk_context&
+         if (qx_needs_dequant && ctx->prealloc_size_x < x_sz_upd) {
+             ctx->prealloc_size_x = x_sz_upd;
+         }
+-        if (qy_needs_dequant && ctx->prealloc_size_y < y_sz_upd) {
++        if ((qy_needs_dequant || quantize_y) && ctx->prealloc_size_y < y_sz_upd) {
+             ctx->prealloc_size_y = y_sz_upd;
+         }
+ 
+@@ -6949,6 +7042,9 @@ static void ggml_vk_mul_mat_id_q_f16(ggml_backend_vk_context * ctx, vk_context&
+         if (qy_needs_dequant) {
+             ggml_pipeline_request_descriptor_sets(ctx, to_fp16_vk_1, 1);
+         }
++        if (quantize_y) {
++            ggml_pipeline_request_descriptor_sets(ctx, to_q8_1, 1);
++        }
+         return;
+     }
+ 
+@@ -6985,6 +7081,9 @@ static void ggml_vk_mul_mat_id_q_f16(ggml_backend_vk_context * ctx, vk_context&
+     if (qy_needs_dequant) {
+         d_Y = ctx->prealloc_y;
+         GGML_ASSERT(d_Y->size >= y_sz * ne12 * ne13);
++    } else if (quantize_y) {
++        d_Y = ctx->prealloc_y;
++        GGML_ASSERT(d_Y->size >= CEIL_DIV(y_sz * ne12 * ne13, 144) * 144);
+     } else {
+         d_Y = d_Qy;
+         y_buf_offset = qy_buf_offset;
+@@ -7016,6 +7115,17 @@ static void ggml_vk_mul_mat_id_q_f16(ggml_backend_vk_context * ctx, vk_context&
+             ctx->prealloc_y_last_tensor_used = src1;
+         }
+     }
++    if (quantize_y) {
++        if (ctx->prealloc_y_last_pipeline_used != to_q8_1.get() ||
++            ctx->prealloc_y_last_tensor_used != src1) {
++            if (ctx->prealloc_y_need_sync) {
++                ggml_vk_sync_buffers(ctx, subctx);
++            }
++            ggml_vk_quantize_q8_1(ctx, subctx, ggml_vk_subbuffer(ctx, d_Qy, qy_buf_offset), ggml_vk_subbuffer(ctx, d_Y, 0), y_ne * ne12 * ne13, true);
++            ctx->prealloc_y_last_pipeline_used = to_q8_1.get();
++            ctx->prealloc_y_last_tensor_used = src1;
++        }
++    }
+ 
+     uint32_t stride_batch_x = ne00*ne01;
+     uint32_t stride_batch_y = ne10*ne11;
+@@ -7024,14 +7134,19 @@ static void ggml_vk_mul_mat_id_q_f16(ggml_backend_vk_context * ctx, vk_context&
+         stride_batch_x = src0->nb[0] / ggml_type_size(src0->type);
+     }
+ 
+-    if (!ggml_vk_dim01_contiguous(src1) && !qy_needs_dequant) {
++    if (!ggml_vk_dim01_contiguous(src1) && !qy_needs_dequant && !quantize_y) {
+         stride_batch_y = src1->nb[0] / ggml_type_size(src1->type);
+     }
+ 
++    uint32_t y_sz_total = y_sz * ne12 * ne13;
++    if (quantize_y) {
++        y_sz_total = CEIL_DIV(y_sz_total, 144) * 144;
++    }
++
+     // compute
+     ggml_vk_matmul_id(
+         ctx, subctx, pipeline,
+-        { d_X, x_buf_offset, x_sz * ne02 * ne03 }, { d_Y, y_buf_offset, y_sz * ne12 * ne13 },
++        { d_X, x_buf_offset, x_sz * ne02 * ne03 }, { d_Y, y_buf_offset, y_sz_total },
+         { d_D, d_buf_offset, d_sz * ne22 * ne23 }, { d_ids, ids_buf_offset, ids_sz },
+         ne01, ne21, ne10, ne10, ne10, ne01,
+         stride_batch_x, stride_batch_y, ne20*ne21,
+diff --git a/ggml/src/ggml-vulkan/vulkan-shaders/dequant_funcs.glsl b/ggml/src/ggml-vulkan/vulkan-shaders/dequant_funcs.glsl
+index 0d98f5a9d..09676a623 100644
+--- a/ggml/src/ggml-vulkan/vulkan-shaders/dequant_funcs.glsl
++++ b/ggml/src/ggml-vulkan/vulkan-shaders/dequant_funcs.glsl
+@@ -437,7 +437,7 @@ vec4 dequantize4(uint ib, uint iqs, uint a_offset) {
+ #if defined(DATA_A_MXFP4)
+ vec2 dequantize(uint ib, uint iqs, uint a_offset) {
+     const uint vui = uint(data_a[a_offset + ib].qs[iqs]);
+-    return vec2(kvalues_mxfp4[vui & 0xF], kvalues_mxfp4[vui >> 4]);
++    return vec2(kvalues_mxfp4[vui & 0xF], kvalues_mxfp4[vui >> 4]) * 0.5;
+ }
+ vec4 dequantize4(uint ib, uint iqs, uint a_offset) {
+     vec2 v0 = dequantize(ib, iqs, a_offset);
+@@ -488,9 +488,9 @@ vec2 dequantize(uint ib, uint iqs, uint a_offset) {
+ 
+     const uvec2 qs = uvec2(data_a[a_offset + ib].qs[qsi], data_a[a_offset + ib].qs[qsi + 1]);
+     const uint scales = data_a[a_offset + ib].scales[scalesi];
+-    const vec2 d = vec2(data_a[a_offset + ib].d);
++    const vec2 dm = vec2(data_a[a_offset + ib].dm);
+ 
+-    return d.x * float(scales & 0xF) * vec2((qs >> qsshift) & 3) - d.y * float(scales >> 4);
++    return dm.x * float(scales & 0xF) * vec2((qs >> qsshift) & 3) - dm.y * float(scales >> 4);
+ }
+ vec2 get_dm(uint ib, uint a_offset) {
+     return vec2(1, 0);
+@@ -529,7 +529,7 @@ vec2 dequantize(uint ib, uint iqs, uint a_offset) {
+     const uint is = 2 * n + b;                 // 0..7
+     const uint qsi = n * 32 + (iqs % 16) * 2;  // 0,2,4..126
+ 
+-    const vec2 loadd = vec2(data_a[a_offset + ib].d);
++    const vec2 loadd = vec2(data_a[a_offset + ib].dm);
+ 
+     const uint scidx0 = (is < 4) ? is : (is + 4);
+     const uint scidx1 = (is < 4) ? is : (is - 4);
+@@ -567,7 +567,7 @@ vec2 dequantize(uint ib, uint iqs, uint a_offset) {
+ 
+     const uint8_t hm = uint8_t(1 << (iqs / 16));
+ 
+-    const vec2 loadd = vec2(data_a[a_offset + ib].d);
++    const vec2 loadd = vec2(data_a[a_offset + ib].dm);
+ 
+     const uint scidx0 = (is < 4) ? is : (is + 4);
+     const uint scidx1 = (is < 4) ? is : (is - 4);
+diff --git a/ggml/src/ggml-vulkan/vulkan-shaders/dequant_funcs_cm2.glsl b/ggml/src/ggml-vulkan/vulkan-shaders/dequant_funcs_cm2.glsl
+index 67baedf7c..8ac6482dc 100644
+--- a/ggml/src/ggml-vulkan/vulkan-shaders/dequant_funcs_cm2.glsl
++++ b/ggml/src/ggml-vulkan/vulkan-shaders/dequant_funcs_cm2.glsl
+@@ -120,7 +120,7 @@ layout(buffer_reference, std430, buffer_reference_align = 16) buffer decodeBufQ2
+ float16_t dequantFuncQ2_K(const in decodeBufQ2_K bl, const in uint blockCoords[2], const in uint coordInBlock[2])
+ {
+     decodeBufQ2_K_packed16 bl16 = decodeBufQ2_K_packed16(bl);
+-    const f16vec2 d = bl.block.d;
++    const f16vec2 dm = bl.block.dm;
+     const uint idx = coordInBlock[1];
+ 
+     const uint scalesi = (idx & 0xF0) >> 4;             // 0..15
+@@ -131,7 +131,7 @@ float16_t dequantFuncQ2_K(const in decodeBufQ2_K bl, const in uint blockCoords[2
+     qs = unpack8(qs)[idx & 1];
+ 
+     const uint scales = bl.block.scales[scalesi];
+-    float16_t ret = d.x * float16_t(scales & 0xF) * float16_t(qs) - d.y * float16_t(scales >> 4);
++    float16_t ret = dm.x * float16_t(scales & 0xF) * float16_t(qs) - dm.y * float16_t(scales >> 4);
+     return ret;
+ }
+ 
+@@ -680,7 +680,7 @@ float16_t dequantFuncMXFP4(const in decodeBufMXFP4 bl, const in uint blockCoords
+     uint32_t qs = bl.block.qs[iqs];
+     qs >>= shift;
+     qs &= 0xF;
+-    float16_t ret = float16_t(kvalues_mxfp4[qs] * d);
++    float16_t ret = float16_t(kvalues_mxfp4[qs] * d * 0.5);
+     return ret;
+ }
+ #endif
+diff --git a/ggml/src/ggml-vulkan/vulkan-shaders/dequant_mxfp4.comp b/ggml/src/ggml-vulkan/vulkan-shaders/dequant_mxfp4.comp
+index ffba5a77d..3194ba291 100644
+--- a/ggml/src/ggml-vulkan/vulkan-shaders/dequant_mxfp4.comp
++++ b/ggml/src/ggml-vulkan/vulkan-shaders/dequant_mxfp4.comp
+@@ -26,7 +26,7 @@ void main() {
+     const float d = e8m0_to_fp32(data_a[ib].e);
+ 
+     [[unroll]] for (uint l = 0; l < 8; ++l) {
+-        data_b[b_idx + l +  0] = D_TYPE(d * kvalues_mxfp4[data_a[ib].qs[q_idx + l] & 0xF]);
+-        data_b[b_idx + l + 16] = D_TYPE(d * kvalues_mxfp4[data_a[ib].qs[q_idx + l] >>  4]);
++        data_b[b_idx + l +  0] = D_TYPE(d * 0.5 * float(kvalues_mxfp4[data_a[ib].qs[q_idx + l] & 0xF]));
++        data_b[b_idx + l + 16] = D_TYPE(d * 0.5 * float(kvalues_mxfp4[data_a[ib].qs[q_idx + l] >>  4]));
+     }
+ }
+diff --git a/ggml/src/ggml-vulkan/vulkan-shaders/dequant_q2_k.comp b/ggml/src/ggml-vulkan/vulkan-shaders/dequant_q2_k.comp
+index 58dc2e5df..dc05a7834 100644
+--- a/ggml/src/ggml-vulkan/vulkan-shaders/dequant_q2_k.comp
++++ b/ggml/src/ggml-vulkan/vulkan-shaders/dequant_q2_k.comp
+@@ -24,8 +24,8 @@ void main() {
+         const uint ql_idx = 32 * ip + il;
+         const uint8_t qs = data_a[i].qs[32 * ip + il];
+ 
+-        FLOAT_TYPE dall = FLOAT_TYPE(data_a[i].d.x);
+-        FLOAT_TYPE dmin = FLOAT_TYPE(data_a[i].d.y);
++        FLOAT_TYPE dall = FLOAT_TYPE(data_a[i].dm.x);
++        FLOAT_TYPE dmin = FLOAT_TYPE(data_a[i].dm.y);
+         data_b[y_idx +  0] = D_TYPE(dall * FLOAT_TYPE((data_a[i].scales[is+0] & 0xF) * ((qs >> 0) & 3)) - dmin * FLOAT_TYPE(data_a[i].scales[is+0] >> 4));
+         data_b[y_idx + 32] = D_TYPE(dall * FLOAT_TYPE((data_a[i].scales[is+2] & 0xF) * ((qs >> 2) & 3)) - dmin * FLOAT_TYPE(data_a[i].scales[is+2] >> 4));
+         data_b[y_idx + 64] = D_TYPE(dall * FLOAT_TYPE((data_a[i].scales[is+4] & 0xF) * ((qs >> 4) & 3)) - dmin * FLOAT_TYPE(data_a[i].scales[is+4] >> 4));
+diff --git a/ggml/src/ggml-vulkan/vulkan-shaders/dequant_q4_k.comp b/ggml/src/ggml-vulkan/vulkan-shaders/dequant_q4_k.comp
+index 8b7be557e..0f23dc0a3 100644
+--- a/ggml/src/ggml-vulkan/vulkan-shaders/dequant_q4_k.comp
++++ b/ggml/src/ggml-vulkan/vulkan-shaders/dequant_q4_k.comp
+@@ -20,8 +20,8 @@ void main() {
+         const uint is = 2 * il;
+         const uint n = 4;
+ 
+-        const FLOAT_TYPE dall = FLOAT_TYPE(data_a[ib].d.x);
+-        const FLOAT_TYPE dmin = FLOAT_TYPE(data_a[ib].d.y);
++        const FLOAT_TYPE dall = FLOAT_TYPE(data_a[ib].dm.x);
++        const FLOAT_TYPE dmin = FLOAT_TYPE(data_a[ib].dm.y);
+ 
+         const uint y_idx = ib * QUANT_K + 64 * il + n * ir;
+         const uint qs_idx = 32*il + n * ir;
+diff --git a/ggml/src/ggml-vulkan/vulkan-shaders/dequant_q5_k.comp b/ggml/src/ggml-vulkan/vulkan-shaders/dequant_q5_k.comp
+index 6bc04670f..970469a60 100644
+--- a/ggml/src/ggml-vulkan/vulkan-shaders/dequant_q5_k.comp
++++ b/ggml/src/ggml-vulkan/vulkan-shaders/dequant_q5_k.comp
+@@ -19,8 +19,8 @@ void main() {
+         const uint ir = tid % 16;
+         const uint is = 2 * il;
+ 
+-        const FLOAT_TYPE dall = FLOAT_TYPE(data_a[ib].d.x);
+-        const FLOAT_TYPE dmin = FLOAT_TYPE(data_a[ib].d.y);
++        const FLOAT_TYPE dall = FLOAT_TYPE(data_a[ib].dm.x);
++        const FLOAT_TYPE dmin = FLOAT_TYPE(data_a[ib].dm.y);
+ 
+         const uint y_idx = ib * QUANT_K + 64 * il + 2 * ir;
+         const uint qs_idx = 32*il + 2 * ir;
+diff --git a/ggml/src/ggml-vulkan/vulkan-shaders/mul_mat_vec_q2_k.comp b/ggml/src/ggml-vulkan/vulkan-shaders/mul_mat_vec_q2_k.comp
+index 03ed25d3b..14093c0de 100644
+--- a/ggml/src/ggml-vulkan/vulkan-shaders/mul_mat_vec_q2_k.comp
++++ b/ggml/src/ggml-vulkan/vulkan-shaders/mul_mat_vec_q2_k.comp
+@@ -41,9 +41,7 @@ void calc_superblock(const uint a_offset, const uint b_offset, const uint itid,
+         const vec4 qs_u32_4 = vec4(unpack8((qs_u32 >> 4) & 0x03030303));
+         const vec4 qs_u32_6 = vec4(unpack8((qs_u32 >> 6) & 0x03030303));
+ 
+-        vec2 d = vec2(data_a[ib0 + i].d);
+-        const FLOAT_TYPE dall = FLOAT_TYPE(d.x);
+-        const FLOAT_TYPE dmin = FLOAT_TYPE(d.y);
++        const FLOAT_TYPE_VEC2 dm = vec2(data_a[ib0 + i].dm);
+ 
+         [[unroll]] for (uint j = 0; j < NUM_COLS; ++j) {
+             vec2 b0 =   vec2(data_b_v2[(j*p.batch_stride_b + b_offset + y_idx) / 2 +  0]);
+@@ -75,7 +73,7 @@ void calc_superblock(const uint a_offset, const uint b_offset, const uint itid,
+                        fma(FLOAT_TYPE(b96[l]),  sccache2[csel][ix][6 + 8*v_im],
+                        fma(FLOAT_TYPE(b112[l]), sccache2[csel][ix][7 + 8*v_im], sum2))))))));
+             }
+-            temp[j][n] = fma(dall, sum1, fma(-dmin, sum2, temp[j][n]));
++            temp[j][n] = fma(dm.x, sum1, fma(-dm.y, sum2, temp[j][n]));
+         }
+     }
+ }
+diff --git a/ggml/src/ggml-vulkan/vulkan-shaders/mul_mat_vec_q4_k.comp b/ggml/src/ggml-vulkan/vulkan-shaders/mul_mat_vec_q4_k.comp
+index 21d07d2e5..49d91ad59 100644
+--- a/ggml/src/ggml-vulkan/vulkan-shaders/mul_mat_vec_q4_k.comp
++++ b/ggml/src/ggml-vulkan/vulkan-shaders/mul_mat_vec_q4_k.comp
+@@ -14,9 +14,7 @@ void calc_superblock(const uint a_offset, const uint b_offset, const uint v_im,
+ 
+     [[unroll]] for (uint n = 0; n < num_rows; ++n) {
+         const uint ib0 = a_offset / QUANT_K + (first_row+n)*num_blocks_per_row;
+-        vec2 d = vec2(data_a[ib0 + i].d);
+-        const FLOAT_TYPE dall = FLOAT_TYPE(d.x);
+-        const FLOAT_TYPE dmin = FLOAT_TYPE(d.y);
++        const FLOAT_TYPE_VEC2 dm = FLOAT_TYPE_VEC2(data_a[ib0 + i].dm);
+ 
+         const uint32_t scale0_u32 = data_a_packed16[ib0 + i].scales[v_im    ];
+         const uint32_t scale4_u32 = data_a_packed16[ib0 + i].scales[v_im + 2];
+@@ -81,7 +79,7 @@ void calc_superblock(const uint a_offset, const uint b_offset, const uint v_im,
+                 fma(FLOAT_TYPE(by10.y), sc2, fma(FLOAT_TYPE(by132.y), sc3, fma(FLOAT_TYPE(by20.y), sc6, fma(FLOAT_TYPE(by232.y), sc7,
+                 fma(FLOAT_TYPE(by10.z), sc2, fma(FLOAT_TYPE(by132.z), sc3, fma(FLOAT_TYPE(by20.z), sc6, fma(FLOAT_TYPE(by232.z), sc7,
+                 fma(FLOAT_TYPE(by10.w), sc2, fma(FLOAT_TYPE(by132.w), sc3, fma(FLOAT_TYPE(by20.w), sc6,     FLOAT_TYPE(by232.w) * sc7)))))))))))))));
+-            temp[j][n] = fma(dall, fma(sx, sc0, fma(sy, sc1, fma(sz, sc4, sw * sc5))), fma(-dmin, smin, temp[j][n]));
++            temp[j][n] = fma(dm.x, fma(sx, sc0, fma(sy, sc1, fma(sz, sc4, sw * sc5))), fma(-dm.y, smin, temp[j][n]));
+         }
+     }
+ }
+diff --git a/ggml/src/ggml-vulkan/vulkan-shaders/mul_mat_vec_q5_k.comp b/ggml/src/ggml-vulkan/vulkan-shaders/mul_mat_vec_q5_k.comp
+index 9e46c89a1..0d61b4966 100644
+--- a/ggml/src/ggml-vulkan/vulkan-shaders/mul_mat_vec_q5_k.comp
++++ b/ggml/src/ggml-vulkan/vulkan-shaders/mul_mat_vec_q5_k.comp
+@@ -14,9 +14,7 @@ void calc_superblock(const uint a_offset, const uint b_offset, const uint v_im,
+ 
+     [[unroll]] for (uint n = 0; n < num_rows; ++n) {
+         const uint ib0 = a_offset / QUANT_K + (first_row+n)*num_blocks_per_row;
+-        vec2 d = vec2(data_a[ib0 + i].d);
+-        const FLOAT_TYPE dall = FLOAT_TYPE(d.x);
+-        const FLOAT_TYPE dmin = FLOAT_TYPE(d.y);
++        const FLOAT_TYPE_VEC2 dm = FLOAT_TYPE_VEC2(data_a[ib0 + i].dm);
+ 
+         const uint32_t scale0_u32 = data_a_packed16[ib0 + i].scales[v_im    ];
+         const uint32_t scale4_u32 = data_a_packed16[ib0 + i].scales[v_im + 2];
+@@ -113,7 +111,7 @@ void calc_superblock(const uint a_offset, const uint b_offset, const uint v_im,
+               fma(FLOAT_TYPE(by132.x) + FLOAT_TYPE(by132.y) + FLOAT_TYPE(by148.x) + FLOAT_TYPE(by148.y), sc3,
+               fma(FLOAT_TYPE(by20.x) + FLOAT_TYPE(by20.y) + FLOAT_TYPE(by216.x) + FLOAT_TYPE(by216.y), sc6,
+                   (FLOAT_TYPE(by232.x) + FLOAT_TYPE(by232.y) + FLOAT_TYPE(by248.x) + FLOAT_TYPE(by248.y)) * sc7)));
+-            temp[j][n] = fma(dall, fma(sx, sc0, fma(sy, sc1, fma(sz, sc4, sw * sc5))), fma(-dmin, smin, temp[j][n]));
++            temp[j][n] = fma(dm.x, fma(sx, sc0, fma(sy, sc1, fma(sz, sc4, sw * sc5))), fma(-dm.y, smin, temp[j][n]));
+         }
+     }
+ }
+diff --git a/ggml/src/ggml-vulkan/vulkan-shaders/mul_mm.comp b/ggml/src/ggml-vulkan/vulkan-shaders/mul_mm.comp
+index a20788c4b..d260969f0 100644
+--- a/ggml/src/ggml-vulkan/vulkan-shaders/mul_mm.comp
++++ b/ggml/src/ggml-vulkan/vulkan-shaders/mul_mm.comp
+@@ -120,81 +120,11 @@ shared FLOAT_TYPE_VEC2 buf_b[BN * SHMEM_STRIDE];
+ 
+ #define NUM_WARPS (BLOCK_SIZE / WARP)
+ 
+-#ifdef MUL_MAT_ID
+-shared u16vec2 row_ids[BN];
+-uint _ne1;
+-
+-#ifdef MUL_MAT_ID_USE_SUBGROUPS
+-shared uvec4 ballots_sh[NUM_WARPS];
+-
+-void load_row_ids(uint expert_idx, bool nei0_is_pow2, uint ic) {
+-    _ne1 = 0;
+-    uint num_elements = p.nei1 * p.nei0;
+-    uint nei0shift = findLSB(p.nei0);
+-
+-    uint ids[16];
+-    uint iter = 0;
+-
+-    for (uint j = 0; j < num_elements; j += BLOCK_SIZE) {
+-        // prefetch up to 16 elements
+-        if (iter == 0) {
+-            [[unroll]] for (uint k = 0; k < 16; ++k) {
+-                uint i = j + gl_LocalInvocationIndex + k*BLOCK_SIZE;
+-                bool in_range = i < num_elements;
+-                uint ii1;
+-                if (nei0_is_pow2) {
+-                    ii1 = i >> nei0shift;
+-                } else {
+-                    ii1 = i / p.nei0;
+-                }
+-                uint ii0 = i - ii1 * p.nei0;
+-                ids[k] = in_range ? data_ids[ii1*p.nbi1 + ii0] : 0;
+-            }
+-        }
+-        uint i = j + gl_LocalInvocationIndex;
+-        bool in_range = i < num_elements;
+-        uint ii1;
+-        if (nei0_is_pow2) {
+-            ii1 = i >> nei0shift;
+-        } else {
+-            ii1 = i / p.nei0;
+-        }
+-        uint ii0 = i - ii1 * p.nei0;
+-        uint id = ids[iter++];
+-        uvec4 ballot = subgroupBallot(in_range && id == expert_idx);
+-
+-        ballots_sh[gl_SubgroupID] = ballot;
+-        barrier();
+-
+-        uint subgroup_base = 0;
+-        uint total = 0;
+-        for (uint k = 0; k < gl_NumSubgroups; ++k) {
+-            if (k == gl_SubgroupID) {
+-                subgroup_base = total;
+-            }
+-            total += subgroupBallotBitCount(ballots_sh[k]);
+-        }
+-        barrier();
+-
+-        uint idx = subgroup_base + subgroupBallotExclusiveBitCount(ballot);
+-        if (in_range && id == expert_idx && _ne1 + idx >= ic * BN && _ne1 + idx < (ic + 1) * BN) {
+-            row_ids[_ne1 + idx - ic * BN] = u16vec2(ii0, ii1);
+-        }
+-        _ne1 += total;
+-        iter &= 15;
+-        if (_ne1 >= (ic + 1) * BN) {
+-            break;
+-        }
+-    }
+-    barrier();
+-}
+-#endif // MUL_MAT_ID_USE_SUBGROUPS
+-#endif // MUL_MAT_ID
+-
+ #ifdef COOPMAT
+ shared ACC_TYPE coopmat_stage[TM * TN * NUM_WARPS];
+ #endif
+ 
++#include "mul_mm_id_funcs.glsl"
+ #include "mul_mm_funcs.glsl"
+ 
+ void main() {
+diff --git a/ggml/src/ggml-vulkan/vulkan-shaders/mul_mm_funcs.glsl b/ggml/src/ggml-vulkan/vulkan-shaders/mul_mm_funcs.glsl
+index 0ebfbd646..ee5ded2e8 100644
+--- a/ggml/src/ggml-vulkan/vulkan-shaders/mul_mm_funcs.glsl
++++ b/ggml/src/ggml-vulkan/vulkan-shaders/mul_mm_funcs.glsl
+@@ -134,15 +134,15 @@ void load_a_to_shmem(const uint pos_a, const uint row, const uint col, const uin
+             const uint ib = idx / 128;                         // 2 values per idx
+             const uint iqs = idx % 128;                        // 0..127
+ 
+-            const uint qsi = (iqs / 64) * 32 + (iqs % 16) * 2; // 0,2,4..30
++            const uint qsi = (iqs / 64) * 16 + (iqs % 16);     // 0..15
+             const uint scalesi = iqs / 8;                      // 0..15
+             const uint qsshift = ((iqs % 64) / 16) * 2;        // 0,2,4,6
+ 
+-            const uvec2 qs = uvec2(data_a[ib].qs[qsi], data_a[ib].qs[qsi + 1]);
++            const uvec2 qs = uvec2(unpack8(data_a_packed16[ib].qs[qsi]));
+             const uint scales = data_a[ib].scales[scalesi];
+-            const vec2 d = vec2(data_a[ib].d);
++            const vec2 dm = vec2(data_a[ib].dm);
+ 
+-            const vec2 v = d.x * float(scales & 0xF) * vec2((qs >> qsshift) & 3) - d.y * float(scales >> 4);
++            const vec2 v = dm.x * float(scales & 0xF) * vec2((qs >> qsshift) & 3) - dm.y * float(scales >> 4);
+ 
+             buf_a[buf_idx] = FLOAT_TYPE_VEC2(v.xy);
+ #elif defined(DATA_A_Q3_K)
+@@ -179,7 +179,7 @@ void load_a_to_shmem(const uint pos_a, const uint row, const uint col, const uin
+             const uint is = 2 * n + b;                 // 0..7
+             const uint qsi = n * 32 + (iqs % 16) * 2;  // 0,2,4..126
+ 
+-            const vec2 loadd = vec2(data_a[ib].d);
++            const vec2 loadd = vec2(data_a[ib].dm);
+ 
+             const uint scidx0 = (is < 4) ? is : (is + 4);
+             const uint scidx1 = (is < 4) ? is : (is - 4);
+@@ -215,7 +215,7 @@ void load_a_to_shmem(const uint pos_a, const uint row, const uint col, const uin
+ 
+             const uint8_t hm = uint8_t(1 << (iqs / 16));
+ 
+-            const vec2 loadd = vec2(data_a[ib].d);
++            const vec2 loadd = vec2(data_a[ib].dm);
+ 
+             const uint scidx0 = (is < 4) ? is : (is + 4);
+             const uint scidx1 = (is < 4) ? is : (is - 4);
+@@ -468,7 +468,7 @@ void load_a_to_shmem(const uint pos_a, const uint row, const uint col, const uin
+             const uint ib = idx / 8;
+             const uint iqs = (idx & 0x07) * 2;
+ 
+-            const float d = e8m0_to_fp32(data_a[ib].e);
++            const float d = e8m0_to_fp32(data_a[ib].e) * 0.5;
+             const uint vui = uint(data_a[ib].qs[iqs]);
+             const uint vui2 = uint(data_a[ib].qs[iqs+1]);
+ 
+diff --git a/ggml/src/ggml-vulkan/vulkan-shaders/mul_mm_id_funcs.glsl b/ggml/src/ggml-vulkan/vulkan-shaders/mul_mm_id_funcs.glsl
+new file mode 100644
+index 000000000..1d0e84ac9
+--- /dev/null
++++ b/ggml/src/ggml-vulkan/vulkan-shaders/mul_mm_id_funcs.glsl
+@@ -0,0 +1,70 @@
++#ifdef MUL_MAT_ID
++shared u16vec2 row_ids[BN];
++uint _ne1;
++
++#ifdef MUL_MAT_ID_USE_SUBGROUPS
++shared uvec4 ballots_sh[NUM_WARPS];
++
++void load_row_ids(uint expert_idx, bool nei0_is_pow2, uint ic) {
++    _ne1 = 0;
++    uint num_elements = p.nei1 * p.nei0;
++    uint nei0shift = findLSB(p.nei0);
++
++    uint ids[16];
++    uint iter = 0;
++
++    for (uint j = 0; j < num_elements; j += BLOCK_SIZE) {
++        // prefetch up to 16 elements
++        if (iter == 0) {
++            [[unroll]] for (uint k = 0; k < 16; ++k) {
++                uint i = j + gl_LocalInvocationIndex + k*BLOCK_SIZE;
++                bool in_range = i < num_elements;
++                uint ii1;
++                if (nei0_is_pow2) {
++                    ii1 = i >> nei0shift;
++                } else {
++                    ii1 = i / p.nei0;
++                }
++                uint ii0 = i - ii1 * p.nei0;
++                ids[k] = in_range ? data_ids[ii1*p.nbi1 + ii0] : 0;
++            }
++        }
++        uint i = j + gl_LocalInvocationIndex;
++        bool in_range = i < num_elements;
++        uint ii1;
++        if (nei0_is_pow2) {
++            ii1 = i >> nei0shift;
++        } else {
++            ii1 = i / p.nei0;
++        }
++        uint ii0 = i - ii1 * p.nei0;
++        uint id = ids[iter++];
++        uvec4 ballot = subgroupBallot(in_range && id == expert_idx);
++
++        ballots_sh[gl_SubgroupID] = ballot;
++        barrier();
++
++        uint subgroup_base = 0;
++        uint total = 0;
++        for (uint k = 0; k < gl_NumSubgroups; ++k) {
++            if (k == gl_SubgroupID) {
++                subgroup_base = total;
++            }
++            total += subgroupBallotBitCount(ballots_sh[k]);
++        }
++        barrier();
++
++        uint idx = subgroup_base + subgroupBallotExclusiveBitCount(ballot);
++        if (in_range && id == expert_idx && _ne1 + idx >= ic * BN && _ne1 + idx < (ic + 1) * BN) {
++            row_ids[_ne1 + idx - ic * BN] = u16vec2(ii0, ii1);
++        }
++        _ne1 += total;
++        iter &= 15;
++        if (_ne1 >= (ic + 1) * BN) {
++            break;
++        }
++    }
++    barrier();
++}
++#endif // MUL_MAT_ID_USE_SUBGROUPS
++#endif // MUL_MAT_ID
+diff --git a/ggml/src/ggml-vulkan/vulkan-shaders/mul_mmq.comp b/ggml/src/ggml-vulkan/vulkan-shaders/mul_mmq.comp
+index b5d761c0b..8b238ac4b 100644
+--- a/ggml/src/ggml-vulkan/vulkan-shaders/mul_mmq.comp
++++ b/ggml/src/ggml-vulkan/vulkan-shaders/mul_mmq.comp
+@@ -10,10 +10,9 @@
+ #extension GL_EXT_shader_explicit_arithmetic_types_float16 : require
+ #endif
+ 
+-#ifdef COOPMAT
+-#extension GL_KHR_cooperative_matrix : enable
+-#extension GL_KHR_memory_scope_semantics : enable
++#if defined(MUL_MAT_ID_USE_SUBGROUPS)
+ #extension GL_KHR_shader_subgroup_basic : enable
++#extension GL_KHR_shader_subgroup_ballot : enable
+ #endif
+ 
+ #ifdef MUL_MAT_ID
+@@ -24,7 +23,10 @@
+ 
+ layout(local_size_x_id = 0, local_size_y = 1, local_size_z = 1) in;
+ 
+-layout (binding = 0) readonly buffer A {A_TYPE_PACKED16 data_a[];};
++layout (binding = 0) readonly buffer A {A_TYPE data_a[];};
++#if defined(A_TYPE_PACKED16)
++layout (binding = 0) readonly buffer A_PACKED16 {A_TYPE_PACKED16 data_a_packed16[];};
++#endif
+ #if defined(A_TYPE_PACKED32)
+ layout (binding = 0) readonly buffer A_PACKED32 {A_TYPE_PACKED32 data_a_packed32[];};
+ #endif
+@@ -76,40 +78,27 @@ layout (constant_id = 10) const uint WARP = 32;
+ 
+ #define BK 32
+ 
+-#ifdef COOPMAT
+-#define SHMEM_STRIDE (BK / 4 + 4)
+-#else
+-#define SHMEM_STRIDE (BK / 4 + 1)
+-#endif
++#define MMQ_SHMEM
+ 
+-shared int32_t buf_a_qs[BM * SHMEM_STRIDE];
++#include "mul_mmq_shmem_types.glsl"
+ 
+-#ifndef COOPMAT
+-#if QUANT_AUXF == 1
+-shared FLOAT_TYPE buf_a_dm[BM];
+-#else
+-shared FLOAT_TYPE_VEC2 buf_a_dm[BM];
+-#endif
++#ifndef BK_STEP
++#define BK_STEP 4
+ #endif
+ 
+-shared int32_t buf_b_qs[BN * SHMEM_STRIDE];
+-#ifndef COOPMAT
+-shared FLOAT_TYPE_VEC2 buf_b_ds[BN];
+-#endif
++// Shared memory cache
++shared block_a_cache buf_a[BM * BK_STEP];
++shared block_b_cache buf_b[BN * BK_STEP];
++// Register cache
++block_a_cache cache_a[WMITER * TM];
++block_b_cache cache_b;
+ 
+-#define LOAD_VEC_A (4 * QUANT_R)
++#define LOAD_VEC_A (4 * QUANT_R_MMQ)
+ #define LOAD_VEC_B 16
+ 
+-#ifdef MUL_MAT_ID
+-shared u16vec2 row_ids[4096];
+-#endif // MUL_MAT_ID
+-
+ #define NUM_WARPS (BLOCK_SIZE / WARP)
+ 
+-#ifdef COOPMAT
+-shared ACC_TYPE coopmat_stage[TM * TN * NUM_WARPS];
+-#endif
+-
++#include "mul_mm_id_funcs.glsl"
+ #include "mul_mmq_funcs.glsl"
+ 
+ void main() {
+@@ -139,26 +128,12 @@ void main() {
+     const uint WNITER = (WM * WN) / (WARP * TM * TN * WMITER);
+     const uint WSUBM = WM / WMITER;
+     const uint WSUBN = WN / WNITER;
+-
+-#ifdef COOPMAT
+-    const uint warp_i = gl_SubgroupID;
+-
+-    const uint tiw = gl_SubgroupInvocationID;
+-
+-    const uint cms_per_row = WM / TM;
+-    const uint cms_per_col = WN / TN;
+-
+-    const uint storestride = WARP / TM;
+-    const uint store_r = tiw % TM;
+-    const uint store_c = tiw / TM;
+-#else
+     const uint warp_i = gl_LocalInvocationID.x / WARP;
+ 
+     const uint tiw = gl_LocalInvocationID.x % WARP;
+ 
+     const uint tiwr = tiw % (WSUBM / TM);
+     const uint tiwc = tiw / (WSUBM / TM);
+-#endif
+ 
+     const uint warp_r = warp_i % (BM / WM);
+     const uint warp_c = warp_i / (BM / WM);
+@@ -172,17 +147,27 @@ void main() {
+     const uint loadstride_b = BLOCK_SIZE * LOAD_VEC_B / BK;
+ 
+ #ifdef MUL_MAT_ID
+-    uint _ne1 = 0;
+-    for (uint ii1 = 0; ii1 < p.nei1; ii1++) {
+-        for (uint ii0 = 0; ii0 < p.nei0; ii0++) {
++#ifdef MUL_MAT_ID_USE_SUBGROUPS
++    if (bitCount(p.nei0) == 1) {
++        load_row_ids(expert_idx, true, ic);
++    } else {
++        load_row_ids(expert_idx, false, ic);
++    }
++#else
++    _ne1 = 0;
++    for (uint ii1 = 0; ii1 < p.nei1 && _ne1 < (ic + 1) * BN; ii1++) {
++        for (uint ii0 = 0; ii0 < p.nei0 && _ne1 < (ic + 1) * BN; ii0++) {
+             if (data_ids[ii1*p.nbi1 + ii0] == expert_idx) {
+-                row_ids[_ne1] = u16vec2(ii0, ii1);
++                if (_ne1 >= ic * BN) {
++                    row_ids[_ne1 - ic * BN] = u16vec2(ii0, ii1);
++                }
+                 _ne1++;
+             }
+         }
+     }
+ 
+     barrier();
++#endif
+ 
+     // Workgroup has no work
+     if (ic * BN >= _ne1) return;
+@@ -209,159 +194,70 @@ void main() {
+     uint pos_b_ib = (batch_idx * p.batch_stride_b + ic * BN * p.stride_b + start_k) / BK;
+ #endif
+ 
+-#ifdef COOPMAT
+-    coopmat<int8_t, gl_ScopeSubgroup, TM, TK, gl_MatrixUseA> cache_a;
+-    coopmat<int8_t, gl_ScopeSubgroup, TK, TN, gl_MatrixUseB> cache_b;
+-    coopmat<int32_t, gl_ScopeSubgroup, TM, TN, gl_MatrixUseAccumulator> cm_result;
+-
+-    coopmat<ACC_TYPE, gl_ScopeSubgroup, TM, TN, gl_MatrixUseAccumulator> factors[cms_per_row * cms_per_col];
+-
+-    coopmat<ACC_TYPE, gl_ScopeSubgroup, TM, TN, gl_MatrixUseAccumulator> sums[cms_per_row * cms_per_col];
+-
+-    [[unroll]] for (uint i = 0; i < cms_per_row * cms_per_col; i++) {
+-        sums[i] = coopmat<ACC_TYPE, gl_ScopeSubgroup, TM, TN, gl_MatrixUseAccumulator>(0.0f);
+-    }
+-#else
+-    int32_t cache_a_qs[WMITER * TM * BK / 4];
+-
+-    int32_t cache_b_qs[TN * BK / 4];
+-
+     ACC_TYPE sums[WMITER * TM * WNITER * TN];
+ 
+     [[unroll]] for (uint i = 0; i < WMITER*TM*WNITER*TN; i++) {
+         sums[i] = ACC_TYPE(0.0f);
+     }
+-#endif
+ 
+-#if QUANT_AUXF == 1
+-    FLOAT_TYPE cache_a_dm[WMITER * TM];
+-#else
+-    FLOAT_TYPE_VEC2 cache_a_dm[WMITER * TM];
+-#endif
+-
+-    FLOAT_TYPE_VEC2 cache_b_ds[TN];
+-
+-    for (uint block = start_k; block < end_k; block += BK) {
++    for (uint block = start_k; block < end_k; block += BK * BK_STEP) {
+         [[unroll]] for (uint l = 0; loadc_a + l < BM; l += loadstride_a) {
+-            const uint ib = pos_a_ib + (loadc_a + l) * p.stride_a / BK;
+-            const uint iqs = loadr_a;
+             const uint buf_ib = loadc_a + l;
++            const uint ib = pos_a_ib + buf_ib * p.stride_a / BK;
++            const uint iqs = loadr_a;
+ 
+-            if (iqs == 0) {
+-#if QUANT_AUXF == 1
+-                buf_a_dm[buf_ib] = get_d(ib);
+-#else
+-                buf_a_dm[buf_ib] = get_dm(ib);
+-#endif
++            [[unroll]] for (uint k_step = 0; k_step < BK_STEP; k_step++) {
++                block_a_to_shmem(k_step * BM + buf_ib, ib + k_step, iqs);
+             }
+-#if QUANT_R == 1
+-            buf_a_qs[buf_ib * SHMEM_STRIDE + iqs] = repack(ib, iqs);
+-#else
+-            const i32vec2 vals = repack(ib, iqs);
+-            buf_a_qs[buf_ib * SHMEM_STRIDE + iqs    ] = vals.x;
+-            buf_a_qs[buf_ib * SHMEM_STRIDE + iqs + 4] = vals.y;
+-#endif
+         }
+         [[unroll]] for (uint l = 0; loadc_b + l < BN; l += loadstride_b) {
++            const uint buf_ib = loadc_b + l;
++
+ #ifdef MUL_MAT_ID
+-            const u16vec2 row_idx = row_ids[ic * BN + loadc_b + l];
+-            const uint idx = pos_b_ib + row_idx.y * p.batch_stride_b / LOAD_VEC_B + (row_idx.x % p.ne11) * p.stride_b / LOAD_VEC_B + loadr_b;
+-            const uint ib = idx / 8;
+-            const uint iqs = idx & 0x7;
++            const u16vec2 row_idx = row_ids[buf_ib];
++            const uint ib = pos_b_ib + row_idx.y * p.batch_stride_b / BK + (row_idx.x % p.ne11) * p.stride_b / BK;
+ #else
+-            const uint ib = pos_b_ib + (loadc_b + l) * p.stride_b / BK;
+-            const uint ib_outer = ib / 4;
+-            const uint ib_inner = ib % 4;
+-
+-            const uint iqs = loadr_b;
++            const uint ib = pos_b_ib + buf_ib * p.stride_b / BK;
+ #endif
++            const uint iqs = loadr_b;
+ 
+-            const uint buf_ib = loadc_b + l;
+-
+-            if (iqs == 0) {
+-                buf_b_ds[buf_ib] = FLOAT_TYPE_VEC2(data_b[ib_outer].ds[ib_inner]);
++            [[unroll]] for (uint k_step = 0; k_step < BK_STEP; k_step++) {
++                block_b_to_shmem(k_step * BN + buf_ib, ib + k_step, iqs);
+             }
+-            const ivec4 values = data_b[ib_outer].qs[ib_inner * 2 + iqs];
+-            buf_b_qs[buf_ib * SHMEM_STRIDE + iqs * 4    ] = values.x;
+-            buf_b_qs[buf_ib * SHMEM_STRIDE + iqs * 4 + 1] = values.y;
+-            buf_b_qs[buf_ib * SHMEM_STRIDE + iqs * 4 + 2] = values.z;
+-            buf_b_qs[buf_ib * SHMEM_STRIDE + iqs * 4 + 3] = values.w;
+         }
+ 
+         barrier();
+ 
+-        pos_a_ib += 1;
+-        pos_b_ib += 1;
++        pos_a_ib += BK_STEP;
++        pos_b_ib += BK_STEP;
+ 
+-#ifdef COOPMAT
+-        [[unroll]] for (uint cm_row = 0; cm_row < cms_per_row; cm_row++) {
+-            const uint ib_a = warp_r * WM + cm_row * TM;
++        for (uint k_step = 0; k_step < BK_STEP; k_step++) {
+             // Load from shared into cache
+-            coopMatLoad(cache_a, buf_a_qs, ib_a * SHMEM_STRIDE, SHMEM_STRIDE, gl_CooperativeMatrixLayoutRowMajor);
+-
+-            // TODO: only cache values that are actually needed
+-            [[unroll]] for (uint t_idx = 0; t_idx < TM; t_idx++) {
+-                cache_a_dm[t_idx] = buf_a_dm[ib_a + t_idx];
+-            }
+-
+-            [[unroll]] for (uint cm_col = 0; cm_col < cms_per_col; cm_col++) {
+-                const uint ib_b = warp_c * WN + cm_col * TN;
+-                coopMatLoad(cache_b, buf_b_qs, ib_b * SHMEM_STRIDE, SHMEM_STRIDE, gl_CooperativeMatrixLayoutColumnMajor);
+-
+-                // TODO: only cache values that are actually needed
+-                [[unroll]] for (uint t_idx = 0; t_idx < TN; t_idx++) {
+-                    cache_b_dm[t_idx] = buf_b_d[ib_b + t_idx];
+-                }
+-
+-                cm_result = coopmat<int32_t, gl_ScopeSubgroup, TM, TN, gl_MatrixUseAccumulator>(0);
+-                cm_result = coopMatMulAdd(cache_a, cache_b, cm_result);
+-
+-                [[unroll]] for (uint col = 0; col < TN; col += storestride) {
+-                    coopmat_stage[warp_i * TM * TN + (store_c + col) * TM + store_r] = ACC_TYPE(float(cache_a_d[store_r]) * float(cache_b_d[store_c + col]));
+-                }
+-
+-                coopMatLoad(factors, coopmat_stage, warp_i * TM * TN, TM, gl_CooperativeMatrixLayoutColumnMajor);
+-                sums[cm_col * cms_per_row + cm_row] += factors * coopmat<ACC_TYPE, gl_ScopeSubgroup, TM, TN, gl_MatrixUseAccumulator>(cm_result);
+-            }
+-        }
+-#else
+-        // Load from shared into cache
+-        [[unroll]] for (uint wsir = 0; wsir < WMITER; wsir++) {
+-            [[unroll]] for (uint cr = 0; cr < TM; cr++) {
+-                const uint ib = warp_r * WM + wsir * WSUBM + tiwr * TM + cr;
+-                cache_a_dm[wsir * TM + cr] = buf_a_dm[ib];
+-                [[unroll]] for (uint idx_k = 0; idx_k < BK / 4; idx_k++) {
+-                    cache_a_qs[(wsir * TM + cr) * (BK / 4) + idx_k] = buf_a_qs[ib * SHMEM_STRIDE + idx_k];
+-                }
+-            }
+-        }
++            [[unroll]] for (uint wsir = 0; wsir < WMITER; wsir++) {
++                [[unroll]] for (uint cr = 0; cr < TM; cr++) {
++                    const uint reg_ib = wsir * TM + cr;
++                    const uint buf_ib = warp_r * WM + wsir * WSUBM + tiwr * TM + cr;
+ 
+-        [[unroll]] for (uint wsic = 0; wsic < WNITER; wsic++) {
+-            [[unroll]] for (uint cc = 0; cc < TN; cc++) {
+-                const uint ib = warp_c * WN + wsic * WSUBN + tiwc * TN + cc;
+-                cache_b_ds[cc] = buf_b_ds[ib];
+-                [[unroll]] for (uint idx_k = 0; idx_k < BK / 4; idx_k++) {
+-                    cache_b_qs[cc * (BK / 4) + idx_k] = buf_b_qs[ib * SHMEM_STRIDE + idx_k];
++                    block_a_to_registers(reg_ib, k_step * BM + buf_ib);
+                 }
+             }
+ 
+-            [[unroll]] for (uint wsir = 0; wsir < WMITER; wsir++) {
++            [[unroll]] for (uint wsic = 0; wsic < WNITER; wsic++) {
+                 [[unroll]] for (uint cc = 0; cc < TN; cc++) {
+-                    [[unroll]] for (uint cr = 0; cr < TM; cr++) {
+-                        const uint cache_a_idx = wsir * TM + cr;
+-                        const uint sums_idx = (wsic * TN + cc) * (WMITER * TM) + wsir * TM + cr;
+-                        int32_t q_sum = 0;
+-                        [[unroll]] for (uint idx_k = 0; idx_k < BK / 4; idx_k++) {
+-                            q_sum += dotPacked4x8EXT(cache_a_qs[cache_a_idx * (BK / 4) + idx_k],
+-                                                     cache_b_qs[cc * (BK / 4) + idx_k]);
+-                        }
++                    const uint ib = k_step * BN + warp_c * WN + wsic * WSUBN + tiwc * TN + cc;
++                    block_b_to_registers(ib);
+ 
+-                        sums[sums_idx] += mul_q8_1(q_sum, cache_a_dm[cache_a_idx], cache_b_ds[cc], 1);
++                    [[unroll]] for (uint wsir = 0; wsir < WMITER; wsir++) {
++                        [[unroll]] for (uint cr = 0; cr < TM; cr++) {
++                            const uint cache_a_idx = wsir * TM + cr;
++                            const uint sums_idx = (wsic * TN + cc) * (WMITER * TM) + wsir * TM + cr;
++
++                            sums[sums_idx] += mmq_dot_product(cache_a_idx);
++                        }
+                     }
+                 }
+             }
+         }
+-#endif
+ 
+         barrier();
+     }
+@@ -373,54 +269,6 @@ void main() {
+     const uint offsets = batch_idx * p.batch_stride_d + ik * p.batch_stride_d * gl_NumWorkGroups.z;
+ #endif
+ 
+-#ifdef COOPMAT
+-#ifdef MUL_MAT_ID
+-    [[unroll]] for (uint cm_row = 0; cm_row < cms_per_row; cm_row++) {
+-        [[unroll]] for (uint cm_col = 0; cm_col < cms_per_col; cm_col++) {
+-            coopMatStore(sums[cm_col * cms_per_row + cm_row], coopmat_stage, warp_i * TM * TN, TM, gl_CooperativeMatrixLayoutColumnMajor);
+-
+-            [[unroll]] for (uint col = 0; col < BN; col += storestride) {
+-                const uint row_i = dc + cm_col * TN + col + store_c;
+-                if (row_i >= _ne1) break;
+-
+-                const u16vec2 row_idx = row_ids[row_i];
+-
+-                data_d[row_idx.y * p.batch_stride_d + row_idx.x * p.stride_d + dr + cm_row * TM + store_r] = D_TYPE(coopmat_stage[warp_i * TM * TN + (col + store_c) * TM + store_r]);
+-            }
+-        }
+-    }
+-#else
+-    const bool is_aligned = p.stride_d % 4 == 0;  // Assumption: D_TYPE == float
+-
+-    [[unroll]] for (uint cm_row = 0; cm_row < cms_per_row; cm_row++) {
+-        [[unroll]] for (uint cm_col = 0; cm_col < cms_per_col; cm_col++) {
+-            const bool is_in_bounds = dr + (cm_row + 1) * TM <= p.M && dc + (cm_col + 1) * TN <= p.N;
+-
+-            if (is_aligned && is_in_bounds) {
+-                // Full coopMat is within bounds and stride_d is aligned with 16B
+-                coopmat<D_TYPE, gl_ScopeSubgroup, TM, TN, gl_MatrixUseAccumulator> cm_dtype = coopmat<D_TYPE, gl_ScopeSubgroup, TM, TN, gl_MatrixUseAccumulator>(sums[cm_col * cms_per_row + cm_row]);
+-                coopMatStore(cm_dtype, data_d, offsets + (dc + cm_col * TN) * p.stride_d + dr + cm_row * TM, p.stride_d, gl_CooperativeMatrixLayoutColumnMajor);
+-            } else if (is_in_bounds) {
+-                // Full coopMat is within bounds, but stride_d is not aligned
+-                coopMatStore(sums[cm_col * cms_per_row + cm_row], coopmat_stage, warp_i * TM * TN, TM, gl_CooperativeMatrixLayoutColumnMajor);
+-
+-                [[unroll]] for (uint col = 0; col < TN; col += storestride) {
+-                    data_d[offsets + (dc + cm_col * TN + col + store_c) * p.stride_d + dr + cm_row * TM + store_r] = D_TYPE(coopmat_stage[warp_i * TM * TN + (col + store_c) * TM + store_r]);
+-                }
+-            } else if (dr + cm_row * TM < p.M && dc + cm_col * TN < p.N) {
+-                // Partial coopMat is within bounds
+-                coopMatStore(sums[cm_col * cms_per_row + cm_row], coopmat_stage, warp_i * TM * TN, TM, gl_CooperativeMatrixLayoutColumnMajor);
+-
+-                [[unroll]] for (uint col = 0; col < TN; col += storestride) {
+-                    if (dr + cm_row * TM + store_r < p.M && dc + cm_col * TN + col + store_c < p.N) {
+-                        data_d[offsets + (dc + cm_col * TN + col + store_c) * p.stride_d + dr + cm_row * TM + store_r] = D_TYPE(coopmat_stage[warp_i * TM * TN + (col + store_c) * TM + store_r]);
+-                    }
+-                }
+-            }
+-        }
+-    }
+-#endif // MUL_MAT_ID
+-#else
+     [[unroll]] for (uint wsic = 0; wsic < WNITER; wsic++) {
+         [[unroll]] for (uint wsir = 0; wsir < WMITER; wsir++) {
+ 
+@@ -431,19 +279,21 @@ void main() {
+                 const uint row_i = dc_warp + cc;
+                 if (row_i >= _ne1) break;
+ 
+-                const u16vec2 row_idx = row_ids[row_i];
++                const u16vec2 row_idx = row_ids[row_i - ic * BN];
+ #endif // MUL_MAT_ID
+                 [[unroll]] for (uint cr = 0; cr < TM; cr++) {
++                    const uint sums_idx = (wsic * TN + cc) * WMITER * TM + wsir * TM + cr;
+ #ifdef MUL_MAT_ID
+-                    data_d[row_idx.y * p.batch_stride_d + row_idx.x * p.stride_d + dr_warp + cr] = D_TYPE(sums[(wsic * TN + cc) * (WMITER * TM) + wsir * TM + cr]);
++                    if (dr_warp + cr < p.M) {
++                        data_d[row_idx.y * p.batch_stride_d + row_idx.x * p.stride_d + dr_warp + cr] = D_TYPE(sums[sums_idx].x);
++                    }
+ #else
+                     if (dr_warp + cr < p.M && dc_warp + cc < p.N) {
+-                        data_d[offsets + (dc_warp + cc) * p.stride_d + dr_warp + cr] = D_TYPE(sums[(wsic * TN + cc) * (WMITER * TM) + wsir * TM + cr]);
++                        data_d[offsets + (dc_warp + cc) * p.stride_d + dr_warp + cr] = D_TYPE(sums[sums_idx].x);
+                     }
+ #endif // MUL_MAT_ID
+                 }
+             }
+         }
+     }
+-#endif // COOPMAT
+ }
+diff --git a/ggml/src/ggml-vulkan/vulkan-shaders/mul_mmq_funcs.glsl b/ggml/src/ggml-vulkan/vulkan-shaders/mul_mmq_funcs.glsl
+index fe71eb131..c0c03fedc 100644
+--- a/ggml/src/ggml-vulkan/vulkan-shaders/mul_mmq_funcs.glsl
++++ b/ggml/src/ggml-vulkan/vulkan-shaders/mul_mmq_funcs.glsl
+@@ -6,41 +6,89 @@
+ 
+ // Each iqs value maps to a 32-bit integer
+ 
+-#if defined(DATA_A_Q4_0)
++#if defined(DATA_A_Q4_0) || defined(DATA_A_Q4_1)
++// 2-byte loads for Q4_0 blocks (18 bytes)
++// 4-byte loads for Q4_1 blocks (20 bytes)
+ i32vec2 repack(uint ib, uint iqs) {
+-    // Use 2-byte loads since a q4_0 block (18 bytes) is not divisible by 4
+-    const u16vec2 quants = u16vec2(data_a[ib].qs[iqs * 2    ],
+-                                   data_a[ib].qs[iqs * 2 + 1]);
++#ifdef DATA_A_Q4_0
++    const u16vec2 quants = u16vec2(data_a_packed16[ib].qs[iqs * 2    ],
++                                   data_a_packed16[ib].qs[iqs * 2 + 1]);
+     const uint32_t vui = pack32(quants);
+     return i32vec2( vui       & 0x0F0F0F0F,
+                    (vui >> 4) & 0x0F0F0F0F);
++#else // DATA_A_Q4_1
++    const uint32_t vui = data_a_packed32[ib].qs[iqs];
++    return i32vec2( vui       & 0x0F0F0F0F,
++                   (vui >> 4) & 0x0F0F0F0F);
++#endif
+ }
+ 
++#ifdef DATA_A_Q4_0
+ ACC_TYPE mul_q8_1(const int32_t q_sum, const float da, const vec2 dsb, const int32_t sum_divisor) {
+     return ACC_TYPE(da * (float(q_sum) * dsb.x - (8 / sum_divisor) * dsb.y));
+ }
++#else // DATA_A_Q4_1
++ACC_TYPE mul_q8_1(const int32_t q_sum, const vec2 dma, const vec2 dsb, const int32_t sum_divisor) {
++    return ACC_TYPE(float(q_sum) * dma.x * dsb.x + dma.y * dsb.y / sum_divisor);
++}
+ #endif
+ 
+-#if defined(DATA_A_Q4_1)
+-i32vec2 repack(uint ib, uint iqs) {
+-    // Use 4-byte loads since a q4_1 block (20 bytes) is divisible by 4
+-    const uint32_t vui = data_a_packed32[ib].qs[iqs];
+-    return i32vec2( vui       & 0x0F0F0F0F,
+-                   (vui >> 4) & 0x0F0F0F0F);
++#ifdef MMQ_SHMEM
++void block_a_to_shmem(const uint buf_ib, const uint ib, const uint iqs) {
++#ifdef DATA_A_Q4_0
++    buf_a[buf_ib].qs[iqs] = pack32(u16vec2(data_a_packed16[ib].qs[iqs * 2],
++                                           data_a_packed16[ib].qs[iqs * 2 + 1]));
++
++    if (iqs == 0) {
++        buf_a[buf_ib].dm = FLOAT_TYPE(data_a_packed16[ib].d);
++    }
++#else // DATA_A_Q4_1
++    buf_a[buf_ib].qs[iqs] = data_a_packed32[ib].qs[iqs];
++
++    if (iqs == 0) {
++        buf_a[buf_ib].dm = FLOAT_TYPE_VEC2(data_a_packed32[ib].dm);
++    }
++#endif
+ }
+ 
+-ACC_TYPE mul_q8_1(const int32_t q_sum, const vec2 dma, const vec2 dsb, const int32_t sum_divisor) {
+-    return ACC_TYPE(float(q_sum) * dma.x * dsb.x + dma.y * dsb.y / sum_divisor);
++void block_a_to_registers(const uint reg_ib, const uint buf_ib) {
++    cache_a[reg_ib].dm = buf_a[buf_ib].dm;
++
++    [[unroll]] for (uint iqs = 0; iqs < 4; iqs++) {
++        cache_a[reg_ib].qs[iqs] = buf_a[buf_ib].qs[iqs];
++    }
+ }
+-#endif
+ 
+-#if defined(DATA_A_Q5_0)
++ACC_TYPE mmq_dot_product(const uint ib_a) {
++    int32_t q_sum = 0;
++    [[unroll]] for (uint iqs = 0; iqs < 4; iqs++) {
++        const uint32_t vui = cache_a[ib_a].qs[iqs];
++        const i32vec2 qs_a = i32vec2( vui       & 0x0F0F0F0F,
++                                     (vui >> 4) & 0x0F0F0F0F);
++
++        const int32_t qs_b0 = cache_b.qs[iqs];
++        const int32_t qs_b1 = cache_b.qs[iqs + 4];
++
++        q_sum += dotPacked4x8EXT(qs_a.x, qs_b0);
++        q_sum += dotPacked4x8EXT(qs_a.y, qs_b1);
++    }
++
++    return mul_q8_1(q_sum, cache_a[ib_a].dm, cache_b.ds, 1);
++}
++#endif // MMQ_SHMEM
++
++#elif defined(DATA_A_Q5_0) || defined(DATA_A_Q5_1)
++// 2-byte loads for Q5_0 blocks (22 bytes)
++// 4-byte loads for Q5_1 blocks (24 bytes)
+ i32vec2 repack(uint ib, uint iqs) {
+-    // Use 2-byte loads since a q5_0 block (22 bytes) is not divisible by 4
+-    const u16vec2 quants = u16vec2(data_a[ib].qs[iqs * 2    ],
+-                                   data_a[ib].qs[iqs * 2 + 1]);
++    const u16vec2 quants = u16vec2(data_a_packed16[ib].qs[iqs * 2    ],
++                                   data_a_packed16[ib].qs[iqs * 2 + 1]);
+     const uint32_t vui = pack32(quants);
+-    const int32_t qh = int32_t((uint32_t(data_a[ib].qh[1]) << 16 | data_a[ib].qh[0]) >> (4 * iqs));
++#ifdef DATA_A_Q5_0
++    const int32_t qh = int32_t((uint32_t(data_a_packed16[ib].qh[1]) << 16 | data_a_packed16[ib].qh[0]) >> (4 * iqs));
++#else // DATA_A_Q5_1
++    const int32_t qh = int32_t(data_a_packed32[ib].qh >> (4 * iqs));
++#endif
+     const int32_t v0 = int32_t(vui & 0x0F0F0F0F)
+                      | ((qh & 0xF) * 0x02040810) & 0x10101010; // (0,1,2,3) -> (4,12,20,28)
+ 
+@@ -50,40 +98,457 @@ i32vec2 repack(uint ib, uint iqs) {
+     return i32vec2(v0, v1);
+ }
+ 
++#ifdef DATA_A_Q5_0
+ ACC_TYPE mul_q8_1(const int32_t q_sum, const float da, const vec2 dsb, const int32_t sum_divisor) {
+     return ACC_TYPE(da * (float(q_sum) * dsb.x - (16 / sum_divisor) * dsb.y));
+ }
++#else // DATA_A_Q5_1
++ACC_TYPE mul_q8_1(const int32_t q_sum, const vec2 dma, const vec2 dsb, const int32_t sum_divisor) {
++    return ACC_TYPE(float(q_sum) * dma.x * dsb.x + dma.y * dsb.y / sum_divisor);
++}
+ #endif
+ 
+-#if defined(DATA_A_Q5_1)
+-i32vec2 repack(uint ib, uint iqs) {
+-    // Use 4-byte loads since a q5_1 block (24 bytes) is divisible by 4
+-    const uint32_t vui = data_a_packed32[ib].qs[iqs];
+-    const int32_t qh = int32_t(data_a_packed32[ib].qh >> (4 * iqs));
+-    const int32_t v0 = int32_t(vui & 0x0F0F0F0F)
+-                     | ((qh & 0xF) * 0x02040810) & 0x10101010; // (0,1,2,3) -> (4,12,20,28)
++#ifdef MMQ_SHMEM
++void block_a_to_shmem(const uint buf_ib, const uint ib, const uint iqs) {
++#ifdef DATA_A_Q5_0
++    buf_a[buf_ib].qs[iqs] = pack32(u16vec2(data_a_packed16[ib].qs[iqs * 2],
++                                           data_a_packed16[ib].qs[iqs * 2 + 1]));
+ 
+-    const int32_t v1 = int32_t((vui >> 4) & 0x0F0F0F0F)
+-                     | (((qh >> 16) & 0xF) * 0x02040810) & 0x10101010; // (16,17,18,19) -> (4,12,20,28)
++    if (iqs == 0) {
++        buf_a[buf_ib].dm = FLOAT_TYPE(data_a_packed16[ib].d);
++        buf_a[buf_ib].qh = pack32(u16vec2(data_a_packed16[ib].qh[0], data_a_packed16[ib].qh[1]));
++    }
++#else // DATA_A_Q5_1
++    buf_a[buf_ib].qs[iqs] = data_a_packed32[ib].qs[iqs];
+ 
+-    return i32vec2(v0, v1);
++    if (iqs == 0) {
++        buf_a[buf_ib].dm = FLOAT_TYPE_VEC2(data_a_packed32[ib].dm);
++        buf_a[buf_ib].qh = data_a_packed32[ib].qh;
++    }
++#endif
+ }
+ 
+-ACC_TYPE mul_q8_1(const int32_t q_sum, const vec2 dma, const vec2 dsb, const int32_t sum_divisor) {
+-    return ACC_TYPE(float(q_sum) * dma.x * dsb.x + dma.y * dsb.y / sum_divisor);
++void block_a_to_registers(const uint reg_ib, const uint buf_ib) {
++    cache_a[reg_ib].dm = buf_a[buf_ib].dm;
++    cache_a[reg_ib].qh = buf_a[buf_ib].qh;
++
++    [[unroll]] for (uint iqs = 0; iqs < 4; iqs++) {
++        cache_a[reg_ib].qs[iqs] = buf_a[buf_ib].qs[iqs];
++    }
+ }
++
++ACC_TYPE mmq_dot_product(const uint ib_a) {
++    int32_t q_sum = 0;
++    [[unroll]] for (uint iqs = 0; iqs < 4; iqs++) {
++        const uint32_t vui = cache_a[ib_a].qs[iqs];
++        const int32_t qh = int32_t(cache_a[ib_a].qh >> (4 * iqs));
++        const int32_t qs_a0 = int32_t(vui & 0x0F0F0F0F)
++                         | ((qh & 0xF) * 0x02040810) & 0x10101010; // (0,1,2,3) -> (4,12,20,28)
++        const int32_t qs_a1 = int32_t((vui >> 4) & 0x0F0F0F0F)
++                         | (((qh >> 16) & 0xF) * 0x02040810) & 0x10101010; // (16,17,18,19) -> (4,12,20,28)
++
++        const int32_t qs_b0 = cache_b.qs[iqs];
++        const int32_t qs_b1 = cache_b.qs[iqs + 4];
++
++        q_sum += dotPacked4x8EXT(qs_a0, qs_b0);
++        q_sum += dotPacked4x8EXT(qs_a1, qs_b1);
++    }
++
++    return mul_q8_1(q_sum, cache_a[ib_a].dm, cache_b.ds, 1);
++}
++#endif // MMQ_SHMEM
+ #endif
+ 
+ #if defined(DATA_A_Q8_0)
++// 2-byte loads for Q8_0 blocks (34 bytes)
+ int32_t repack(uint ib, uint iqs) {
+-    // Use 2-byte loads since a q8_0 block (34 bytes) is not divisible by 4
+-    return pack32(i16vec2(data_a[ib].qs[iqs * 2    ],
+-                          data_a[ib].qs[iqs * 2 + 1]));
++    return pack32(i16vec2(data_a_packed16[ib].qs[iqs * 2    ],
++                          data_a_packed16[ib].qs[iqs * 2 + 1]));
+ }
+ 
+ ACC_TYPE mul_q8_1(const int32_t q_sum, const float da, const vec2 dsb, const int32_t sum_divisor) {
+     return ACC_TYPE(float(q_sum) * da * dsb.x);
+ }
++
++#ifdef MMQ_SHMEM
++void block_a_to_shmem(const uint buf_ib, const uint ib, const uint iqs) {
++    buf_a[buf_ib].qs[iqs] = pack32(i16vec2(data_a_packed16[ib].qs[iqs * 2],
++                                           data_a_packed16[ib].qs[iqs * 2 + 1]));
++
++    if (iqs == 0) {
++        buf_a[buf_ib].dm = FLOAT_TYPE(data_a_packed16[ib].d);
++    }
++}
++
++void block_a_to_registers(const uint reg_ib, const uint buf_ib) {
++    cache_a[reg_ib].dm = buf_a[buf_ib].dm;
++
++    [[unroll]] for (uint iqs = 0; iqs < 8; iqs++) {
++        cache_a[reg_ib].qs[iqs] = buf_a[buf_ib].qs[iqs];
++    }
++}
++
++ACC_TYPE mmq_dot_product(const uint ib_a) {
++    int32_t q_sum = 0;
++    [[unroll]] for (uint iqs = 0; iqs < 8; iqs++) {
++        const int32_t qs_a = cache_a[ib_a].qs[iqs];
++        const int32_t qs_b = cache_b.qs[iqs];
++
++        q_sum += dotPacked4x8EXT(qs_a, qs_b);
++    }
++
++    return mul_q8_1(q_sum, cache_a[ib_a].dm, cache_b.ds, 1);
++}
++#endif // MMQ_SHMEM
++#endif
++
++#if defined(DATA_A_MXFP4)
++// 1-byte loads for mxfp4 blocks (17 bytes)
++i32vec2 repack(uint ib, uint iqs) {
++    const uint32_t quants = pack32(u8vec4(data_a[ib].qs[iqs * 4    ],
++                                          data_a[ib].qs[iqs * 4 + 1],
++                                          data_a[ib].qs[iqs * 4 + 2],
++                                          data_a[ib].qs[iqs * 4 + 3]));
++
++    return i32vec2( quants       & 0x0F0F0F0F,
++                   (quants >> 4) & 0x0F0F0F0F);
++}
++
++ACC_TYPE mul_q8_1(const int32_t q_sum, const float da, const vec2 dsb, const int32_t sum_divisor) {
++    return ACC_TYPE(da * dsb.x * float(q_sum));
++}
++
++#ifdef MMQ_SHMEM
++void block_a_to_shmem(const uint buf_ib, const uint ib, const uint iqs) {
++    const uint32_t qs = pack32(u8vec4(data_a[ib].qs[iqs * 4    ],
++                                      data_a[ib].qs[iqs * 4 + 1],
++                                      data_a[ib].qs[iqs * 4 + 2],
++                                      data_a[ib].qs[iqs * 4 + 3]));
++
++    const u8vec4 i_a0 = unpack8( qs       & 0x0F0F0F0F);
++    const u8vec4 i_a1 = unpack8((qs >> 4) & 0x0F0F0F0F);
++
++    buf_a[buf_ib].qs[iqs    ] = pack32(i8vec4(kvalues_mxfp4[i_a0.x], kvalues_mxfp4[i_a0.y], kvalues_mxfp4[i_a0.z], kvalues_mxfp4[i_a0.w]));
++    buf_a[buf_ib].qs[iqs + 4] = pack32(i8vec4(kvalues_mxfp4[i_a1.x], kvalues_mxfp4[i_a1.y], kvalues_mxfp4[i_a1.z], kvalues_mxfp4[i_a1.w]));
++
++    if (iqs == 0) {
++        buf_a[buf_ib].d = FLOAT_TYPE(e8m0_to_fp32(data_a[ib].e) * 0.5);
++    }
++}
++
++void block_a_to_registers(const uint reg_ib, const uint buf_ib) {
++    cache_a[reg_ib].d = buf_a[buf_ib].d;
++
++    [[unroll]] for (uint iqs = 0; iqs < 8; iqs++) {
++        cache_a[reg_ib].qs[iqs] = buf_a[buf_ib].qs[iqs];
++    }
++}
++
++ACC_TYPE mmq_dot_product(const uint ib_a) {
++    int32_t q_sum = 0;
++    [[unroll]] for (uint iqs = 0; iqs < 8; iqs++) {
++        const int32_t qs_a = cache_a[ib_a].qs[iqs];
++
++        q_sum += dotPacked4x8EXT(qs_a, cache_b.qs[iqs]);
++    }
++
++    return mul_q8_1(q_sum, cache_a[ib_a].d, cache_b.ds, 1);
++}
++#endif // MMQ_SHMEM
++#endif
++
++// For k-quants, ib and iqs still assume 32-wide blocks, but k-quants are 256-wide
++// iqs still refers to a 32-bit integer, meaning 0..7 for 32-wide quants
++#if defined(DATA_A_Q2_K)
++// 4-byte loads for Q2_K blocks (84 bytes)
++int32_t repack(uint ib, uint iqs) {
++    const uint ib_k = ib / 8;
++    const uint iqs_k = (ib % 8) * 8 + iqs;
++
++    const uint qs_idx = (iqs_k / 32) * 8 + (iqs_k % 8);
++    const uint qs_shift = ((iqs_k % 32) / 8) * 2;
++
++    return int32_t((data_a_packed32[ib_k].qs[qs_idx] >> qs_shift) & 0x03030303);
++}
++
++uint8_t get_scale(uint ib, uint iqs) {
++    const uint ib_k = ib / 8;
++    const uint iqs_k = (ib % 8) * 8 + iqs;
++
++    return data_a[ib_k].scales[iqs_k / 4];
++}
++
++ACC_TYPE mul_q8_1(const int32_t sum_d, const int32_t sum_m, const vec2 dma, const vec2 dsb, const int32_t sum_divisor) {
++    return ACC_TYPE(dsb.x * (dma.x * float(sum_d) - dma.y * float(sum_m)));
++}
++
++#ifdef MMQ_SHMEM
++void block_a_to_shmem(const uint buf_ib, const uint ib, const uint iqs) {
++    const uint ib_k = ib / 8;
++    const uint iqs_k = (ib % 8) * 8 + iqs * QUANT_R_MMQ;
++
++    const uint qs_idx = (iqs_k / 32) * 8 + (iqs_k % 8);
++    const uint qs_shift = ((iqs_k % 32) / 8) * 2;
++
++    // Repack 4x4 quants into one int
++    const uint32_t vals0 = (data_a_packed32[ib_k].qs[qs_idx    ] >> qs_shift) & 0x03030303;
++    const uint32_t vals1 = (data_a_packed32[ib_k].qs[qs_idx + 1] >> qs_shift) & 0x03030303;
++    const uint32_t vals2 = (data_a_packed32[ib_k].qs[qs_idx + 2] >> qs_shift) & 0x03030303;
++    const uint32_t vals3 = (data_a_packed32[ib_k].qs[qs_idx + 3] >> qs_shift) & 0x03030303;
++
++    buf_a[buf_ib].qs[iqs] = vals0 | (vals1 << 2) | (vals2 << 4) | (vals3 << 6);
++
++    if (iqs == 0) {
++        buf_a[buf_ib].dm = FLOAT_TYPE_VEC2(data_a_packed32[ib_k].dm);
++        buf_a[buf_ib].scales = unpack8(data_a_packed16[ib_k].scales[iqs_k / 8]);
++    }
++}
++
++void block_a_to_registers(const uint reg_ib, const uint buf_ib) {
++    cache_a[reg_ib].dm = buf_a[buf_ib].dm;
++    cache_a[reg_ib].scales = buf_a[buf_ib].scales;
++
++    [[unroll]] for (uint iqs = 0; iqs < 2; iqs++) {
++        cache_a[reg_ib].qs[iqs] = buf_a[buf_ib].qs[iqs];
++    }
++}
++
++ACC_TYPE mmq_dot_product(const uint ib_a) {
++    int32_t sum_d = 0;
++    int32_t sum_m = 0;
++
++    [[unroll]] for (uint iqs = 0; iqs < 8; iqs++) {
++        const uint8_t scale = cache_a[ib_a].scales[iqs / 4];
++        const int32_t scale_m = int32_t(scale >> 4) * 0x01010101; // Duplicate 8-bit value across 32-bits.
++        const int32_t qs_a = int32_t((cache_a[ib_a].qs[iqs / 4] >> ((iqs % 4) * 2)) & 0x03030303);
++
++        sum_d += dotPacked4x8EXT(qs_a, cache_b.qs[iqs]) * (scale & 0xF);
++        sum_m += dotPacked4x8EXT(scale_m, cache_b.qs[iqs]);
++    }
++
++    return mul_q8_1(sum_d, sum_m, cache_a[ib_a].dm, cache_b.ds, 1);
++}
++#endif // MMQ_SHMEM
++#endif
++
++#if defined(DATA_A_Q3_K)
++// 2-byte loads for Q3_K blocks (110 bytes)
++#ifdef MMQ_SHMEM
++void block_a_to_shmem(const uint buf_ib, const uint ib, const uint iqs) {
++    const uint ib_k = ib / 8;
++    const uint hm_idx = iqs * QUANT_R_MMQ;
++    const uint iqs_k = (ib % 8) * 8 + hm_idx;
++
++    const uint qs_idx = (iqs_k / 32) * 8 + (iqs_k % 8);
++    const uint qs_shift = ((iqs_k % 32) / 8) * 2;
++    const uint hm_shift = iqs_k / 8;
++
++    // Repack 2x4 quants into one int
++    // Add the 3rd bit instead of subtracting it to allow packing the quants
++    const i8vec2 vals00 = unpack8(int16_t((data_a_packed16[ib_k].qs[qs_idx * 2        ] >> qs_shift) & uint16_t(0x0303))) |
++                          unpack8(int16_t(((data_a_packed16[ib_k].hmask[hm_idx * 2    ] >> hm_shift) & uint16_t(0x0101)) << 2));
++    const i8vec2 vals01 = unpack8(int16_t((data_a_packed16[ib_k].qs[qs_idx * 2 + 1    ] >> qs_shift) & uint16_t(0x0303))) |
++                          unpack8(int16_t(((data_a_packed16[ib_k].hmask[hm_idx * 2 + 1] >> hm_shift) & uint16_t(0x0101)) << 2));
++    const i8vec2 vals10 = unpack8(int16_t((data_a_packed16[ib_k].qs[qs_idx * 2 + 2    ] >> qs_shift) & uint16_t(0x0303))) |
++                          unpack8(int16_t(((data_a_packed16[ib_k].hmask[hm_idx * 2 + 2] >> hm_shift) & uint16_t(0x0101)) << 2));
++    const i8vec2 vals11 = unpack8(int16_t((data_a_packed16[ib_k].qs[qs_idx * 2 + 3    ] >> qs_shift) & uint16_t(0x0303))) |
++                          unpack8(int16_t(((data_a_packed16[ib_k].hmask[hm_idx * 2 + 3] >> hm_shift) & uint16_t(0x0101)) << 2));
++    buf_a[buf_ib].qs[iqs] = pack32(u8vec4(vals00.x, vals00.y, vals01.x, vals01.y)) |
++                           (pack32(u8vec4(vals10.x, vals10.y, vals11.x, vals11.y)) << 4);
++
++    if (iqs == 0) {
++        const uint is = iqs_k / 4;
++        const i8vec2 scales = i8vec2(unpack8(((data_a_packed16[ib_k].scales[(is % 8      ) / 2] >> (4 * (is / 8))) & 0x0F0F) |
++                                            (((data_a_packed16[ib_k].scales[(8 + (is % 4)) / 2] >> (2 * (is / 4))) & 0x0303) << 4)));
++
++        buf_a[buf_ib].d_scales = FLOAT_TYPE(data_a_packed16[ib_k].d) * FLOAT_TYPE_VEC2(scales - 32);
++    }
++}
++
++void block_a_to_registers(const uint reg_ib, const uint buf_ib) {
++    cache_a[reg_ib].d_scales = buf_a[buf_ib].d_scales;
++
++    [[unroll]] for (uint iqs = 0; iqs < 4; iqs++) {
++        cache_a[reg_ib].qs[iqs] = buf_a[buf_ib].qs[iqs];
++    }
++}
++
++ACC_TYPE mmq_dot_product(const uint ib_a) {
++    float result = 0.0;
++    int32_t q_sum = 0;
++
++    [[unroll]] for (uint iqs = 0; iqs < 4; iqs++) {
++        // Subtract 4 from the quants to correct the 3rd bit offset
++        const int32_t qs_a = pack32(unpack8(int32_t((cache_a[ib_a].qs[iqs / 2] >> ((iqs % 2) * 4)) & 0x0F0F0F0F)) - int8_t(4));
++
++        q_sum += dotPacked4x8EXT(qs_a, cache_b.qs[iqs]);
++    }
++    result += float(cache_a[ib_a].d_scales[0]) * float(q_sum);
++    q_sum = 0;
++
++    [[unroll]] for (uint iqs = 4; iqs < 8; iqs++) {
++        const int32_t qs_a = pack32(unpack8(int32_t((cache_a[ib_a].qs[iqs / 2] >> ((iqs % 2) * 4)) & 0x0F0F0F0F)) - int8_t(4));
++
++        q_sum += dotPacked4x8EXT(qs_a, cache_b.qs[iqs]);
++    }
++    result += float(cache_a[ib_a].d_scales[1]) * float(q_sum);
++
++    return ACC_TYPE(cache_b.ds.x * result);
++}
++#endif // MMQ_SHMEM
++#endif
++
++#if defined(DATA_A_Q4_K) || defined(DATA_A_Q5_K)
++// 4-byte loads for Q4_K blocks (144 bytes) and Q5_K blocks (176 bytes)
++ACC_TYPE mul_q8_1(const int32_t q_sum, const vec2 dma, const vec2 dsb, const int32_t sum_divisor) {
++    return ACC_TYPE(dsb.x * dma.x * float(q_sum) - dma.y * dsb.y);
++}
++
++#ifdef MMQ_SHMEM
++void block_a_to_shmem(const uint buf_ib, const uint ib, const uint iqs) {
++    const uint ib_k = ib / 8;
++    const uint iqs_k = (ib % 8) * 8 + iqs * QUANT_R_MMQ;
++
++    const uint qs_idx = (iqs_k / 16) * 8 + (iqs_k % 8);
++    const uint qs_shift = ((iqs_k % 16) / 8) * 4;
++
++    // Repack 2x4 quants into one int
++#if defined(DATA_A_Q4_K)
++    const uint32_t vals0 = (data_a_packed32[ib_k].qs[qs_idx    ] >> qs_shift) & 0x0F0F0F0F;
++    const uint32_t vals1 = (data_a_packed32[ib_k].qs[qs_idx + 1] >> qs_shift) & 0x0F0F0F0F;
++
++    buf_a[buf_ib].qs[iqs] = vals0 | (vals1 << 4);
++#else // defined(DATA_A_Q5_K)
++    const uint qh_idx = iqs * QUANT_R_MMQ;
++    const uint qh_shift = iqs_k / 8;
++
++    buf_a[buf_ib].qs[iqs] = int32_t(((data_a_packed32[ib_k].qs[qs_idx] >> qs_shift) & 0x0F0F0F0F) |
++                                   (((data_a_packed32[ib_k].qh[qh_idx] >> qh_shift) & 0x01010101) << 4));
++#endif
++
++
++    if (iqs == 0) {
++        // Scale index
++        const uint is = iqs_k / 8;
++        u8vec2 scale_dm;
++        if (is < 4) {
++            scale_dm = u8vec2(data_a[ib_k].scales[is] & 0x3F, data_a[ib_k].scales[is + 4] & 0x3F);
++        } else {
++            scale_dm = u8vec2((data_a[ib_k].scales[is+4] & 0xF) | ((data_a[ib_k].scales[is-4] & 0xC0) >> 2),
++                              (data_a[ib_k].scales[is+4] >>  4) | ((data_a[ib_k].scales[is  ] & 0xC0) >> 2));
++        }
++
++        buf_a[buf_ib].dm = FLOAT_TYPE_VEC2(data_a_packed32[ib_k].dm) * FLOAT_TYPE_VEC2(scale_dm);
++    }
++}
++
++void block_a_to_registers(const uint reg_ib, const uint buf_ib) {
++    cache_a[reg_ib].dm = buf_a[buf_ib].dm;
++
++    [[unroll]] for (uint iqs = 0; iqs < 8 / QUANT_R_MMQ; iqs++) {
++        cache_a[reg_ib].qs[iqs] = buf_a[buf_ib].qs[iqs];
++    }
++}
++
++ACC_TYPE mmq_dot_product(const uint ib_a) {
++    int32_t q_sum = 0;
++
++    [[unroll]] for (uint iqs = 0; iqs < 8; iqs++) {
++#if defined(DATA_A_Q4_K)
++        const int32_t qs_a = int32_t((cache_a[ib_a].qs[iqs / 2] >> ((iqs % 2) * 4)) & 0x0F0F0F0F);
++#else // defined(DATA_A_Q5_K)
++        const int32_t qs_a = cache_a[ib_a].qs[iqs];
++#endif
++
++        q_sum += dotPacked4x8EXT(qs_a, cache_b.qs[iqs]);
++    }
++
++    return mul_q8_1(q_sum, cache_a[ib_a].dm, cache_b.ds, 1);
++}
++#endif // MMQ_SHMEM
++#endif
++
++#ifdef MMQ_SHMEM
++void block_b_to_shmem(const uint buf_ib, const uint ib, const uint iqs) {
++    const uint ib_outer = ib / 4;
++    const uint ib_inner = ib % 4;
++
++    if (iqs == 0) {
++        buf_b[buf_ib].ds = FLOAT_TYPE_VEC2(data_b[ib_outer].ds[ib_inner]);
++    }
++
++    const ivec4 values = data_b[ib_outer].qs[ib_inner * 2 + iqs];
++    buf_b[buf_ib].qs[iqs * 4    ] = values.x;
++    buf_b[buf_ib].qs[iqs * 4 + 1] = values.y;
++    buf_b[buf_ib].qs[iqs * 4 + 2] = values.z;
++    buf_b[buf_ib].qs[iqs * 4 + 3] = values.w;
++}
++
++void block_b_to_registers(const uint ib) {
++    cache_b.ds = buf_b[ib].ds;
++    [[unroll]] for (uint iqs = 0; iqs < BK / 4; iqs++) {
++        cache_b.qs[iqs] = buf_b[ib].qs[iqs];
++    }
++}
++#endif
++
++#if defined(DATA_A_Q6_K)
++// 2-byte loads for Q6_K blocks (210 bytes)
++#ifdef MMQ_SHMEM
++void block_a_to_shmem(const uint buf_ib, const uint ib, const uint iqs) {
++    const uint ib_k = ib / 8;
++    const uint iqs_k = (ib % 8) * 8 + iqs;
++
++    const uint ql_idx = (iqs_k / 32) * 16 + iqs_k % 16;
++    const uint ql_shift = ((iqs_k % 32) / 16) * 4;
++
++    const uint qh_idx = (iqs_k / 32) * 8 + iqs;
++    const uint qh_shift = ((iqs_k % 32) / 8) * 2;
++
++    const i8vec2 vals00 = (unpack8(int16_t((data_a_packed16[ib_k].ql[ql_idx * 2    ] >> ql_shift) & uint16_t(0x0F0F))) |
++                          unpack8(int16_t(((data_a_packed16[ib_k].qh[qh_idx * 2    ] >> qh_shift) & uint16_t(0x0303)) << 4))) - int8_t(32);
++    const i8vec2 vals01 = (unpack8(int16_t((data_a_packed16[ib_k].ql[ql_idx * 2 + 1] >> ql_shift) & uint16_t(0x0F0F))) |
++                          unpack8(int16_t(((data_a_packed16[ib_k].qh[qh_idx * 2 + 1] >> qh_shift) & uint16_t(0x0303)) << 4))) - int8_t(32);
++    buf_a[buf_ib].qs[iqs] = pack32(i8vec4(vals00.x, vals00.y, vals01.x, vals01.y));
++
++    if (iqs == 0) {
++        const uint is = iqs_k / 4;
++        const i8vec2 scales = unpack8(data_a_packed16[ib_k].scales[is / 2]);
++
++        buf_a[buf_ib].d_scales = FLOAT_TYPE(data_a_packed16[ib_k].d) * FLOAT_TYPE_VEC2(scales);
++    }
++}
++
++void block_a_to_registers(const uint reg_ib, const uint buf_ib) {
++    cache_a[reg_ib].d_scales = buf_a[buf_ib].d_scales;
++
++    [[unroll]] for (uint iqs = 0; iqs < 8; iqs++) {
++        cache_a[reg_ib].qs[iqs] = buf_a[buf_ib].qs[iqs];
++    }
++}
++
++ACC_TYPE mmq_dot_product(const uint ib_a) {
++    float result = 0.0;
++    int32_t q_sum = 0;
++
++    [[unroll]] for (uint iqs = 0; iqs < 4; iqs++) {
++        const int32_t qs_a = cache_a[ib_a].qs[iqs];
++
++        q_sum += dotPacked4x8EXT(qs_a, cache_b.qs[iqs]);
++    }
++    result += float(cache_a[ib_a].d_scales[0]) * float(q_sum);
++    q_sum = 0;
++
++    [[unroll]] for (uint iqs = 4; iqs < 8; iqs++) {
++        const int32_t qs_a = cache_a[ib_a].qs[iqs];
++
++        q_sum += dotPacked4x8EXT(qs_a, cache_b.qs[iqs]);
++    }
++    result += float(cache_a[ib_a].d_scales[1]) * float(q_sum);
++
++    return ACC_TYPE(cache_b.ds.x * result);
++}
++#endif // MMQ_SHMEM
+ #endif
+ 
+ #if defined(DATA_A_Q4_0) || defined(DATA_A_Q5_0) || defined(DATA_A_Q8_0) || defined(DATA_A_IQ1_S) || defined(DATA_A_IQ2_XXS) || defined(DATA_A_IQ2_XS) || defined(DATA_A_IQ2_S) || defined(DATA_A_IQ3_XXS) || defined(DATA_A_IQ3_S) || defined(DATA_A_IQ4_XS) || defined(DATA_A_IQ4_NL)
+@@ -103,3 +568,10 @@ FLOAT_TYPE_VEC2 get_dm(uint ib) {
+     return FLOAT_TYPE_VEC2(data_a_packed32[ib].dm);
+ }
+ #endif
++
++#if defined(DATA_A_Q2_K)
++FLOAT_TYPE_VEC2 get_dm(uint ib) {
++    const uint ib_k = ib / 8;
++    return FLOAT_TYPE_VEC2(data_a_packed32[ib_k].dm);
++}
++#endif
+diff --git a/ggml/src/ggml-vulkan/vulkan-shaders/mul_mmq_shmem_types.glsl b/ggml/src/ggml-vulkan/vulkan-shaders/mul_mmq_shmem_types.glsl
+new file mode 100644
+index 000000000..72fec4404
+--- /dev/null
++++ b/ggml/src/ggml-vulkan/vulkan-shaders/mul_mmq_shmem_types.glsl
+@@ -0,0 +1,78 @@
++#if defined(DATA_A_Q4_0)
++#define QUANT_R_MMQ 2
++struct block_a_cache {
++    uint32_t qs[16/4];
++    FLOAT_TYPE dm;
++};
++#elif defined(DATA_A_Q4_1)
++#define QUANT_R_MMQ 2
++struct block_a_cache {
++    uint32_t qs[16/4];
++    FLOAT_TYPE_VEC2 dm;
++};
++#elif defined(DATA_A_Q5_0)
++#define QUANT_R_MMQ 2
++struct block_a_cache {
++    uint32_t qs[16/4];
++    uint32_t qh;
++    FLOAT_TYPE dm;
++};
++#elif defined(DATA_A_Q5_1)
++#define QUANT_R_MMQ 2
++struct block_a_cache {
++    uint32_t qs[16/4];
++    uint32_t qh;
++    FLOAT_TYPE_VEC2 dm;
++};
++#elif defined(DATA_A_Q8_0)
++#define QUANT_R_MMQ 1
++// AMD likes 4, Intel likes 1 and Nvidia likes 2
++#define BK_STEP 1
++struct block_a_cache {
++    int32_t qs[32/4];
++    FLOAT_TYPE dm;
++};
++#elif defined(DATA_A_MXFP4)
++#define QUANT_R_MMQ 2
++struct block_a_cache {
++    int32_t qs[8];
++    FLOAT_TYPE d;
++};
++#elif defined(DATA_A_Q2_K)
++#define QUANT_R_MMQ 4
++struct block_a_cache {
++    uint32_t qs[2];
++    u8vec2 scales;
++    FLOAT_TYPE_VEC2 dm;
++};
++#elif defined(DATA_A_Q3_K)
++#define QUANT_R_MMQ 2
++struct block_a_cache {
++    uint32_t qs[4];
++    FLOAT_TYPE_VEC2 d_scales;
++};
++#elif defined(DATA_A_Q4_K)
++#define QUANT_R_MMQ 2
++struct block_a_cache {
++    uint32_t qs[4];
++    FLOAT_TYPE_VEC2 dm;
++};
++#elif defined(DATA_A_Q5_K)
++#define QUANT_R_MMQ 1
++struct block_a_cache {
++    int32_t qs[8];
++    FLOAT_TYPE_VEC2 dm;
++};
++#elif defined(DATA_A_Q6_K)
++#define QUANT_R_MMQ 1
++struct block_a_cache {
++    int32_t qs[8];
++    FLOAT_TYPE_VEC2 d_scales;
++};
++#endif
++
++struct block_b_cache
++{
++    int32_t qs[8];
++    FLOAT_TYPE_VEC2 ds;
++};
+diff --git a/ggml/src/ggml-vulkan/vulkan-shaders/types.glsl b/ggml/src/ggml-vulkan/vulkan-shaders/types.glsl
+index 2fa54ce51..02578c77c 100644
+--- a/ggml/src/ggml-vulkan/vulkan-shaders/types.glsl
++++ b/ggml/src/ggml-vulkan/vulkan-shaders/types.glsl
+@@ -66,6 +66,7 @@ struct block_q4_0_packed16
+ #define QUANT_AUXF 1
+ #define A_TYPE block_q4_0
+ #define A_TYPE_PACKED16 block_q4_0_packed16
++#define DATA_A_QUANT_LEGACY
+ #endif
+ 
+ #define QUANT_K_Q4_1 32
+@@ -98,6 +99,7 @@ struct block_q4_1_packed32
+ #define A_TYPE block_q4_1
+ #define A_TYPE_PACKED16 block_q4_1_packed16
+ #define A_TYPE_PACKED32 block_q4_1_packed32
++#define DATA_A_QUANT_LEGACY
+ #endif
+ 
+ #define QUANT_K_Q5_0 32
+@@ -123,6 +125,7 @@ struct block_q5_0_packed16
+ #define QUANT_AUXF 1
+ #define A_TYPE block_q5_0
+ #define A_TYPE_PACKED16 block_q5_0_packed16
++#define DATA_A_QUANT_LEGACY
+ #endif
+ 
+ #define QUANT_K_Q5_1 32
+@@ -158,6 +161,7 @@ struct block_q5_1_packed32
+ #define A_TYPE block_q5_1
+ #define A_TYPE_PACKED16 block_q5_1_packed16
+ #define A_TYPE_PACKED32 block_q5_1_packed32
++#define DATA_A_QUANT_LEGACY
+ #endif
+ 
+ #define QUANT_K_Q8_0 32
+@@ -186,6 +190,7 @@ struct block_q8_0_packed32
+ #define A_TYPE block_q8_0
+ #define A_TYPE_PACKED16 block_q8_0_packed16
+ #define A_TYPE_PACKED32 block_q8_0_packed32
++#define DATA_A_QUANT_LEGACY
+ #endif
+ 
+ #define QUANT_K_Q8_1 32
+@@ -226,21 +231,21 @@ struct block_q2_K
+ {
+     uint8_t scales[QUANT_K_Q2_K/16];
+     uint8_t qs[QUANT_K_Q2_K/4];
+-    f16vec2 d;
++    f16vec2 dm;
+ };
+ 
+ struct block_q2_K_packed16
+ {
+     uint16_t scales[QUANT_K_Q2_K/16/2];
+     uint16_t qs[QUANT_K_Q2_K/4/2];
+-    f16vec2 d;
++    f16vec2 dm;
+ };
+ 
+ struct block_q2_K_packed32
+ {
+     uint32_t scales[QUANT_K_Q2_K/16/4];
+     uint32_t qs[QUANT_K_Q2_K/4/4];
+-    f16vec2 d;
++    f16vec2 dm;
+ };
+ 
+ #if defined(DATA_A_Q2_K)
+@@ -249,6 +254,8 @@ struct block_q2_K_packed32
+ #define A_TYPE block_q2_K
+ #define A_TYPE_PACKED16 block_q2_K_packed16
+ #define A_TYPE_PACKED32 block_q2_K_packed32
++#define SCALES_PER_32 2
++#define DATA_A_QUANT_K
+ #endif
+ 
+ #define QUANT_K_Q3_K 256
+@@ -274,27 +281,28 @@ struct block_q3_K_packed16
+ #define QUANT_R 1
+ #define A_TYPE block_q3_K
+ #define A_TYPE_PACKED16 block_q3_K_packed16
++#define DATA_A_QUANT_K
+ #endif
+ 
+ #define QUANT_K_Q4_K 256
+ 
+ struct block_q4_K
+ {
+-    f16vec2 d;
++    f16vec2 dm;
+     uint8_t scales[3*QUANT_K_Q4_K/64];
+     uint8_t qs[QUANT_K_Q4_K/2];
+ };
+ 
+ struct block_q4_K_packed16
+ {
+-    f16vec2 d;
++    f16vec2 dm;
+     uint16_t scales[3*QUANT_K_Q4_K/64/2];
+     uint16_t qs[QUANT_K_Q4_K/2/2];
+ };
+ 
+ struct block_q4_K_packed32
+ {
+-    f16vec2 d;
++    f16vec2 dm;
+     uint32_t scales[3*QUANT_K_Q4_K/64/4];
+     uint32_t qs[QUANT_K_Q4_K/2/4];
+ };
+@@ -310,13 +318,14 @@ struct block_q4_K_packed128
+ #define A_TYPE block_q4_K
+ #define A_TYPE_PACKED16 block_q4_K_packed16
+ #define A_TYPE_PACKED32 block_q4_K_packed32
++#define DATA_A_QUANT_K
+ #endif
+ 
+ #define QUANT_K_Q5_K 256
+ 
+ struct block_q5_K
+ {
+-    f16vec2 d;
++    f16vec2 dm;
+     uint8_t scales[12];
+     uint8_t qh[QUANT_K_Q5_K/8];
+     uint8_t qs[QUANT_K_Q5_K/2];
+@@ -324,12 +333,20 @@ struct block_q5_K
+ 
+ struct block_q5_K_packed16
+ {
+-    f16vec2 d;
++    f16vec2 dm;
+     uint16_t scales[12/2];
+     uint16_t qh[QUANT_K_Q5_K/8/2];
+     uint16_t qs[QUANT_K_Q5_K/2/2];
+ };
+ 
++struct block_q5_K_packed32
++{
++    f16vec2 dm;
++    uint32_t scales[12/4];
++    uint32_t qh[QUANT_K_Q5_K/8/4];
++    uint32_t qs[QUANT_K_Q5_K/2/4];
++};
++
+ struct block_q5_K_packed128
+ {
+     uvec4 q5k[11];
+@@ -340,6 +357,8 @@ struct block_q5_K_packed128
+ #define QUANT_R 1
+ #define A_TYPE block_q5_K
+ #define A_TYPE_PACKED16 block_q5_K_packed16
++#define A_TYPE_PACKED32 block_q5_K_packed32
++#define DATA_A_QUANT_K
+ #endif
+ 
+ #define QUANT_K_Q6_K 256
+@@ -356,7 +375,7 @@ struct block_q6_K_packed16
+ {
+     uint16_t ql[QUANT_K_Q6_K/2/2];
+     uint16_t qh[QUANT_K_Q6_K/4/2];
+-    int8_t scales[QUANT_K_Q6_K/16];
++    int16_t scales[QUANT_K_Q6_K/16/2];
+     float16_t d;
+ };
+ 
+@@ -365,6 +384,7 @@ struct block_q6_K_packed16
+ #define QUANT_R 1
+ #define A_TYPE block_q6_K
+ #define A_TYPE_PACKED16 block_q6_K_packed16
++#define DATA_A_QUANT_K
+ #endif
+ 
+ // IQuants
+@@ -1363,18 +1383,11 @@ struct block_mxfp4
+     uint8_t qs[QUANT_K_MXFP4/2];
+ };
+ 
+-//struct block_mxfp4_packed16
+-//{
+-//    uint8_t e;
+-//    uint16_t qs[QUANT_K_MXFP4/2/2];
+-//};
+-
+ #if defined(DATA_A_MXFP4)
+ #define QUANT_K QUANT_K_MXFP4
+ #define QUANT_R QUANT_R_MXFP4
+ #define QUANT_AUXF 1
+ #define A_TYPE block_mxfp4
+-//#define A_TYPE_PACKED16 block_mxfp4_packed16
+ #endif
+ 
+ #if defined(DATA_A_IQ4_NL) || defined(DATA_A_IQ4_XS)
+@@ -1397,12 +1410,12 @@ void init_iq_shmem(uvec3 wgsize)
+ #endif
+ 
+ #if defined(DATA_A_MXFP4)
+-const FLOAT_TYPE kvalues_mxfp4_const[16] = {
+-    FLOAT_TYPE(0.0f), FLOAT_TYPE(0.5f), FLOAT_TYPE(1.0f), FLOAT_TYPE(1.5f), FLOAT_TYPE(2.0f), FLOAT_TYPE(3.0f), FLOAT_TYPE(4.0f), FLOAT_TYPE(6.0f),
+-    FLOAT_TYPE(-0.0f), FLOAT_TYPE(-0.5f), FLOAT_TYPE(-1.0f), FLOAT_TYPE(-1.5f), FLOAT_TYPE(-2.0f), FLOAT_TYPE(-3.0f), FLOAT_TYPE(-4.0f), FLOAT_TYPE(-6.0f)
++const int8_t kvalues_mxfp4_const[16] = {
++    int8_t(0), int8_t(1), int8_t(2), int8_t(3), int8_t(4), int8_t(6), int8_t(8), int8_t(12),
++    int8_t(0), int8_t(-1), int8_t(-2), int8_t(-3), int8_t(-4), int8_t(-6), int8_t(-8), int8_t(-12),
+ };
+ 
+-shared FLOAT_TYPE kvalues_mxfp4[16];
++shared int8_t kvalues_mxfp4[16];
+ 
+ #define NEEDS_INIT_IQ_SHMEM
+ void init_iq_shmem(uvec3 wgsize)
+diff --git a/ggml/src/ggml-vulkan/vulkan-shaders/vulkan-shaders-gen.cpp b/ggml/src/ggml-vulkan/vulkan-shaders/vulkan-shaders-gen.cpp
+index 0f25ba345..03fa01639 100644
+--- a/ggml/src/ggml-vulkan/vulkan-shaders/vulkan-shaders-gen.cpp
++++ b/ggml/src/ggml-vulkan/vulkan-shaders/vulkan-shaders-gen.cpp
+@@ -566,7 +566,8 @@ void matmul_shaders(bool fp16, MatMulIdType matmul_id_type, bool coopmat, bool c
+         }
+ 
+ #if defined(GGML_VULKAN_INTEGER_DOT_GLSLC_SUPPORT)
+-        if (!coopmat && !coopmat2 && matmul_id_type == MatMulIdType::NONE && is_legacy_quant(tname)) {
++        // Integer dot mmq performs better with f32 accumulators
++        if (!f16acc && !coopmat && !coopmat2 && (is_legacy_quant(tname) || is_k_quant(tname) || tname == "mxfp4")) {
+             string_to_spv(shader_name + "_" + tname + "_q8_1", "mul_mmq.comp", merge_maps(merge_maps(base_dict, float_type_dict), {{data_a_key, "1"}, {"D_TYPE", "float"},}), fp16, coopmat, coopmat2, f16acc);
+         }
+ #endif
+@@ -574,7 +575,7 @@ void matmul_shaders(bool fp16, MatMulIdType matmul_id_type, bool coopmat, bool c
+ }
+ 
+ void process_shaders() {
+-    std::map<std::string, std::string> base_dict = {{"FLOAT_TYPE", "float"}};
++    std::map<std::string, std::string> base_dict = {{"FLOAT_TYPE", "float"}, {"FLOAT_TYPE_VEC2", "vec2"}};
+ 
+     // matmul
+     for (const MatMulIdType& matmul_id_type : {MatMulIdType::NONE, MatMulIdType::DEFAULT, MatMulIdType::SUBGROUP}) {
diff --git a/llama/patches/0031-vulkan-Update-topk_moe-fusion-to-handle-gpt-s-late-s.patch b/llama/patches/0031-vulkan-Update-topk_moe-fusion-to-handle-gpt-s-late-s.patch
new file mode 100644
index 00000000..41cd9cd5
--- /dev/null
+++ b/llama/patches/0031-vulkan-Update-topk_moe-fusion-to-handle-gpt-s-late-s.patch
@@ -0,0 +1,657 @@
+From 0000000000000000000000000000000000000000 Mon Sep 17 00:00:00 2001
+From: Jeff Bolz <jbolz@nvidia.com>
+Date: Wed, 29 Oct 2025 08:44:29 -0500
+Subject: [PATCH] vulkan: Update topk_moe fusion to handle gpt's late softmax
+ (#16656)
+
+* vulkan: Update topk_moe fusion to handle gpt's late softmax
+
+Based on #16649.
+
+* Add ggml_check_edges
+
+* Add sync logging to show fusion effects
+
+* handle clamp added in #16655
+
+* Update ggml/src/ggml-impl.h
+
+Co-authored-by: Diego Devesa <slarengh@gmail.com>
+---
+ ggml/src/ggml-impl.h                          |  16 +
+ ggml/src/ggml-vulkan/ggml-vulkan.cpp          | 304 +++++++++++-------
+ .../ggml-vulkan/vulkan-shaders/topk_moe.comp  |  90 ++++--
+ 3 files changed, 272 insertions(+), 138 deletions(-)
+
+diff --git a/ggml/src/ggml-impl.h b/ggml/src/ggml-impl.h
+index 639d551a2..e5c446d1d 100644
+--- a/ggml/src/ggml-impl.h
++++ b/ggml/src/ggml-impl.h
+@@ -693,6 +693,7 @@ GGML_API void ggml_dxgi_pdh_release();
+ #endif
+ 
+ #ifdef __cplusplus
++#include <array>
+ #include <initializer_list>
+ #include <vector>
+ 
+@@ -708,6 +709,21 @@ inline bool ggml_can_fuse_subgraph(const struct ggml_cgraph *          cgraph,
+     return ggml_can_fuse_subgraph(cgraph, start_idx, ops.size(), ops.begin(), outputs.begin(), outputs.size());
+ }
+ 
++// Return true if the edges in the graph match expectations.
++inline bool ggml_check_edges(const struct ggml_cgraph *                cgraph,
++                             int                                       start_idx,
++                             std::initializer_list<std::array<int, 3>> edges) {
++    for (const auto & edge : edges) {
++        int dst_node = edge[0];
++        int src_idx  = edge[1];
++        int src_node = edge[2];
++        if (cgraph->nodes[start_idx + dst_node]->src[src_idx] != cgraph->nodes[start_idx + src_node]) {
++            return false;
++        }
++    }
++    return true;
++}
++
+ // expose GGUF internals for test code
+ GGML_API size_t gguf_type_size(enum gguf_type type);
+ GGML_API struct gguf_context * gguf_init_from_file_impl(FILE * file, struct gguf_init_params params);
+diff --git a/ggml/src/ggml-vulkan/ggml-vulkan.cpp b/ggml/src/ggml-vulkan/ggml-vulkan.cpp
+index 53b57c179..b2855b078 100644
+--- a/ggml/src/ggml-vulkan/ggml-vulkan.cpp
++++ b/ggml/src/ggml-vulkan/ggml-vulkan.cpp
+@@ -387,12 +387,76 @@ static constexpr uint32_t num_argsort_pipelines = 11;
+ static constexpr uint32_t max_argsort_cols = 1 << (num_argsort_pipelines-1);
+ static constexpr uint32_t num_topk_moe_pipelines = 10;
+ 
+-static constexpr std::array topk_moe_norm{ GGML_OP_SOFT_MAX, GGML_OP_RESHAPE,  GGML_OP_ARGSORT,
+-                                           GGML_OP_VIEW,     GGML_OP_GET_ROWS, GGML_OP_RESHAPE,
+-                                           GGML_OP_SUM_ROWS, GGML_OP_DIV,      GGML_OP_RESHAPE };
+-static constexpr std::array topk_moe     { GGML_OP_SOFT_MAX, GGML_OP_RESHAPE,  GGML_OP_ARGSORT,
+-                                           GGML_OP_VIEW,     GGML_OP_GET_ROWS };
++static constexpr std::initializer_list<ggml_op> topk_moe_early_softmax_norm{ GGML_OP_SOFT_MAX, GGML_OP_RESHAPE,  GGML_OP_ARGSORT,
++                                                                             GGML_OP_VIEW,     GGML_OP_GET_ROWS, GGML_OP_RESHAPE,
++                                                                             GGML_OP_SUM_ROWS, GGML_OP_CLAMP,    GGML_OP_DIV,
++                                                                             GGML_OP_RESHAPE };
++static constexpr std::initializer_list<ggml_op> topk_moe_early_softmax     { GGML_OP_SOFT_MAX, GGML_OP_RESHAPE,  GGML_OP_ARGSORT,
++                                                                             GGML_OP_VIEW,     GGML_OP_GET_ROWS };
++static constexpr std::initializer_list<ggml_op> topk_moe_late_softmax      { GGML_OP_ARGSORT,  GGML_OP_VIEW,
++                                                                             GGML_OP_GET_ROWS, GGML_OP_RESHAPE,
++                                                                             GGML_OP_SOFT_MAX, GGML_OP_RESHAPE };
++
++//node #978 (  SOFT_MAX):     ffn_moe_probs-15 (   0K) [Vulka         ] use=2:    ffn_moe_logits-15 (   0K) [Vulka         ]
++//node #979 (   RESHAPE): ffn_moe_probs-15 (re (   0K) [Vulka         ] use=1:     ffn_moe_probs-15 (   0K) [Vulka         ]
++//node #980 (   ARGSORT):   ffn_moe_argsort-15 (   0K) [Vulka         ] use=1:     ffn_moe_probs-15 (   0K) [Vulka         ]
++//node #981 (      VIEW):      ffn_moe_topk-15 (   0K) [Vulka         ] use=4:   ffn_moe_argsort-15 (   0K) [Vulka         ]
++//node #982 (  GET_ROWS):   ffn_moe_weights-15 (   0K) [Vulka         ] use=1: ffn_moe_probs-15 (re (   0K) [Vulka         ]      ffn_moe_topk-15 (   0K) [Vulka         ]
++//node #983 (   RESHAPE): ffn_moe_weights-15 ( (   0K) [Vulka         ] use=2:   ffn_moe_weights-15 (   0K) [Vulka         ]
++//node #984 (  SUM_ROWS): ffn_moe_weights_sum- (   0K) [Vulka         ] use=1: ffn_moe_weights-15 ( (   0K) [Vulka         ]
++//node #985 (     CLAMP): ffn_moe_weights_sum_ (   0K) [Vulka         ] use=1: ffn_moe_weights_sum- (   0K) [Vulka         ]
++//node #986 (       DIV): ffn_moe_weights_norm (   0K) [Vulka         ] use=1: ffn_moe_weights-15 ( (   0K) [Vulka         ] ffn_moe_weights_sum_ (   0K) [Vulka         ]
++//node #987 (   RESHAPE): ffn_moe_weights_norm (   0K) [Vulka         ] use=1: ffn_moe_weights_norm (   0K) [Vulka         ]
++static constexpr std::initializer_list<std::array<int, 3>> topk_moe_early_softmax_norm_edges {
++    { 1, 0, 0 }, // reshape->src[0]  == softmax
++    { 2, 0, 0 }, // argsort->src[0]  == softmax
++    { 3, 0, 2 }, // view->src[0]     == argsort
++    { 4, 0, 1 }, // get_rows->src[0] == reshape
++    { 4, 1, 3 }, // get_rows->src[1] == view
++    { 5, 0, 4 }, // reshape->src[0]  == get_rows
++    { 6, 0, 5 }, // sum_rows->src[0] == reshape
++    { 7, 0, 6 }, // clamp->src[0]    == sum_rows
++    { 8, 0, 5 }, // div->src[0]      == reshape
++    { 8, 1, 7 }, // div->src[1]      == clamp
++    { 9, 0, 8 }, // reshape->src[0]  == div
++};
++
++// same as early_softmax_norm but ending after the get_rows
++static constexpr std::initializer_list<std::array<int, 3>> topk_moe_early_softmax_edges {
++    { 1, 0, 0 }, // reshape->src[0]  == softmax
++    { 2, 0, 0 }, // argsort->src[0]  == softmax
++    { 3, 0, 2 }, // view->src[0]     == argsort
++    { 4, 0, 1 }, // get_rows->src[0] == reshape
++    { 4, 1, 3 }, // get_rows->src[1] == view
++};
+ 
++//node #652 (   ARGSORT):   ffn_moe_argsort-11 (   0K) [Vulka         ] use=1:     ffn_moe_probs-11 (   0K) [Vulka         ]
++//node #653 (      VIEW):      ffn_moe_topk-11 (   0K) [Vulka         ] use=7:   ffn_moe_argsort-11 (   0K) [Vulka         ]
++//node #654 (  GET_ROWS):   ffn_moe_weights-11 (   0K) [Vulka         ] use=1: ffn_moe_probs-11 (re (   0K) [Vulka         ]      ffn_moe_topk-11 (   0K) [Vulka         ]
++//node #655 (   RESHAPE): ffn_moe_weights-11 ( (   0K) [Vulka         ] use=1:   ffn_moe_weights-11 (   0K) [Vulka         ]
++//node #656 (  SOFT_MAX):             node_656 (   0K) [Vulka         ] use=1: ffn_moe_weights-11 ( (   0K) [Vulka         ]
++//node #657 (   RESHAPE): ffn_moe_weights_soft (   0K) [Vulka         ] use=1:             node_656 (   0K) [Vulka         ]
++static constexpr std::initializer_list<std::array<int, 3>> topk_moe_late_softmax_edges {
++    { 1, 0, 0 }, // view->src[0]     == argsort
++    { 2, 1, 1 }, // get_rows->src[1] == view
++    { 3, 0, 2 }, // reshape->src[0]  == get_rows
++    { 4, 0, 3 }, // soft_max->src[0] == reshape
++    { 5, 0, 4 }, // reshape->src[0]  == soft_max
++};
++
++enum topk_moe_mode {
++    TOPK_MOE_EARLY_SOFTMAX,
++    TOPK_MOE_EARLY_SOFTMAX_NORM,
++    TOPK_MOE_LATE_SOFTMAX,
++    TOPK_MOE_COUNT,
++};
++
++static topk_moe_mode ggml_vk_num_additional_ops_to_topk_moe_mode(uint32_t num) {
++    topk_moe_mode mode = num == topk_moe_early_softmax_norm.size() - 1 ? TOPK_MOE_EARLY_SOFTMAX_NORM :
++                         num == topk_moe_early_softmax.size() - 1      ? TOPK_MOE_EARLY_SOFTMAX :
++                                                                         TOPK_MOE_LATE_SOFTMAX;
++    return mode;
++}
+ 
+ struct vk_device_struct {
+     std::recursive_mutex mutex;
+@@ -607,8 +671,7 @@ struct vk_device_struct {
+ 
+     vk_pipeline pipeline_flash_attn_split_k_reduce;
+ 
+-    // [2] is {!norm, norm}
+-    vk_pipeline pipeline_topk_moe[num_topk_moe_pipelines][2];
++    vk_pipeline pipeline_topk_moe[num_topk_moe_pipelines][TOPK_MOE_COUNT];
+ 
+     std::vector<vk_pipeline_ref> all_pipelines;
+ 
+@@ -956,6 +1019,8 @@ static_assert(sizeof(vk_op_multi_add_push_constants) <= 256);
+ struct vk_op_topk_moe_push_constants {
+     uint32_t n_rows;
+     uint32_t n_expert_used;
++    float clamp_min;
++    float clamp_max;
+ };
+ 
+ struct vk_op_add_id_push_constants {
+@@ -3806,8 +3871,9 @@ static void ggml_vk_load_shaders(vk_device& device) {
+     ggml_vk_create_pipeline(device, device->pipeline_conv2d_dw_cwhn_f16_f32, "conv2d_dw_cwhn_f16_f32", conv2d_dw_cwhn_f16_f32_len, conv2d_dw_cwhn_f16_f32_data, "main", 3, sizeof(vk_op_conv2d_dw_push_constants), {512, 1, 1}, {}, 1);
+ 
+     for (uint32_t i = 0; i < num_topk_moe_pipelines; ++i) {
+-        ggml_vk_create_pipeline2(device, device->pipeline_topk_moe[i][0], "topk_moe_f32_"+std::to_string(i),   topk_moe_f32_len, topk_moe_f32_data, "main", 3, sizeof(vk_op_topk_moe_push_constants), {1, 1, 1}, {device->subgroup_size, 1u<<i, 0}, 1, true, true);
+-        ggml_vk_create_pipeline2(device, device->pipeline_topk_moe[i][1], "topk_moe_f32_"+std::to_string(i),   topk_moe_f32_len, topk_moe_f32_data, "main", 3, sizeof(vk_op_topk_moe_push_constants), {1, 1, 1}, {device->subgroup_size, 1u<<i, 1}, 1, true, true);
++        ggml_vk_create_pipeline2(device, device->pipeline_topk_moe[i][TOPK_MOE_EARLY_SOFTMAX],      "topk_moe_f32_early_softmax_"+std::to_string(i),       topk_moe_f32_len, topk_moe_f32_data, "main", 3, sizeof(vk_op_topk_moe_push_constants), {1, 1, 1}, {device->subgroup_size, 1u<<i, 0, 0}, 1, true, true);
++        ggml_vk_create_pipeline2(device, device->pipeline_topk_moe[i][TOPK_MOE_EARLY_SOFTMAX_NORM], "topk_moe_f32_early_softmax_norm"+std::to_string(i),   topk_moe_f32_len, topk_moe_f32_data, "main", 3, sizeof(vk_op_topk_moe_push_constants), {1, 1, 1}, {device->subgroup_size, 1u<<i, 1, 0}, 1, true, true);
++        ggml_vk_create_pipeline2(device, device->pipeline_topk_moe[i][TOPK_MOE_LATE_SOFTMAX],       "topk_moe_f32_late_softmax"+std::to_string(i),         topk_moe_f32_len, topk_moe_f32_data, "main", 3, sizeof(vk_op_topk_moe_push_constants), {1, 1, 1}, {device->subgroup_size, 1u<<i, 0, 1}, 1, true, true);
+     }
+ 
+     for (auto &c : compiles) {
+@@ -8085,8 +8151,8 @@ static vk_pipeline ggml_vk_op_get_pipeline(ggml_backend_vk_context * ctx, const
+         if (ctx->num_additional_fused_ops) {
+             uint32_t idx = (uint32_t)ceilf(log2f(float(dst->ne[0])));
+             GGML_ASSERT(idx < num_topk_moe_pipelines);
+-            bool with_norm = ctx->num_additional_fused_ops == topk_moe_norm.size() - 1;
+-            return ctx->device->pipeline_topk_moe[idx][with_norm];
++            topk_moe_mode mode = ggml_vk_num_additional_ops_to_topk_moe_mode(ctx->num_additional_fused_ops);
++            return ctx->device->pipeline_topk_moe[idx][mode];
+         }
+ 
+         if (src0->type == GGML_TYPE_F32 && (src1 == nullptr || src1->type == GGML_TYPE_F32) && dst->type == GGML_TYPE_F32) {
+@@ -8141,6 +8207,13 @@ static vk_pipeline ggml_vk_op_get_pipeline(ggml_backend_vk_context * ctx, const
+             return nullptr;
+         }
+     case GGML_OP_ARGSORT:
++        if (ctx->num_additional_fused_ops) {
++            uint32_t idx = (uint32_t)ceilf(log2f(float(dst->ne[0])));
++            GGML_ASSERT(idx < num_topk_moe_pipelines);
++            topk_moe_mode mode = ggml_vk_num_additional_ops_to_topk_moe_mode(ctx->num_additional_fused_ops);
++            return ctx->device->pipeline_topk_moe[idx][mode];
++        }
++
+         if (src0->type == GGML_TYPE_F32 && dst->type == GGML_TYPE_I32) {
+             uint32_t idx = (uint32_t)ceilf(log2f(float(dst->ne[0])));
+             return ctx->device->pipeline_argsort_f32[idx];
+@@ -9676,10 +9749,12 @@ static void ggml_vk_soft_max_back(ggml_backend_vk_context * ctx, vk_context& sub
+ 
+ static void ggml_vk_topk_moe(ggml_backend_vk_context * ctx, vk_context& subctx, ggml_cgraph * cgraph, int node_idx, bool dryrun = false) {
+ 
+-    bool with_norm = ctx->num_additional_fused_ops == topk_moe_norm.size() - 1;
++    topk_moe_mode mode = ggml_vk_num_additional_ops_to_topk_moe_mode(ctx->num_additional_fused_ops);
+     ggml_tensor * logits = cgraph->nodes[node_idx + 0]->src[0];
+-    ggml_tensor * weights = with_norm ? cgraph->nodes[node_idx + 8] : cgraph->nodes[node_idx + 4];
+-    ggml_tensor * ids = cgraph->nodes[node_idx + 3];
++    ggml_tensor * weights = (mode == TOPK_MOE_EARLY_SOFTMAX_NORM) ? cgraph->nodes[node_idx + 9] :
++                            (mode == TOPK_MOE_EARLY_SOFTMAX)      ? cgraph->nodes[node_idx + 4] :
++                                                                    cgraph->nodes[node_idx + 5];
++    ggml_tensor * ids = (mode == TOPK_MOE_LATE_SOFTMAX) ? cgraph->nodes[node_idx + 1] : cgraph->nodes[node_idx + 3];
+ 
+     GGML_ASSERT(logits->type == GGML_TYPE_F32);
+     GGML_ASSERT(weights->type == GGML_TYPE_F32);
+@@ -9738,9 +9813,14 @@ static void ggml_vk_topk_moe(ggml_backend_vk_context * ctx, vk_context& subctx,
+         GGML_ASSERT(d_ids != nullptr);
+     }
+ 
+-    vk_op_topk_moe_push_constants pc;
++    vk_op_topk_moe_push_constants pc {};
+     pc.n_rows = n_rows;
+     pc.n_expert_used = n_expert_used;
++    if (mode == TOPK_MOE_EARLY_SOFTMAX_NORM) {
++        ggml_tensor * clamp = cgraph->nodes[node_idx + 7];
++        pc.clamp_min = ggml_get_op_params_f32(clamp, 0);
++        pc.clamp_max = ggml_get_op_params_f32(clamp, 1);
++    }
+ 
+     GGML_ASSERT(n_expert_used <= n_experts);
+ 
+@@ -11335,7 +11415,13 @@ static bool ggml_vk_build_graph(ggml_backend_vk_context * ctx, ggml_cgraph * cgr
+                 }
+             }
+         }
++
++#define ENABLE_SYNC_LOGGING 0
++
+         if (need_sync) {
++#if ENABLE_SYNC_LOGGING
++            std::cerr <<  "sync" << std::endl;
++#endif
+             ctx->unsynced_nodes_written.clear();
+             ctx->unsynced_nodes_read.clear();
+             ggml_vk_sync_buffers(ctx, compute_ctx);
+@@ -11353,6 +11439,18 @@ static bool ggml_vk_build_graph(ggml_backend_vk_context * ctx, ggml_cgraph * cgr
+             }
+         }
+     }
++#if ENABLE_SYNC_LOGGING
++    if (!dryrun) {
++        for (int i = 0; i < ctx->num_additional_fused_ops + 1; ++i) {
++            auto *n = cgraph->nodes[node_idx + i];
++            std::cerr << node_idx + i << " " << ggml_op_name(n->op) << " " <<  n->name;
++            if (n->op == GGML_OP_GLU) {
++                std::cerr << " " << ggml_glu_op_name(ggml_get_glu_op(n)) << " " << (n->src[1] ? "split" : "single") << " ";
++            }
++            std::cerr << std::endl;
++        }
++    }
++#endif
+ 
+     switch (node->op) {
+     case GGML_OP_REPEAT:
+@@ -11531,7 +11629,11 @@ static bool ggml_vk_build_graph(ggml_backend_vk_context * ctx, ggml_cgraph * cgr
+ 
+         break;
+     case GGML_OP_ARGSORT:
+-        ggml_vk_argsort(ctx, compute_ctx, src0, node, dryrun);
++        if (ctx->num_additional_fused_ops) {
++            ggml_vk_topk_moe(ctx, compute_ctx, cgraph, node_idx, dryrun);
++        } else {
++            ggml_vk_argsort(ctx, compute_ctx, src0, node, dryrun);
++        }
+ 
+         break;
+     case GGML_OP_SUM:
+@@ -12329,30 +12431,27 @@ static bool ggml_vk_can_fuse(const struct ggml_cgraph * cgraph, int node_idx, st
+ }
+ 
+ static bool ggml_vk_can_fuse_topk_moe(ggml_backend_vk_context * ctx, const struct ggml_cgraph * cgraph,
+-                                      int node_idx, bool with_norm) {
++                                      int node_idx, topk_moe_mode mode) {
+ 
+-    if (with_norm) {
+-        if (node_idx + (int)topk_moe_norm.size() > cgraph->n_nodes) {
+-            return false;
+-        }
+-        for (size_t i = 0; i < topk_moe_norm.size(); ++i) {
+-            if (cgraph->nodes[node_idx + i]->op != topk_moe_norm[i]) {
+-                return false;
+-            }
+-        }
+-    } else {
+-        if (node_idx + (int)topk_moe.size() > cgraph->n_nodes) {
+-            return false;
+-        }
+-        for (size_t i = 0; i < topk_moe.size(); ++i) {
+-            if (cgraph->nodes[node_idx + i]->op != topk_moe[i]) {
+-                return false;
+-            }
+-        }
+-    }
++    const ggml_tensor * softmax;
++    const ggml_tensor * weights;
+ 
+-    const ggml_tensor * softmax =  cgraph->nodes[node_idx + 0];
+-    const ggml_tensor * weights = with_norm ? cgraph->nodes[node_idx + 8] : cgraph->nodes[node_idx + 4];
++    switch (mode) {
++    case TOPK_MOE_EARLY_SOFTMAX_NORM:
++        softmax = cgraph->nodes[node_idx + 0];
++        weights = cgraph->nodes[node_idx + 9];
++        break;
++    case TOPK_MOE_EARLY_SOFTMAX:
++        softmax = cgraph->nodes[node_idx + 0];
++        weights = cgraph->nodes[node_idx + 4];
++        break;
++    case TOPK_MOE_LATE_SOFTMAX:
++        softmax = cgraph->nodes[node_idx + 4];
++        weights = cgraph->nodes[node_idx + 5];
++        break;
++    default:
++        return false;
++    }
+ 
+     const float * op_params = (const float *)softmax->op_params;
+ 
+@@ -12378,60 +12477,6 @@ static bool ggml_vk_can_fuse_topk_moe(ggml_backend_vk_context * ctx, const struc
+         return false;
+     }
+ 
+-    // Check that the nodes don't have any unexpected uses
+-    const ggml_tensor * reshape1 =  cgraph->nodes[node_idx + 1];
+-    const ggml_tensor * argsort =   cgraph->nodes[node_idx + 2];
+-    const ggml_tensor * view =      cgraph->nodes[node_idx + 3];
+-    const ggml_tensor * get_rows =  cgraph->nodes[node_idx + 4];
+-    const ggml_tensor * reshape5 =  with_norm ? cgraph->nodes[node_idx + 5] : nullptr;
+-    const ggml_tensor * sum_rows =  with_norm ? cgraph->nodes[node_idx + 6] : nullptr;
+-    const ggml_tensor * div =       with_norm ? cgraph->nodes[node_idx + 7] : nullptr;
+-    const ggml_tensor * reshape8 =  with_norm ? cgraph->nodes[node_idx + 8] : nullptr;
+-
+-    // softmax is used by reshape and argsort
+-    if (ggml_node_get_use_count(cgraph, node_idx) != 2 ||
+-        reshape1->src[0] != softmax ||
+-        argsort->src[0] != softmax) {
+-        return false;
+-    }
+-    // reshape is used by get_rows
+-    if (ggml_node_get_use_count(cgraph, node_idx + 1) != 1 ||
+-        get_rows->src[0] != reshape1) {
+-        return false;
+-    }
+-    // argsort is used by view
+-    if (ggml_node_get_use_count(cgraph, node_idx + 2) != 1 ||
+-        view->src[0] != argsort) {
+-        return false;
+-    }
+-    // view is written (via argsort), we can skip checking it
+-
+-    if (with_norm) {
+-        // get_rows is used by reshape
+-        if (ggml_node_get_use_count(cgraph, node_idx + 4) != 1 ||
+-            reshape5->src[0] != get_rows) {
+-            return false;
+-        }
+-
+-        // reshape is used by sum_rows and div
+-        if (ggml_node_get_use_count(cgraph, node_idx + 5) != 2 ||
+-            sum_rows->src[0] != reshape5 ||
+-            div->src[0] != reshape5) {
+-            return false;
+-        }
+-
+-        // sum_rows is used by div
+-        if (ggml_node_get_use_count(cgraph, node_idx + 6) != 1 ||
+-            div->src[1] != sum_rows) {
+-            return false;
+-        }
+-
+-        // div/reshape are written
+-        if (reshape8->src[0] != div) {
+-            return false;
+-        }
+-    }
+-
+     if (!ctx->device->subgroup_arithmetic ||
+         !ctx->device->subgroup_shuffle ||
+         !ctx->device->subgroup_require_full_support ||
+@@ -12517,10 +12562,18 @@ static ggml_status ggml_backend_vk_graph_compute(ggml_backend_t backend, ggml_cg
+                 ctx->num_additional_fused_ops = num_adds - 1;
+             } else if (ggml_vk_can_fuse(cgraph, i, { GGML_OP_RMS_NORM, GGML_OP_MUL })) {
+                 ctx->num_additional_fused_ops = 1;
+-            } else if (ggml_vk_can_fuse_topk_moe(ctx, cgraph, i, true)) {
+-                ctx->num_additional_fused_ops = topk_moe_norm.size() - 1;
+-            } else if (ggml_vk_can_fuse_topk_moe(ctx, cgraph, i, false)) {
+-                ctx->num_additional_fused_ops = topk_moe.size() - 1;
++            } else if (ggml_can_fuse_subgraph(cgraph, i, topk_moe_early_softmax_norm, { i + 3, i + 9 }) &&
++                       ggml_check_edges(cgraph, i, topk_moe_early_softmax_norm_edges) &&
++                       ggml_vk_can_fuse_topk_moe(ctx, cgraph, i, TOPK_MOE_EARLY_SOFTMAX_NORM)) {
++                ctx->num_additional_fused_ops = topk_moe_early_softmax_norm.size() - 1;
++            } else if (ggml_can_fuse_subgraph(cgraph, i, topk_moe_early_softmax, { i + 3, i + 4 }) &&
++                       ggml_check_edges(cgraph, i, topk_moe_early_softmax_edges) &&
++                       ggml_vk_can_fuse_topk_moe(ctx, cgraph, i, TOPK_MOE_EARLY_SOFTMAX)) {
++                ctx->num_additional_fused_ops = topk_moe_early_softmax.size() - 1;
++            } else if (ggml_can_fuse_subgraph(cgraph, i, topk_moe_late_softmax, { i + 1, i + 5 }) &&
++                       ggml_check_edges(cgraph, i, topk_moe_late_softmax_edges) &&
++                       ggml_vk_can_fuse_topk_moe(ctx, cgraph, i, TOPK_MOE_LATE_SOFTMAX)) {
++                ctx->num_additional_fused_ops = topk_moe_late_softmax.size() - 1;
+             }
+         }
+         ggml_vk_build_graph(ctx, cgraph, i, nullptr, 0, true, false, false, false);
+@@ -12618,10 +12671,18 @@ static ggml_status ggml_backend_vk_graph_compute(ggml_backend_t backend, ggml_cg
+                 ctx->num_additional_fused_ops = num_adds - 1;
+             } else if (ggml_vk_can_fuse(cgraph, i, { GGML_OP_RMS_NORM, GGML_OP_MUL })) {
+                 ctx->num_additional_fused_ops = 1;
+-            } else if (ggml_vk_can_fuse_topk_moe(ctx, cgraph, i, true)) {
+-                ctx->num_additional_fused_ops = topk_moe_norm.size() - 1;
+-            } else if (ggml_vk_can_fuse_topk_moe(ctx, cgraph, i, false)) {
+-                ctx->num_additional_fused_ops = topk_moe.size() - 1;
++            } else if (ggml_can_fuse_subgraph(cgraph, i, topk_moe_early_softmax_norm, { i + 3, i + 9 }) &&
++                       ggml_check_edges(cgraph, i, topk_moe_early_softmax_norm_edges) &&
++                       ggml_vk_can_fuse_topk_moe(ctx, cgraph, i, TOPK_MOE_EARLY_SOFTMAX_NORM)) {
++                ctx->num_additional_fused_ops = topk_moe_early_softmax_norm.size() - 1;
++            } else if (ggml_can_fuse_subgraph(cgraph, i, topk_moe_early_softmax, { i + 3, i + 4 }) &&
++                       ggml_check_edges(cgraph, i, topk_moe_early_softmax_edges) &&
++                       ggml_vk_can_fuse_topk_moe(ctx, cgraph, i, TOPK_MOE_EARLY_SOFTMAX)) {
++                ctx->num_additional_fused_ops = topk_moe_early_softmax.size() - 1;
++            } else if (ggml_can_fuse_subgraph(cgraph, i, topk_moe_late_softmax, { i + 1, i + 5 }) &&
++                       ggml_check_edges(cgraph, i, topk_moe_late_softmax_edges) &&
++                       ggml_vk_can_fuse_topk_moe(ctx, cgraph, i, TOPK_MOE_LATE_SOFTMAX)) {
++                ctx->num_additional_fused_ops = topk_moe_late_softmax.size() - 1;
+             }
+         }
+ 
+@@ -12754,25 +12815,44 @@ static void ggml_vk_graph_optimize(ggml_backend_t backend, struct ggml_cgraph *
+     while (first_unused < graph->n_nodes) {
+         std::vector<int> current_set;
+ 
+-        // Avoid reordering topk_moe_norm
+-        if (first_unused + (int)topk_moe_norm.size() <= graph->n_nodes) {
+-            bool is_topk_moe_norm = true;
+-            for (size_t j = 0; j < topk_moe_norm.size(); ++j) {
+-                if (graph->nodes[first_unused + j]->op != topk_moe_norm[j] || used[first_unused + j]) {
+-                    is_topk_moe_norm = false;
++        // Check for fusion patterns and avoid reordering them
++        auto const &match_pattern = [&](const std::initializer_list<ggml_op> &pattern, int start) -> bool {
++            if (start + (int)pattern.size() <= graph->n_nodes) {
++                bool is_pattern = true;
++                for (size_t j = 0; j < pattern.size(); ++j) {
++                    if (graph->nodes[start + j]->op != pattern.begin()[j] || used[start + j]) {
++                        is_pattern = false;
++                    }
+                 }
++                return is_pattern;
+             }
+-            if (is_topk_moe_norm) {
+-                for (size_t j = 0; j < topk_moe_norm.size(); ++j) {
++            return false;
++        };
++
++        auto const &keep_pattern = [&](const std::initializer_list<ggml_op> &pattern) -> bool {
++            if (match_pattern(pattern, first_unused)) {
++                for (size_t j = 0; j < pattern.size(); ++j) {
+                     new_order.push_back(graph->nodes[first_unused + j]);
+                     used[first_unused + j] = true;
+                 }
+                 while (first_unused < graph->n_nodes && used[first_unused]) {
+                     first_unused++;
+                 }
+-                continue;
++                return true;
+             }
++            return false;
++        };
++
++        if (keep_pattern(topk_moe_early_softmax_norm)) {
++            continue;
++        }
++        if (keep_pattern(topk_moe_early_softmax)) {
++            continue;
+         }
++        if (keep_pattern(topk_moe_late_softmax)) {
++            continue;
++        }
++
+         // First, grab the next unused node.
+         current_set.push_back(first_unused);
+ 
+@@ -12790,6 +12870,12 @@ static void ggml_vk_graph_optimize(ggml_backend_t backend, struct ggml_cgraph *
+             if (is_empty(graph->nodes[j])) {
+                 continue;
+             }
++            // Don't pull forward nodes from fusion patterns
++            if (match_pattern(topk_moe_early_softmax_norm, j) ||
++                match_pattern(topk_moe_early_softmax, j) ||
++                match_pattern(topk_moe_late_softmax, j)) {
++                continue;
++            }
+             bool ok = true;
+             for (int c = first_unused; c < j; ++c) {
+                 if (!used[c] &&
+diff --git a/ggml/src/ggml-vulkan/vulkan-shaders/topk_moe.comp b/ggml/src/ggml-vulkan/vulkan-shaders/topk_moe.comp
+index 9e56d5f8a..bc1c278bf 100644
+--- a/ggml/src/ggml-vulkan/vulkan-shaders/topk_moe.comp
++++ b/ggml/src/ggml-vulkan/vulkan-shaders/topk_moe.comp
+@@ -11,6 +11,8 @@ layout (push_constant) uniform parameter
+ {
+     uint n_rows;
+     uint n_expert_used;
++    float clamp_min;
++    float clamp_max;
+ };
+ 
+ layout(local_size_x_id = 0, local_size_y = 4, local_size_z = 1) in;
+@@ -18,6 +20,7 @@ layout(local_size_x_id = 0, local_size_y = 4, local_size_z = 1) in;
+ layout(constant_id = 0) const uint WARP_SIZE = 32;
+ layout(constant_id = 1) const uint n_experts = 512;
+ layout(constant_id = 2) const bool with_norm = true;
++layout(constant_id = 3) const bool late_softmax = false;
+ 
+ const uint experts_per_thread = (n_experts > WARP_SIZE) ? n_experts / WARP_SIZE : 1;
+ 
+@@ -25,53 +28,72 @@ layout (binding = 0, std430) readonly buffer Logits {float logits[];};
+ layout (binding = 1, std430) writeonly buffer Weights {float weights[];};
+ layout (binding = 2, std430) writeonly buffer Ids {uint ids[];};
+ 
+-void main() {
+-    const uint row = gl_WorkGroupID.x * gl_WorkGroupSize.y + gl_LocalInvocationID.y;
+-    if (row >= n_rows) {
+-        return;
+-    }
++const float INFINITY = 1.0 / 0.0;
+ 
+-    const uint logits_offset = n_experts * row;
+-    const uint weights_offset = n_expert_used * row;
+-    const uint ids_offset = n_experts * row;
+-
+-    float logits_r[experts_per_thread];
+-
+-    const float INFINITY = 1.0 / 0.0;
++// Warp-local softmax used for both the pre-top-k logits and the post-top-k delayed path.
++void softmax_warp_inplace(inout float vals[experts_per_thread], const uint limit, const uint lane, const bool use_limit) {
++    float max_val = -INFINITY;
+ 
+     [[unroll]]
+-    for (uint i = 0; i < n_experts; i += WARP_SIZE) {
+-        const uint expert        = i + gl_LocalInvocationID.x;
+-        logits_r[i / WARP_SIZE] = n_experts % WARP_SIZE == 0 || expert < n_experts ? logits[logits_offset + expert] : -INFINITY;
++    for (int i = 0; i < experts_per_thread; i++) {
++        const uint idx       = lane + i * WARP_SIZE;
++        const bool is_active = !use_limit || (idx < limit);
++        if (is_active) {
++            max_val = max(max_val, vals[i]);
++        }
+     }
+ 
+-    float max_val = logits_r[0];
++    max_val = subgroupMax(max_val);
++
++    float sum = 0.f;
+ 
+     [[unroll]]
+-    for (int i = 1; i < experts_per_thread; i++) {
+-        const float val = logits_r[i];
+-        max_val         = max(val, max_val);
++    for (int i = 0; i < experts_per_thread; i++) {
++        const uint idx       = lane + i * WARP_SIZE;
++        const bool is_active = !use_limit || (idx < limit);
++        if (is_active) {
++            const float val = exp(vals[i] - max_val);
++            vals[i]         = val;
++            sum += val;
++        } else {
++            vals[i] = 0.f;
++        }
+     }
+ 
+-    max_val = subgroupMax(max_val);
++    sum = subgroupAdd(sum);
+ 
+-    float wt[experts_per_thread];
+-    float tmp = 0.f;
++    const float inv_sum = 1.0f / sum;
+ 
+     [[unroll]]
+     for (int i = 0; i < experts_per_thread; i++) {
+-        const float val = logits_r[i];
+-        wt[i]           = exp(val - max_val);
+-        tmp += wt[i];
++        const uint idx       = lane + i * WARP_SIZE;
++        const bool is_active = !use_limit || (idx < limit);
++        if (is_active) {
++            vals[i] *= inv_sum;
++        }
+     }
++}
+ 
+-    tmp = subgroupAdd(tmp);
++void main() {
++    const uint row = gl_WorkGroupID.x * gl_WorkGroupSize.y + gl_LocalInvocationID.y;
++    if (row >= n_rows) {
++        return;
++    }
+ 
+-    const float inv_sum = 1.0f / tmp;
++    const uint logits_offset = n_experts * row;
++    const uint weights_offset = n_expert_used * row;
++    const uint ids_offset = n_experts * row;
++
++    float wt[experts_per_thread];
+ 
+     [[unroll]]
+-    for (int i = 0; i < experts_per_thread; i++) {
+-        wt[i] = wt[i] * inv_sum;
++    for (uint i = 0; i < n_experts; i += WARP_SIZE) {
++        const uint expert = i + gl_LocalInvocationID.x;
++        wt[i / WARP_SIZE] = (n_experts % WARP_SIZE == 0 || expert < n_experts) ? logits[logits_offset + expert] : -INFINITY;
++    }
++
++    if (!late_softmax) {
++        softmax_warp_inplace(wt, n_experts, gl_LocalInvocationID.x, false);
+     }
+ 
+     // at this point, each thread holds a portion of softmax,
+@@ -82,6 +104,11 @@ void main() {
+ 
+     float output_weights[experts_per_thread];
+ 
++    [[unroll]]
++    for (int i = 0; i < experts_per_thread; i++) {
++        output_weights[i] = 0.f;
++    }
++
+     for (int k = 0; k < n_expert_used; k++) {
+         float max_val    = wt[0];
+         uint   max_expert = gl_LocalInvocationID.x;
+@@ -121,6 +148,7 @@ void main() {
+ 
+     if (with_norm) {
+         wt_sum              = subgroupAdd(wt_sum);
++        wt_sum              = clamp(wt_sum, clamp_min, clamp_max);
+         const float inv_sum = 1.0f / wt_sum;
+ 
+         [[unroll]]
+@@ -129,6 +157,10 @@ void main() {
+         }
+     }
+ 
++    if (late_softmax) {
++        softmax_warp_inplace(output_weights, n_expert_used, gl_LocalInvocationID.x, true);
++    }
++
+     [[unroll]]
+     for (uint i = 0; i < experts_per_thread; ++i) {
+         uint idx = i * WARP_SIZE + gl_LocalInvocationID.x;
diff --git a/llama/patches/0032-vulkan-Fuse-rope-set_rows-16769.patch b/llama/patches/0032-vulkan-Fuse-rope-set_rows-16769.patch
new file mode 100644
index 00000000..64c7ffa4
--- /dev/null
+++ b/llama/patches/0032-vulkan-Fuse-rope-set_rows-16769.patch
@@ -0,0 +1,1242 @@
+From 0000000000000000000000000000000000000000 Mon Sep 17 00:00:00 2001
+From: Jeff Bolz <jbolz@nvidia.com>
+Date: Wed, 29 Oct 2025 15:13:10 -0500
+Subject: [PATCH] vulkan: Fuse rope+set_rows (#16769)
+
+This pattern appears in a lot of models, the rope operation is applied right
+before storing into the KV cache (usually on the K tensor).
+
+Add a path to some of the rope shaders that computes the destination address
+based on the set_rows tensor. Compile variants of the shader with D_TYPE of
+f16 (the usual KV cache type).
+
+Add a src3 operand to ggml_vk_op_f32 - sometimes rope uses three srcs and needs
+the fourth for the row indices.
+
+Add fused_ops_write_mask to indicate which intermediate tensors need to write
+their results to memory. Skipping writing the roped K value helps to allow more
+nodes to run concurrently.
+
+Add logic to ggml_vk_graph_optimize to make ROPE+VIEW+SET_ROWS consecutive. It
+rarely starts out that way in the graph.
+
+Add new backend tests.
+---
+ ggml/src/ggml-vulkan/ggml-vulkan.cpp          | 334 +++++++++++++-----
+ .../ggml-vulkan/vulkan-shaders/rope_head.glsl |   2 +
+ .../ggml-vulkan/vulkan-shaders/rope_neox.comp |  13 +-
+ .../ggml-vulkan/vulkan-shaders/rope_norm.comp |  13 +-
+ .../vulkan-shaders/vulkan-shaders-gen.cpp     |   4 +
+ tests/test-backend-ops.cpp                    | 122 +++++--
+ 6 files changed, 371 insertions(+), 117 deletions(-)
+
+diff --git a/ggml/src/ggml-vulkan/ggml-vulkan.cpp b/ggml/src/ggml-vulkan/ggml-vulkan.cpp
+index b2855b078..aaf4334b5 100644
+--- a/ggml/src/ggml-vulkan/ggml-vulkan.cpp
++++ b/ggml/src/ggml-vulkan/ggml-vulkan.cpp
+@@ -458,6 +458,11 @@ static topk_moe_mode ggml_vk_num_additional_ops_to_topk_moe_mode(uint32_t num) {
+     return mode;
+ }
+ 
++static constexpr std::initializer_list<std::array<int, 3>> rope_view_set_rows_edges {
++    { 1, 0, 0 }, // view->src[0]     == rope
++    { 2, 0, 1 }, // set_rows->src[0] == view
++};
++
+ struct vk_device_struct {
+     std::recursive_mutex mutex;
+ 
+@@ -640,8 +645,8 @@ struct vk_device_struct {
+     vk_pipeline pipeline_soft_max_f32, pipeline_soft_max_f32_f16;
+     vk_pipeline pipeline_soft_max_f32_wg512, pipeline_soft_max_f32_f16_wg512;
+     vk_pipeline pipeline_soft_max_back_f32;
+-    vk_pipeline pipeline_rope_norm_f32, pipeline_rope_norm_f16;
+-    vk_pipeline pipeline_rope_neox_f32, pipeline_rope_neox_f16;
++    vk_pipeline pipeline_rope_norm_f32, pipeline_rope_norm_f16, pipeline_rope_norm_f32_f16;
++    vk_pipeline pipeline_rope_neox_f32, pipeline_rope_neox_f16, pipeline_rope_neox_f32_f16;
+     vk_pipeline pipeline_rope_multi_f32, pipeline_rope_multi_f16;
+     vk_pipeline pipeline_rope_vision_f32, pipeline_rope_vision_f16;
+     vk_pipeline pipeline_argsort_f32[num_argsort_pipelines];
+@@ -1054,6 +1059,7 @@ struct vk_op_rope_push_constants {
+     uint32_t s2;
+     int32_t sections[4];
+     uint32_t is_back;
++    uint32_t set_rows_stride;
+ };
+ 
+ struct vk_op_soft_max_push_constants {
+@@ -1563,6 +1569,10 @@ struct ggml_backend_vk_context {
+     // number of additional consecutive nodes that are being fused with the
+     // node currently being processed
+     int num_additional_fused_ops {};
++    // Bitmask of which fused ops need to write an intermediate value to memory.
++    // Bit 'i' means nodes[start_of_fusion + i] writes to memory.
++    // If there's no fusion, bit 0 is still set.
++    int fused_ops_write_mask {};
+ };
+ 
+ static void * const vk_ptr_base = (void *)(uintptr_t) 0x1000;  // NOLINT
+@@ -3697,21 +3707,27 @@ static void ggml_vk_load_shaders(vk_device& device) {
+     ggml_vk_create_pipeline(device, device->pipeline_soft_max_f32_f16_wg512, "soft_max_f32_f16_wg512", soft_max_f32_f16_len, soft_max_f32_f16_data, "main", 4, sizeof(vk_op_soft_max_push_constants), {1, 1, 1}, { 512 }, 1);
+     ggml_vk_create_pipeline(device, device->pipeline_soft_max_back_f32, "soft_max_back_f32", soft_max_back_f32_len, soft_max_back_f32_data, "main", 3, sizeof(vk_op_push_constants), {1, 1, 1}, { device->subgroup_size }, 1, true);
+ 
+-    ggml_vk_create_pipeline(device, device->pipeline_rope_norm_f32, "rope_norm_f32", rope_norm_f32_len, rope_norm_f32_data, "main", 4, sizeof(vk_op_rope_push_constants), {1, 512, 1}, {}, 1);
+-    ggml_vk_create_pipeline(device, device->pipeline_rope_neox_f32, "rope_neox_f32", rope_neox_f32_len, rope_neox_f32_data, "main", 4, sizeof(vk_op_rope_push_constants), {1, 512, 1}, {}, 1);
+-    ggml_vk_create_pipeline(device, device->pipeline_rope_multi_f32, "rope_multi_f32", rope_multi_f32_len, rope_multi_f32_data, "main", 4, sizeof(vk_op_rope_push_constants), {1, 512, 1}, {}, 1);
+-    ggml_vk_create_pipeline(device, device->pipeline_rope_vision_f32, "rope_vision_f32", rope_vision_f32_len, rope_vision_f32_data, "main", 4, sizeof(vk_op_rope_push_constants), {1, 512, 1}, {}, 1);
++    ggml_vk_create_pipeline(device, device->pipeline_rope_norm_f32, "rope_norm_f32", rope_norm_f32_len, rope_norm_f32_data, "main", 5, sizeof(vk_op_rope_push_constants), {1, 512, 1}, {}, 1);
++    ggml_vk_create_pipeline(device, device->pipeline_rope_neox_f32, "rope_neox_f32", rope_neox_f32_len, rope_neox_f32_data, "main", 5, sizeof(vk_op_rope_push_constants), {1, 512, 1}, {}, 1);
++    ggml_vk_create_pipeline(device, device->pipeline_rope_multi_f32, "rope_multi_f32", rope_multi_f32_len, rope_multi_f32_data, "main", 5, sizeof(vk_op_rope_push_constants), {1, 512, 1}, {}, 1);
++    ggml_vk_create_pipeline(device, device->pipeline_rope_vision_f32, "rope_vision_f32", rope_vision_f32_len, rope_vision_f32_data, "main", 5, sizeof(vk_op_rope_push_constants), {1, 512, 1}, {}, 1);
+ 
+     if (device->float_controls_rte_fp16) {
+-        ggml_vk_create_pipeline(device, device->pipeline_rope_norm_f16, "rope_norm_f16", rope_norm_f16_rte_len, rope_norm_f16_rte_data, "main", 4, sizeof(vk_op_rope_push_constants), {1, 512, 1}, {}, 1);
+-        ggml_vk_create_pipeline(device, device->pipeline_rope_neox_f16, "rope_neox_f16", rope_neox_f16_rte_len, rope_neox_f16_rte_data, "main", 4, sizeof(vk_op_rope_push_constants), {1, 512, 1}, {}, 1);
+-        ggml_vk_create_pipeline(device, device->pipeline_rope_multi_f16, "rope_multi_f16", rope_multi_f16_rte_len, rope_multi_f16_rte_data, "main", 4, sizeof(vk_op_rope_push_constants), {1, 512, 1}, {}, 1);
+-        ggml_vk_create_pipeline(device, device->pipeline_rope_vision_f16, "rope_vision_f16", rope_vision_f16_rte_len, rope_vision_f16_rte_data, "main", 4, sizeof(vk_op_rope_push_constants), {1, 512, 1}, {}, 1);
++        ggml_vk_create_pipeline(device, device->pipeline_rope_norm_f16, "rope_norm_f16", rope_norm_f16_rte_len, rope_norm_f16_rte_data, "main", 5, sizeof(vk_op_rope_push_constants), {1, 512, 1}, {}, 1);
++        ggml_vk_create_pipeline(device, device->pipeline_rope_neox_f16, "rope_neox_f16", rope_neox_f16_rte_len, rope_neox_f16_rte_data, "main", 5, sizeof(vk_op_rope_push_constants), {1, 512, 1}, {}, 1);
++        ggml_vk_create_pipeline(device, device->pipeline_rope_multi_f16, "rope_multi_f16", rope_multi_f16_rte_len, rope_multi_f16_rte_data, "main", 5, sizeof(vk_op_rope_push_constants), {1, 512, 1}, {}, 1);
++        ggml_vk_create_pipeline(device, device->pipeline_rope_vision_f16, "rope_vision_f16", rope_vision_f16_rte_len, rope_vision_f16_rte_data, "main", 5, sizeof(vk_op_rope_push_constants), {1, 512, 1}, {}, 1);
++
++        ggml_vk_create_pipeline(device, device->pipeline_rope_norm_f32_f16, "rope_norm_f32_f16", rope_norm_f32_f16_rte_len, rope_norm_f32_f16_rte_data, "main", 5, sizeof(vk_op_rope_push_constants), {1, 512, 1}, {}, 1);
++        ggml_vk_create_pipeline(device, device->pipeline_rope_neox_f32_f16, "rope_neox_f32_f16", rope_neox_f32_f16_rte_len, rope_neox_f32_f16_rte_data, "main", 5, sizeof(vk_op_rope_push_constants), {1, 512, 1}, {}, 1);
+     } else {
+-        ggml_vk_create_pipeline(device, device->pipeline_rope_norm_f16, "rope_norm_f16", rope_norm_f16_len, rope_norm_f16_data, "main", 4, sizeof(vk_op_rope_push_constants), {1, 512, 1}, {}, 1);
+-        ggml_vk_create_pipeline(device, device->pipeline_rope_neox_f16, "rope_neox_f16", rope_neox_f16_len, rope_neox_f16_data, "main", 4, sizeof(vk_op_rope_push_constants), {1, 512, 1}, {}, 1);
+-        ggml_vk_create_pipeline(device, device->pipeline_rope_multi_f16, "rope_multi_f16", rope_multi_f16_len, rope_multi_f16_data, "main", 4, sizeof(vk_op_rope_push_constants), {1, 512, 1}, {}, 1);
+-        ggml_vk_create_pipeline(device, device->pipeline_rope_vision_f16, "rope_vision_f16", rope_vision_f16_len, rope_vision_f16_data, "main", 4, sizeof(vk_op_rope_push_constants), {1, 512, 1}, {}, 1);
++        ggml_vk_create_pipeline(device, device->pipeline_rope_norm_f16, "rope_norm_f16", rope_norm_f16_len, rope_norm_f16_data, "main", 5, sizeof(vk_op_rope_push_constants), {1, 512, 1}, {}, 1);
++        ggml_vk_create_pipeline(device, device->pipeline_rope_neox_f16, "rope_neox_f16", rope_neox_f16_len, rope_neox_f16_data, "main", 5, sizeof(vk_op_rope_push_constants), {1, 512, 1}, {}, 1);
++        ggml_vk_create_pipeline(device, device->pipeline_rope_multi_f16, "rope_multi_f16", rope_multi_f16_len, rope_multi_f16_data, "main", 5, sizeof(vk_op_rope_push_constants), {1, 512, 1}, {}, 1);
++        ggml_vk_create_pipeline(device, device->pipeline_rope_vision_f16, "rope_vision_f16", rope_vision_f16_len, rope_vision_f16_data, "main", 5, sizeof(vk_op_rope_push_constants), {1, 512, 1}, {}, 1);
++
++        ggml_vk_create_pipeline(device, device->pipeline_rope_norm_f32_f16, "rope_norm_f32_f16", rope_norm_f32_f16_len, rope_norm_f32_f16_data, "main", 5, sizeof(vk_op_rope_push_constants), {1, 512, 1}, {}, 1);
++        ggml_vk_create_pipeline(device, device->pipeline_rope_neox_f32_f16, "rope_neox_f32_f16", rope_neox_f32_f16_len, rope_neox_f32_f16_data, "main", 5, sizeof(vk_op_rope_push_constants), {1, 512, 1}, {}, 1);
+     }
+ 
+     for (uint32_t i = 0; i < num_argsort_pipelines; ++i) {
+@@ -8170,7 +8186,8 @@ static vk_pipeline ggml_vk_op_get_pipeline(ggml_backend_vk_context * ctx, const
+     case GGML_OP_ROPE:
+     case GGML_OP_ROPE_BACK:
+         {
+-            const int mode = ((const int32_t *) dst->op_params)[2];
++            const ggml_tensor *rope = ctx->num_additional_fused_ops == 2 ? dst->src[0]->src[0] : dst;
++            const int mode = ((const int32_t *) rope->op_params)[2];
+             const bool is_neox = mode & GGML_ROPE_TYPE_NEOX;
+             const bool is_mrope = mode & GGML_ROPE_TYPE_MROPE;
+             const bool is_vision = mode == GGML_ROPE_TYPE_VISION;
+@@ -8179,6 +8196,9 @@ static vk_pipeline ggml_vk_op_get_pipeline(ggml_backend_vk_context * ctx, const
+                 if (src0->type == GGML_TYPE_F32 && dst->type == GGML_TYPE_F32) {
+                     return ctx->device->pipeline_rope_neox_f32;
+                 }
++                if (src0->type == GGML_TYPE_F32 && dst->type == GGML_TYPE_F16) {
++                    return ctx->device->pipeline_rope_neox_f32_f16;
++                }
+                 if (src0->type == GGML_TYPE_F16 && dst->type == GGML_TYPE_F16) {
+                     return ctx->device->pipeline_rope_neox_f16;
+                 }
+@@ -8200,6 +8220,9 @@ static vk_pipeline ggml_vk_op_get_pipeline(ggml_backend_vk_context * ctx, const
+                 if (src0->type == GGML_TYPE_F32 && dst->type == GGML_TYPE_F32) {
+                     return ctx->device->pipeline_rope_norm_f32;
+                 }
++                if (src0->type == GGML_TYPE_F32 && dst->type == GGML_TYPE_F16) {
++                    return ctx->device->pipeline_rope_norm_f32_f16;
++                }
+                 if (src0->type == GGML_TYPE_F16 && dst->type == GGML_TYPE_F16) {
+                     return ctx->device->pipeline_rope_norm_f16;
+                 }
+@@ -8409,20 +8432,22 @@ static uint32_t get_misalign_bytes(ggml_backend_vk_context * ctx, const ggml_ten
+     return ((vk_tensor_offset(t) + t->view_offs) & (ctx->device->properties.limits.minStorageBufferOffsetAlignment - 1));;
+ }
+ 
+-template <typename T> void init_pushconst_tensor_offsets(ggml_backend_vk_context * ctx, T &p, const ggml_tensor * src0, const ggml_tensor * src1, const ggml_tensor * src2, ggml_tensor * dst) {
++template <typename T> void init_pushconst_tensor_offsets(ggml_backend_vk_context * ctx, T &p, const ggml_tensor * src0, const ggml_tensor * src1, const ggml_tensor * src2, const ggml_tensor * src3, ggml_tensor * dst) {
+     GGML_UNUSED(p);
+     GGML_UNUSED(src0);
+     GGML_UNUSED(src1);
+     GGML_UNUSED(src2);
++    GGML_UNUSED(src3);
+     GGML_UNUSED(dst);
+     static_assert(!std::is_const<T>::value, "unexpected type");
+     GGML_ASSERT(!src0 || get_misalign_bytes(ctx, src0) == 0);
+     GGML_ASSERT(!src1 || get_misalign_bytes(ctx, src1) == 0);
+     GGML_ASSERT(!src2 || get_misalign_bytes(ctx, src2) == 0);
++    GGML_ASSERT(!src3 || get_misalign_bytes(ctx, src3) == 0);
+     GGML_ASSERT(!dst  || get_misalign_bytes(ctx, dst) == 0);
+ }
+ 
+-template <> void init_pushconst_tensor_offsets(ggml_backend_vk_context * ctx, vk_op_unary_push_constants &p, const ggml_tensor * src0, const ggml_tensor * src1, const ggml_tensor * src2, ggml_tensor * dst) {
++template <> void init_pushconst_tensor_offsets(ggml_backend_vk_context * ctx, vk_op_unary_push_constants &p, const ggml_tensor * src0, const ggml_tensor * src1, const ggml_tensor * src2, const ggml_tensor * src3, ggml_tensor * dst) {
+     const uint32_t a_offset = get_misalign_bytes(ctx, src0) / ggml_type_size(src0->type);
+     const uint32_t d_offset = get_misalign_bytes(ctx, dst) / ggml_type_size(dst->type);
+ 
+@@ -8430,9 +8455,10 @@ template <> void init_pushconst_tensor_offsets(ggml_backend_vk_context * ctx, vk
+ 
+     GGML_UNUSED(src1);
+     GGML_UNUSED(src2);
++    GGML_UNUSED(src3);
+ }
+ 
+-template <> void init_pushconst_tensor_offsets(ggml_backend_vk_context * ctx, vk_op_sum_rows_push_constants &p, const ggml_tensor * src0, const ggml_tensor * src1, const ggml_tensor * src2, ggml_tensor * dst) {
++template <> void init_pushconst_tensor_offsets(ggml_backend_vk_context * ctx, vk_op_sum_rows_push_constants &p, const ggml_tensor * src0, const ggml_tensor * src1, const ggml_tensor * src2, const ggml_tensor * src3, ggml_tensor * dst) {
+     const uint32_t a_offset = get_misalign_bytes(ctx, src0) / ggml_type_size(src0->type);
+     const uint32_t d_offset = get_misalign_bytes(ctx, dst) / ggml_type_size(dst->type);
+ 
+@@ -8440,9 +8466,10 @@ template <> void init_pushconst_tensor_offsets(ggml_backend_vk_context * ctx, vk
+ 
+     GGML_UNUSED(src1);
+     GGML_UNUSED(src2);
++    GGML_UNUSED(src3);
+ }
+ 
+-template <> void init_pushconst_tensor_offsets(ggml_backend_vk_context * ctx, vk_op_pad_push_constants &p, const ggml_tensor * src0, const ggml_tensor * src1, const ggml_tensor * src2, ggml_tensor * dst) {
++template <> void init_pushconst_tensor_offsets(ggml_backend_vk_context * ctx, vk_op_pad_push_constants &p, const ggml_tensor * src0, const ggml_tensor * src1, const ggml_tensor * src2, const ggml_tensor * src3, ggml_tensor * dst) {
+     const uint32_t a_offset = get_misalign_bytes(ctx, src0) / ggml_type_size(src0->type);
+     const uint32_t d_offset = get_misalign_bytes(ctx, dst) / ggml_type_size(dst->type);
+ 
+@@ -8450,9 +8477,10 @@ template <> void init_pushconst_tensor_offsets(ggml_backend_vk_context * ctx, vk
+ 
+     GGML_UNUSED(src1);
+     GGML_UNUSED(src2);
++    GGML_UNUSED(src3);
+ }
+ 
+-template <> void init_pushconst_tensor_offsets(ggml_backend_vk_context * ctx, vk_op_im2col_3d_push_constants &p, const ggml_tensor * src0, const ggml_tensor * src1, const ggml_tensor * src2, ggml_tensor * dst) {
++template <> void init_pushconst_tensor_offsets(ggml_backend_vk_context * ctx, vk_op_im2col_3d_push_constants &p, const ggml_tensor * src0, const ggml_tensor * src1, const ggml_tensor * src2, const ggml_tensor * src3, ggml_tensor * dst) {
+     const uint32_t a_offset = get_misalign_bytes(ctx, src1) / ggml_type_size(src1->type);
+     const uint32_t d_offset = get_misalign_bytes(ctx, dst) / ggml_type_size(dst->type);
+ 
+@@ -8460,9 +8488,10 @@ template <> void init_pushconst_tensor_offsets(ggml_backend_vk_context * ctx, vk
+ 
+     GGML_UNUSED(src0);
+     GGML_UNUSED(src2);
++    GGML_UNUSED(src3);
+ }
+ 
+-template <> void init_pushconst_tensor_offsets(ggml_backend_vk_context * ctx, vk_op_binary_push_constants &p, const ggml_tensor * src0, const ggml_tensor * src1, const ggml_tensor * src2, ggml_tensor * dst) {
++template <> void init_pushconst_tensor_offsets(ggml_backend_vk_context * ctx, vk_op_binary_push_constants &p, const ggml_tensor * src0, const ggml_tensor * src1, const ggml_tensor * src2, const ggml_tensor * src3, ggml_tensor * dst) {
+     const uint32_t a_offset = get_misalign_bytes(ctx, src0) / ggml_type_size(src0->type);
+     const uint32_t b_offset = get_misalign_bytes(ctx, src1) / ggml_type_size(src1->type);
+     const uint32_t d_offset = get_misalign_bytes(ctx, dst) / ggml_type_size(dst->type);
+@@ -8472,9 +8501,10 @@ template <> void init_pushconst_tensor_offsets(ggml_backend_vk_context * ctx, vk
+     p.misalign_offsets = (a_offset << 16) | (b_offset << 8) | d_offset;
+ 
+     GGML_UNUSED(src2);
++    GGML_UNUSED(src3);
+ }
+ 
+-template <> void init_pushconst_tensor_offsets(ggml_backend_vk_context * ctx, vk_op_upscale_push_constants &p, const ggml_tensor * src0, const ggml_tensor * src1, const ggml_tensor * src2, ggml_tensor * dst) {
++template <> void init_pushconst_tensor_offsets(ggml_backend_vk_context * ctx, vk_op_upscale_push_constants &p, const ggml_tensor * src0, const ggml_tensor * src1, const ggml_tensor * src2, const ggml_tensor * src3, ggml_tensor * dst) {
+     const uint32_t a_offset = get_misalign_bytes(ctx, src0) / ggml_type_size(src0->type);
+     const uint32_t d_offset = get_misalign_bytes(ctx, dst) / ggml_type_size(dst->type);
+ 
+@@ -8483,10 +8513,11 @@ template <> void init_pushconst_tensor_offsets(ggml_backend_vk_context * ctx, vk
+ 
+     GGML_UNUSED(src1);
+     GGML_UNUSED(src2);
++    GGML_UNUSED(src3);
+ }
+ 
+ template<typename PC>
+-static void ggml_vk_op_f32(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, const ggml_tensor * src1, const ggml_tensor * src2, ggml_tensor * dst, ggml_op op, PC&& pc, bool dryrun = false) {
++static void ggml_vk_op_f32(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, const ggml_tensor * src1, const ggml_tensor * src2, const ggml_tensor * src3, ggml_tensor * dst, ggml_op op, PC&& pc, bool dryrun = false) {
+     VK_LOG_DEBUG("ggml_vk_op_f32((" << src0 << ", name=" << src0->name << ", type=" << src0->type << ", ne0=" << src0->ne[0] << ", ne1=" << src0->ne[1] << ", ne2=" << src0->ne[2] << ", ne3=" << src0->ne[3] << ", nb0=" << src0->nb[0] << ", nb1=" << src0->nb[1] << ", nb2=" << src0->nb[2] << ", nb3=" << src0->nb[3];
+     if (src1 != nullptr) {
+         std::cerr << "), (" << src1 << ", name=" << src1->name << ", type=" << src1->type << ", ne0=" << src1->ne[0] << ", ne1=" << src1->ne[1] << ", ne2=" << src1->ne[2] << ", ne3=" << src1->ne[3] << ", nb0=" << src1->nb[0] << ", nb1=" << src1->nb[1] << ", nb2=" << src1->nb[2] << ", nb3=" << src1->nb[3];
+@@ -8494,6 +8525,9 @@ static void ggml_vk_op_f32(ggml_backend_vk_context * ctx, vk_context& subctx, co
+     if (src2 != nullptr) {
+         std::cerr << "), (" << src2 << ", name=" << src2->name << ", type=" << src2->type << ", ne0=" << src2->ne[0] << ", ne1=" << src2->ne[1] << ", ne2=" << src2->ne[2] << ", ne3=" << src2->ne[3] << ", nb0=" << src2->nb[0] << ", nb1=" << src2->nb[1] << ", nb2=" << src2->nb[2] << ", nb3=" << src2->nb[3];
+     }
++    if (src3 != nullptr) {
++        std::cerr << "), (" << src3 << ", name=" << src3->name << ", type=" << src3->type << ", ne0=" << src3->ne[0] << ", ne1=" << src3->ne[1] << ", ne2=" << src3->ne[2] << ", ne3=" << src3->ne[3] << ", nb0=" << src3->nb[0] << ", nb1=" << src3->nb[1] << ", nb2=" << src3->nb[2] << ", nb3=" << src3->nb[3];
++    }
+     std::cerr << "), (" << dst << ", name=" << dst->name << ", type=" << dst->type << ", ne0=" << dst->ne[0] << ", ne1=" << dst->ne[1] << ", ne2=" << dst->ne[2] << ", ne3=" << dst->ne[3] << ", nb0=" << dst->nb[0] << ", nb1=" << dst->nb[1] << ", nb2=" << dst->nb[2] << ", nb3=" << dst->nb[3];
+     std::cerr << "), " << ggml_op_name(op) << ", " << (dryrun ? "dryrun" : "") << ")");
+     GGML_ASSERT(op == GGML_OP_GET_ROWS || op == GGML_OP_CPY || (!ggml_is_quantized(src0->type) && (src1 == nullptr || !ggml_is_quantized(src1->type))));  // NOLINT
+@@ -8520,6 +8554,13 @@ static void ggml_vk_op_f32(ggml_backend_vk_context * ctx, vk_context& subctx, co
+     const uint64_t ne23 = use_src2 ? src2->ne[3] : 0;
+     const uint64_t ne2 = ne20 * ne21;
+ 
++    const bool use_src3 = src3 != nullptr;
++    const uint64_t ne30 = use_src3 ? src3->ne[0] : 0;
++    const uint64_t ne31 = use_src3 ? src3->ne[1] : 0;
++    const uint64_t ne32 = use_src3 ? src3->ne[2] : 0;
++    const uint64_t ne33 = use_src3 ? src3->ne[3] : 0;
++    const uint64_t ne3 = ne30 * ne31;
++
+     const uint64_t ned0 = dst->ne[0];
+     const uint64_t ned1 = dst->ne[1];
+     const uint64_t ned2 = dst->ne[2];
+@@ -8550,6 +8591,7 @@ static void ggml_vk_op_f32(ggml_backend_vk_context * ctx, vk_context& subctx, co
+     ggml_backend_vk_buffer_context * src0_buf_ctx = (ggml_backend_vk_buffer_context *)src0->buffer->context;
+     ggml_backend_vk_buffer_context * src1_buf_ctx = use_src1 ? (ggml_backend_vk_buffer_context *)src1->buffer->context : nullptr;
+     ggml_backend_vk_buffer_context * src2_buf_ctx = use_src2 ? (ggml_backend_vk_buffer_context *)src2->buffer->context : nullptr;
++    ggml_backend_vk_buffer_context * src3_buf_ctx = use_src3 ? (ggml_backend_vk_buffer_context *)src3->buffer->context : nullptr;
+ 
+     vk_buffer d_X = nullptr;
+     size_t x_buf_offset = 0;
+@@ -8557,10 +8599,13 @@ static void ggml_vk_op_f32(ggml_backend_vk_context * ctx, vk_context& subctx, co
+     size_t y_buf_offset = 0;
+     vk_buffer d_Z = nullptr;
+     size_t z_buf_offset = 0;
++    vk_buffer d_W = nullptr;
++    size_t w_buf_offset = 0;
+ 
+     bool src0_uma = false;
+     bool src1_uma = false;
+     bool src2_uma = false;
++    bool src3_uma = false;
+ 
+     if (ctx->device->uma) {
+         ggml_vk_host_get(ctx->device, src0->data, d_X, x_buf_offset);
+@@ -8573,6 +8618,10 @@ static void ggml_vk_op_f32(ggml_backend_vk_context * ctx, vk_context& subctx, co
+             ggml_vk_host_get(ctx->device, src2->data, d_Z, z_buf_offset);
+             src2_uma = d_Z != nullptr;
+         }
++        if (use_src3) {
++            ggml_vk_host_get(ctx->device, src3->data, d_W, w_buf_offset);
++            src3_uma = d_W != nullptr;
++        }
+     }
+ 
+     vk_buffer d_D = dst_buf_ctx->dev_buffer;
+@@ -8594,11 +8643,17 @@ static void ggml_vk_op_f32(ggml_backend_vk_context * ctx, vk_context& subctx, co
+         z_buf_offset = vk_tensor_offset(src2) + src2->view_offs;
+         GGML_ASSERT(d_Z != nullptr);
+     }
++    if (use_src3 && !src3_uma) {
++        d_W = src3_buf_ctx->dev_buffer;
++        w_buf_offset = vk_tensor_offset(src3) + src3->view_offs;
++        GGML_ASSERT(d_W != nullptr);
++    }
+     // Compute misalignment offset for descriptors and store it in in push constants, then align the descriptor offsets.
+-    init_pushconst_tensor_offsets(ctx, pc, src0, src1, src2, dst);
++    init_pushconst_tensor_offsets(ctx, pc, src0, src1, src2, src3, dst);
+     x_buf_offset &= ~(ctx->device->properties.limits.minStorageBufferOffsetAlignment - 1);
+     y_buf_offset &= ~(ctx->device->properties.limits.minStorageBufferOffsetAlignment - 1);
+     z_buf_offset &= ~(ctx->device->properties.limits.minStorageBufferOffsetAlignment - 1);
++    w_buf_offset &= ~(ctx->device->properties.limits.minStorageBufferOffsetAlignment - 1);
+     d_buf_offset &= ~(ctx->device->properties.limits.minStorageBufferOffsetAlignment - 1);
+ 
+     std::array<uint32_t, 3> elements;
+@@ -8799,12 +8854,13 @@ static void ggml_vk_op_f32(ggml_backend_vk_context * ctx, vk_context& subctx, co
+         break;
+     }
+ 
+-    uint64_t x_sz, y_sz, z_sz, d_sz;
++    uint64_t x_sz, y_sz, z_sz, w_sz, d_sz;
+ 
+     if (op_supports_incontiguous) {
+         x_sz = ggml_nbytes(src0) + get_misalign_bytes(ctx, src0);
+         y_sz = use_src1 ? ggml_nbytes(src1) + get_misalign_bytes(ctx, src1) : 0;
+         z_sz = use_src2 ? ggml_nbytes(src2) + get_misalign_bytes(ctx, src2) : 0;
++        w_sz = use_src3 ? ggml_nbytes(src3) + get_misalign_bytes(ctx, src3) : 0;
+         d_sz = ggml_nbytes(dst) + get_misalign_bytes(ctx, dst);
+ 
+         if (x_buf_offset + x_sz >= d_X->size) {
+@@ -8816,6 +8872,9 @@ static void ggml_vk_op_f32(ggml_backend_vk_context * ctx, vk_context& subctx, co
+         if (use_src2 && z_buf_offset + z_sz >= d_Z->size) {
+             z_sz = ggml_vk_get_max_buffer_range(ctx, d_Z, z_buf_offset);
+         }
++        if (use_src3 && w_buf_offset + w_sz >= d_W->size) {
++            w_sz = ggml_vk_get_max_buffer_range(ctx, d_W, w_buf_offset);
++        }
+         if (d_buf_offset + d_sz >= d_D->size) {
+             d_sz = ggml_vk_get_max_buffer_range(ctx, d_D, d_buf_offset);
+         }
+@@ -8823,6 +8882,7 @@ static void ggml_vk_op_f32(ggml_backend_vk_context * ctx, vk_context& subctx, co
+         x_sz = ggml_type_size(src0->type)/ggml_blck_size(src0->type) * ne0 * ne02 * ne03;
+         y_sz = use_src1 ? ggml_type_size(src1->type) * ne1 * ne12 * ne13 : 0;
+         z_sz = use_src2 ? ggml_type_size(src2->type) * ne2 * ne22 * ne23 : 0;
++        w_sz = use_src3 ? ggml_type_size(src3->type) * ne3 * ne32 * ne33 : 0;
+         d_sz = ggml_type_size(dst->type) * ned * ned2 * ned3;
+     }
+ 
+@@ -8864,14 +8924,19 @@ static void ggml_vk_op_f32(ggml_backend_vk_context * ctx, vk_context& subctx, co
+         ggml_vk_dispatch_pipeline(ctx, subctx, pipeline, { vk_subbuffer{ d_X, x_buf_offset, x_sz }, subbuf_y, subbuf_z, vk_subbuffer{ d_D, d_buf_offset, d_sz } }, pc, elements);
+     } else if (op == GGML_OP_ROPE || op == GGML_OP_ROPE_BACK) {
+         // Empty src2 is possible in rope, but the shader needs a buffer
+-        vk_subbuffer subbuf_z;
++        vk_subbuffer subbuf_z, subbuf_w;
+         if (use_src2) {
+             subbuf_z = { d_Z, z_buf_offset, z_sz };
+         } else {
+             subbuf_z = { d_X, 0, x_sz };
+         }
++        if (use_src3) {
++            subbuf_w = { d_W, w_buf_offset, w_sz };
++        } else {
++            subbuf_w = { d_X, 0, x_sz };
++        }
+ 
+-        ggml_vk_dispatch_pipeline(ctx, subctx, pipeline, { vk_subbuffer{ d_X, x_buf_offset, x_sz }, vk_subbuffer{ d_Y, y_buf_offset, y_sz }, subbuf_z, vk_subbuffer{ d_D, d_buf_offset, d_sz } }, pc, elements);
++        ggml_vk_dispatch_pipeline(ctx, subctx, pipeline, { vk_subbuffer{ d_X, x_buf_offset, x_sz }, vk_subbuffer{ d_Y, y_buf_offset, y_sz }, subbuf_z, vk_subbuffer{ d_D, d_buf_offset, d_sz }, subbuf_w }, pc, elements);
+     } else if (op == GGML_OP_IM2COL || op == GGML_OP_IM2COL_3D) {
+         if (ctx->device->shader_int64 && ctx->device->buffer_device_address) {
+             // buffer device address path doesn't use dst buffer
+@@ -8887,6 +8952,8 @@ static void ggml_vk_op_f32(ggml_backend_vk_context * ctx, vk_context& subctx, co
+     } else if (op == GGML_OP_OPT_STEP_SGD) {
+         // OPT_STEP_SGD works on src0, it does not need dst
+         ggml_vk_dispatch_pipeline(ctx, subctx, pipeline, { vk_subbuffer{ d_X, x_buf_offset, x_sz }, vk_subbuffer{ d_Y, y_buf_offset, y_sz }, vk_subbuffer{ d_Z, z_buf_offset, z_sz } }, pc, elements);
++    } else if (use_src3) {
++        ggml_vk_dispatch_pipeline(ctx, subctx, pipeline, { vk_subbuffer{ d_X, x_buf_offset, x_sz }, vk_subbuffer{ d_Y, y_buf_offset, y_sz }, vk_subbuffer{ d_Z, z_buf_offset, z_sz }, vk_subbuffer{ d_W, w_buf_offset, w_sz }, vk_subbuffer{ d_D, d_buf_offset, d_sz } }, pc, elements);
+     } else if (use_src2) {
+         ggml_vk_dispatch_pipeline(ctx, subctx, pipeline, { vk_subbuffer{ d_X, x_buf_offset, x_sz }, vk_subbuffer{ d_Y, y_buf_offset, y_sz }, vk_subbuffer{ d_Z, z_buf_offset, z_sz }, vk_subbuffer{ d_D, d_buf_offset, d_sz } }, pc, elements);
+     } else if (use_src1) {
+@@ -8901,7 +8968,7 @@ static void ggml_vk_get_rows(ggml_backend_vk_context * ctx, vk_context& subctx,
+     const uint32_t src1_type_size = ggml_type_size(src1->type);
+     const uint32_t dst_type_size = ggml_type_size(dst->type);
+ 
+-    ggml_vk_op_f32<vk_op_binary_push_constants>(ctx, subctx, src0, src1, nullptr, dst, GGML_OP_GET_ROWS, {
++    ggml_vk_op_f32<vk_op_binary_push_constants>(ctx, subctx, src0, src1, nullptr, nullptr, dst, GGML_OP_GET_ROWS, {
+         (uint32_t)ggml_nelements(src0),
+         (uint32_t)src0->ne[0], (uint32_t)src0->ne[1], (uint32_t)src0->ne[2],(uint32_t)src0->ne[3], (uint32_t)src0->nb[0] / src0_type_size, (uint32_t)src0->nb[1] / src0_type_size, (uint32_t)src0->nb[2] / src0_type_size, (uint32_t)src0->nb[3] / src0_type_size,
+         (uint32_t)src1->ne[0], (uint32_t)src1->ne[1], (uint32_t)src1->ne[2],(uint32_t)src1->ne[3], (uint32_t)src1->nb[0] / src1_type_size, (uint32_t)src1->nb[1] / src1_type_size, (uint32_t)src1->nb[2] / src1_type_size, (uint32_t)src1->nb[3] / src1_type_size,
+@@ -8921,7 +8988,7 @@ static void ggml_vk_acc(ggml_backend_vk_context * ctx, vk_context& subctx, const
+     // int nb3 = dst->op_params[2] / 4; // 4 bytes of float32 - unused
+     int offset = dst->op_params[3] / 4; // offset in bytes
+ 
+-    ggml_vk_op_f32<vk_op_binary_push_constants>(ctx, subctx, src0, src1, nullptr, dst, GGML_OP_ACC, {
++    ggml_vk_op_f32<vk_op_binary_push_constants>(ctx, subctx, src0, src1, nullptr, nullptr, dst, GGML_OP_ACC, {
+         (uint32_t)ggml_nelements(src0),
+         (uint32_t)src0->ne[0], (uint32_t)src0->ne[1], (uint32_t)src0->ne[2],(uint32_t)src0->ne[3], (uint32_t)src0->nb[0] / src0_type_size, (uint32_t)nb1, (uint32_t)nb2, (uint32_t)src0->nb[3] / src0_type_size,
+         (uint32_t)src1->ne[0], (uint32_t)src1->ne[1], (uint32_t)src1->ne[2],(uint32_t)src1->ne[3], (uint32_t)src1->nb[0] / src1_type_size, (uint32_t)src1->nb[1] / src1_type_size, (uint32_t)src1->nb[2] / src1_type_size, (uint32_t)src1->nb[3] / src1_type_size,
+@@ -9046,7 +9113,7 @@ static void ggml_vk_add(ggml_backend_vk_context * ctx, vk_context& subctx, const
+     const uint32_t src1_type_size = ggml_type_size(src1->type);
+     const uint32_t dst_type_size = ggml_type_size(dst->type);
+ 
+-    ggml_vk_op_f32<vk_op_binary_push_constants>(ctx, subctx, src0, src1, nullptr, dst, GGML_OP_ADD, {
++    ggml_vk_op_f32<vk_op_binary_push_constants>(ctx, subctx, src0, src1, nullptr, nullptr, dst, GGML_OP_ADD, {
+         (uint32_t)ggml_nelements(src0),
+         (uint32_t)src0->ne[0], (uint32_t)src0->ne[1], (uint32_t)src0->ne[2],(uint32_t)src0->ne[3], (uint32_t)src0->nb[0] / src0_type_size, (uint32_t)src0->nb[1] / src0_type_size, (uint32_t)src0->nb[2] / src0_type_size, (uint32_t)src0->nb[3] / src0_type_size,
+         (uint32_t)src1->ne[0], (uint32_t)src1->ne[1], (uint32_t)src1->ne[2],(uint32_t)src1->ne[3], (uint32_t)src1->nb[0] / src1_type_size, (uint32_t)src1->nb[1] / src1_type_size, (uint32_t)src1->nb[2] / src1_type_size, (uint32_t)src1->nb[3] / src1_type_size,
+@@ -9061,7 +9128,7 @@ static void ggml_vk_sub(ggml_backend_vk_context * ctx, vk_context& subctx, const
+     const uint32_t src1_type_size = ggml_type_size(src1->type);
+     const uint32_t dst_type_size = ggml_type_size(dst->type);
+ 
+-    ggml_vk_op_f32<vk_op_binary_push_constants>(ctx, subctx, src0, src1, nullptr, dst, GGML_OP_SUB, {
++    ggml_vk_op_f32<vk_op_binary_push_constants>(ctx, subctx, src0, src1, nullptr, nullptr, dst, GGML_OP_SUB, {
+         (uint32_t)ggml_nelements(src0),
+         (uint32_t)src0->ne[0], (uint32_t)src0->ne[1], (uint32_t)src0->ne[2],(uint32_t)src0->ne[3], (uint32_t)src0->nb[0] / src0_type_size, (uint32_t)src0->nb[1] / src0_type_size, (uint32_t)src0->nb[2] / src0_type_size, (uint32_t)src0->nb[3] / src0_type_size,
+         (uint32_t)src1->ne[0], (uint32_t)src1->ne[1], (uint32_t)src1->ne[2],(uint32_t)src1->ne[3], (uint32_t)src1->nb[0] / src1_type_size, (uint32_t)src1->nb[1] / src1_type_size, (uint32_t)src1->nb[2] / src1_type_size, (uint32_t)src1->nb[3] / src1_type_size,
+@@ -9076,7 +9143,7 @@ static void ggml_vk_mul(ggml_backend_vk_context * ctx, vk_context& subctx, const
+     const uint32_t src1_type_size = ggml_type_size(src1->type);
+     const uint32_t dst_type_size = ggml_type_size(dst->type);
+ 
+-    ggml_vk_op_f32<vk_op_binary_push_constants>(ctx, subctx, src0, src1, nullptr, dst, GGML_OP_MUL, {
++    ggml_vk_op_f32<vk_op_binary_push_constants>(ctx, subctx, src0, src1, nullptr, nullptr, dst, GGML_OP_MUL, {
+         (uint32_t)ggml_nelements(src0),
+         (uint32_t)src0->ne[0], (uint32_t)src0->ne[1], (uint32_t)src0->ne[2],(uint32_t)src0->ne[3], (uint32_t)src0->nb[0] / src0_type_size, (uint32_t)src0->nb[1] / src0_type_size, (uint32_t)src0->nb[2] / src0_type_size, (uint32_t)src0->nb[3] / src0_type_size,
+         (uint32_t)src1->ne[0], (uint32_t)src1->ne[1], (uint32_t)src1->ne[2],(uint32_t)src1->ne[3], (uint32_t)src1->nb[0] / src1_type_size, (uint32_t)src1->nb[1] / src1_type_size, (uint32_t)src1->nb[2] / src1_type_size, (uint32_t)src1->nb[3] / src1_type_size,
+@@ -9091,7 +9158,7 @@ static void ggml_vk_div(ggml_backend_vk_context * ctx, vk_context& subctx, const
+     const uint32_t src1_type_size = ggml_type_size(src1->type);
+     const uint32_t dst_type_size = ggml_type_size(dst->type);
+ 
+-    ggml_vk_op_f32<vk_op_binary_push_constants>(ctx, subctx, src0, src1, nullptr, dst, GGML_OP_DIV, {
++    ggml_vk_op_f32<vk_op_binary_push_constants>(ctx, subctx, src0, src1, nullptr, nullptr, dst, GGML_OP_DIV, {
+         (uint32_t)ggml_nelements(src0),
+         (uint32_t)src0->ne[0], (uint32_t)src0->ne[1], (uint32_t)src0->ne[2],(uint32_t)src0->ne[3], (uint32_t)src0->nb[0] / src0_type_size, (uint32_t)src0->nb[1] / src0_type_size, (uint32_t)src0->nb[2] / src0_type_size, (uint32_t)src0->nb[3] / src0_type_size,
+         (uint32_t)src1->ne[0], (uint32_t)src1->ne[1], (uint32_t)src1->ne[2],(uint32_t)src1->ne[3], (uint32_t)src1->nb[0] / src1_type_size, (uint32_t)src1->nb[1] / src1_type_size, (uint32_t)src1->nb[2] / src1_type_size, (uint32_t)src1->nb[3] / src1_type_size,
+@@ -9106,7 +9173,7 @@ static void ggml_vk_add_id(ggml_backend_vk_context * ctx, vk_context& subctx, co
+     const uint32_t src1_type_size = ggml_type_size(src1->type);
+     const uint32_t src2_type_size = ggml_type_size(src2->type);
+ 
+-    ggml_vk_op_f32<vk_op_add_id_push_constants>(ctx, subctx, src0, src1, src2, dst, GGML_OP_ADD_ID, {
++    ggml_vk_op_f32<vk_op_add_id_push_constants>(ctx, subctx, src0, src1, src2, nullptr, dst, GGML_OP_ADD_ID, {
+         (uint32_t)dst->ne[0],
+         (uint32_t)dst->ne[1],
+         (uint32_t)src0->nb[1] / src0_type_size,
+@@ -9339,7 +9406,7 @@ static void ggml_vk_ssm_conv(ggml_backend_vk_context * ctx, vk_context& subctx,
+     const ggml_tensor * src0 = dst->src[0];
+     const ggml_tensor * src1 = dst->src[1];
+ 
+-    ggml_vk_op_f32<vk_op_ssm_conv_push_constants>(ctx, subctx, src0, src1, nullptr, dst, GGML_OP_SSM_CONV, {
++    ggml_vk_op_f32<vk_op_ssm_conv_push_constants>(ctx, subctx, src0, src1, nullptr, nullptr, dst, GGML_OP_SSM_CONV, {
+         (uint32_t)src0->nb[1], (uint32_t)src0->nb[2],
+         (uint32_t)src1->nb[1],
+         (uint32_t)dst->nb[0], (uint32_t)dst->nb[1], (uint32_t)dst->nb[2],
+@@ -9457,7 +9524,7 @@ static void ggml_vk_opt_step_adamw(ggml_backend_vk_context * ctx, vk_context& su
+ static void ggml_vk_opt_step_sgd(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, const ggml_tensor * src1, const ggml_tensor * src2, ggml_tensor * dst, bool dryrun = false) {
+     const size_t n = ggml_nelements(dst->src[0]);
+ 
+-    ggml_vk_op_f32<vk_op_push_constants>(ctx, subctx, src0, src1, src2, dst, GGML_OP_OPT_STEP_SGD, { (uint32_t)n, 0, 0.0f, 0.0f }, dryrun);
++    ggml_vk_op_f32<vk_op_push_constants>(ctx, subctx, src0, src1, src2, nullptr, dst, GGML_OP_OPT_STEP_SGD, { (uint32_t)n, 0, 0.0f, 0.0f }, dryrun);
+ }
+ 
+ static void ggml_vk_concat(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst, bool dryrun = false) {
+@@ -9467,7 +9534,7 @@ static void ggml_vk_concat(ggml_backend_vk_context * ctx, vk_context& subctx, co
+     const uint32_t src1_type_size = ggml_type_size(src1->type);
+     const uint32_t dst_type_size = ggml_type_size(dst->type);
+ 
+-    ggml_vk_op_f32<vk_op_binary_push_constants>(ctx, subctx, src0, src1, nullptr, dst, GGML_OP_CONCAT, {
++    ggml_vk_op_f32<vk_op_binary_push_constants>(ctx, subctx, src0, src1, nullptr, nullptr, dst, GGML_OP_CONCAT, {
+         (uint32_t)ggml_nelements(dst),
+         (uint32_t)src0->ne[0], (uint32_t)src0->ne[1], (uint32_t)src0->ne[2],(uint32_t)src0->ne[3], (uint32_t)src0->nb[0] / src0_type_size, (uint32_t)src0->nb[1] / src0_type_size, (uint32_t)src0->nb[2] / src0_type_size, (uint32_t)src0->nb[3] / src0_type_size,
+         (uint32_t)src1->ne[0], (uint32_t)src1->ne[1], (uint32_t)src1->ne[2],(uint32_t)src1->ne[3], (uint32_t)src1->nb[0] / src1_type_size, (uint32_t)src1->nb[1] / src1_type_size, (uint32_t)src1->nb[2] / src1_type_size, (uint32_t)src1->nb[3] / src1_type_size,
+@@ -9491,7 +9558,7 @@ static void ggml_vk_upscale(ggml_backend_vk_context * ctx, vk_context& subctx, c
+         sf1 = (float)(dst->ne[1] - 1) / (src0->ne[1] - 1);
+     }
+ 
+-    ggml_vk_op_f32<vk_op_upscale_push_constants>(ctx, subctx, src0, nullptr, nullptr, dst, GGML_OP_UPSCALE, {
++    ggml_vk_op_f32<vk_op_upscale_push_constants>(ctx, subctx, src0, nullptr, nullptr, nullptr, dst, GGML_OP_UPSCALE, {
+         (uint32_t)ggml_nelements(dst), 0, 0,
+         (uint32_t)src0->ne[0], (uint32_t)src0->ne[1],
+         (uint32_t)src0->nb[0] / src0_type_size, (uint32_t)src0->nb[1] / src0_type_size, (uint32_t)src0->nb[2] / src0_type_size, (uint32_t)src0->nb[3] / src0_type_size,
+@@ -9505,23 +9572,23 @@ static void ggml_vk_scale(ggml_backend_vk_context * ctx, vk_context& subctx, con
+     p.param1 = ggml_get_op_params_f32(dst, 0);
+     p.param2 = ggml_get_op_params_f32(dst, 1);
+ 
+-    ggml_vk_op_f32(ctx, subctx, src0, nullptr, nullptr, dst, GGML_OP_SCALE, std::move(p), dryrun);
++    ggml_vk_op_f32(ctx, subctx, src0, nullptr, nullptr, nullptr, dst, GGML_OP_SCALE, std::move(p), dryrun);
+ }
+ 
+ static void ggml_vk_sqr(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, ggml_tensor * dst, bool dryrun = false) {
+-    ggml_vk_op_f32(ctx, subctx, src0, nullptr, nullptr, dst, GGML_OP_SQR, vk_op_unary_push_constants_init(src0, dst), dryrun);
++    ggml_vk_op_f32(ctx, subctx, src0, nullptr, nullptr, nullptr, dst, GGML_OP_SQR, vk_op_unary_push_constants_init(src0, dst), dryrun);
+ }
+ 
+ static void ggml_vk_sqrt(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, ggml_tensor * dst, bool dryrun = false) {
+-    ggml_vk_op_f32(ctx, subctx, src0, nullptr, nullptr, dst, GGML_OP_SQRT, vk_op_unary_push_constants_init(src0, dst), dryrun);
++    ggml_vk_op_f32(ctx, subctx, src0, nullptr, nullptr, nullptr, dst, GGML_OP_SQRT, vk_op_unary_push_constants_init(src0, dst), dryrun);
+ }
+ 
+ static void ggml_vk_sin(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, ggml_tensor * dst, bool dryrun = false) {
+-    ggml_vk_op_f32(ctx, subctx, src0, nullptr, nullptr, dst, GGML_OP_SIN, vk_op_unary_push_constants_init(src0, dst), dryrun);
++    ggml_vk_op_f32(ctx, subctx, src0, nullptr, nullptr, nullptr, dst, GGML_OP_SIN, vk_op_unary_push_constants_init(src0, dst), dryrun);
+ }
+ 
+ static void ggml_vk_cos(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, ggml_tensor * dst, bool dryrun = false) {
+-    ggml_vk_op_f32(ctx, subctx, src0, nullptr, nullptr, dst, GGML_OP_COS, vk_op_unary_push_constants_init(src0, dst), dryrun);
++    ggml_vk_op_f32(ctx, subctx, src0, nullptr, nullptr, nullptr, dst, GGML_OP_COS, vk_op_unary_push_constants_init(src0, dst), dryrun);
+ }
+ 
+ static void ggml_vk_clamp(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, ggml_tensor * dst, bool dryrun = false) {
+@@ -9529,12 +9596,12 @@ static void ggml_vk_clamp(ggml_backend_vk_context * ctx, vk_context& subctx, con
+     p.param1 = ggml_get_op_params_f32(dst, 0);
+     p.param2 = ggml_get_op_params_f32(dst, 1);
+ 
+-    ggml_vk_op_f32(ctx, subctx, src0, nullptr, nullptr, dst, GGML_OP_CLAMP, std::move(p), dryrun);
++    ggml_vk_op_f32(ctx, subctx, src0, nullptr, nullptr, nullptr, dst, GGML_OP_CLAMP, std::move(p), dryrun);
+ }
+ 
+ static void ggml_vk_pad(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, ggml_tensor * dst, bool dryrun = false) {
+     vk_op_pad_push_constants p = vk_op_pad_push_constants_init(src0, dst);
+-    ggml_vk_op_f32(ctx, subctx, src0, nullptr, nullptr, dst, GGML_OP_PAD, std::move(p), dryrun);
++    ggml_vk_op_f32(ctx, subctx, src0, nullptr, nullptr, nullptr, dst, GGML_OP_PAD, std::move(p), dryrun);
+ }
+ 
+ static void ggml_vk_roll(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, ggml_tensor * dst, bool dryrun = false) {
+@@ -9549,17 +9616,17 @@ static void ggml_vk_roll(ggml_backend_vk_context * ctx, vk_context& subctx, cons
+     memcpy(&p.param1, &s01_packed, sizeof(float));
+     memcpy(&p.param2, &s23_packed, sizeof(float));
+ 
+-    ggml_vk_op_f32(ctx, subctx, src0, nullptr, nullptr, dst, GGML_OP_ROLL, std::move(p), dryrun);
++    ggml_vk_op_f32(ctx, subctx, src0, nullptr, nullptr, nullptr, dst, GGML_OP_ROLL, std::move(p), dryrun);
+ }
+ 
+ static void ggml_vk_repeat(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, ggml_tensor * dst, bool dryrun = false) {
+     vk_op_unary_push_constants p = vk_op_unary_push_constants_init(src0, dst, ggml_nelements(dst));
+-    ggml_vk_op_f32(ctx, subctx, src0, nullptr, nullptr, dst, GGML_OP_REPEAT, std::move(p), dryrun);
++    ggml_vk_op_f32(ctx, subctx, src0, nullptr, nullptr, nullptr, dst, GGML_OP_REPEAT, std::move(p), dryrun);
+ }
+ 
+ static void ggml_vk_repeat_back(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, ggml_tensor * dst, bool dryrun = false) {
+     vk_op_unary_push_constants p = vk_op_unary_push_constants_init(src0, dst, ggml_nelements(dst));
+-    ggml_vk_op_f32(ctx, subctx, src0, nullptr, nullptr, dst, GGML_OP_REPEAT_BACK, std::move(p), dryrun);
++    ggml_vk_op_f32(ctx, subctx, src0, nullptr, nullptr, nullptr, dst, GGML_OP_REPEAT_BACK, std::move(p), dryrun);
+ }
+ 
+ static void ggml_vk_cpy(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, ggml_tensor * dst, bool dryrun = false) {
+@@ -9575,7 +9642,7 @@ static void ggml_vk_cpy(ggml_backend_vk_context * ctx, vk_context& subctx, const
+     }
+ 
+     vk_op_unary_push_constants p = vk_op_unary_push_constants_init(src0, dst, ne);
+-    ggml_vk_op_f32(ctx, subctx, src0, nullptr, nullptr, dst, GGML_OP_CPY, std::move(p), dryrun);
++    ggml_vk_op_f32(ctx, subctx, src0, nullptr, nullptr, nullptr, dst, GGML_OP_CPY, std::move(p), dryrun);
+ }
+ 
+ static void ggml_vk_set_rows(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst, bool dryrun = false) {
+@@ -9590,7 +9657,7 @@ static void ggml_vk_set_rows(ggml_backend_vk_context * ctx, vk_context& subctx,
+         return;
+     }
+ 
+-    ggml_vk_op_f32<vk_op_binary_push_constants>(ctx, subctx, src0, src1, nullptr, dst, GGML_OP_SET_ROWS, {
++    ggml_vk_op_f32<vk_op_binary_push_constants>(ctx, subctx, src0, src1, nullptr, nullptr, dst, GGML_OP_SET_ROWS, {
+         (uint32_t)ggml_nelements(src0),
+         (uint32_t)src0->ne[0], (uint32_t)src0->ne[1], (uint32_t)src0->ne[2],(uint32_t)src0->ne[3], (uint32_t)src0->nb[0] / src0_type_size, (uint32_t)src0->nb[1] / src0_type_size, (uint32_t)src0->nb[2] / src0_type_size, (uint32_t)src0->nb[3] / src0_type_size,
+         (uint32_t)src1->ne[0], (uint32_t)src1->ne[1], (uint32_t)src1->ne[2],(uint32_t)src1->ne[3], (uint32_t)src1->nb[0] / src1_type_size, (uint32_t)src1->nb[1] / src1_type_size, (uint32_t)src1->nb[2] / src1_type_size, (uint32_t)src1->nb[3] / src1_type_size,
+@@ -9601,13 +9668,13 @@ static void ggml_vk_set_rows(ggml_backend_vk_context * ctx, vk_context& subctx,
+ }
+ 
+ static void ggml_vk_silu_back(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst, bool dryrun = false) {
+-    ggml_vk_op_f32<vk_op_push_constants>(ctx, subctx, src0, src1, nullptr, dst, GGML_OP_SILU_BACK, { (uint32_t)ggml_nelements(src0), 0, 0.0f, 0.0f }, dryrun);
++    ggml_vk_op_f32<vk_op_push_constants>(ctx, subctx, src0, src1, nullptr, nullptr, dst, GGML_OP_SILU_BACK, { (uint32_t)ggml_nelements(src0), 0, 0.0f, 0.0f }, dryrun);
+ }
+ 
+ static void ggml_vk_norm(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, ggml_tensor * dst, bool dryrun = false) {
+     float * op_params = (float *)dst->op_params;
+ 
+-    ggml_vk_op_f32<vk_op_push_constants>(ctx, subctx, src0, nullptr, nullptr, dst, GGML_OP_NORM, { (uint32_t)src0->ne[0], (uint32_t)src0->ne[1], op_params[0], 0.0f }, dryrun);
++    ggml_vk_op_f32<vk_op_push_constants>(ctx, subctx, src0, nullptr, nullptr, nullptr, dst, GGML_OP_NORM, { (uint32_t)src0->ne[0], (uint32_t)src0->ne[1], op_params[0], 0.0f }, dryrun);
+ }
+ 
+ static void ggml_vk_group_norm(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, ggml_tensor * dst, bool dryrun = false) {
+@@ -9618,7 +9685,7 @@ static void ggml_vk_group_norm(ggml_backend_vk_context * ctx, vk_context& subctx
+     const float eps = float_op_params[1];
+     const uint32_t group_size = src0->ne[0] * src0->ne[1] * ((src0->ne[2] + num_groups - 1) / num_groups);
+ 
+-    ggml_vk_op_f32<vk_op_push_constants>(ctx, subctx, src0, nullptr, nullptr, dst, GGML_OP_GROUP_NORM, { group_size, 0, eps, 0.0f }, dryrun);
++    ggml_vk_op_f32<vk_op_push_constants>(ctx, subctx, src0, nullptr, nullptr, nullptr, dst, GGML_OP_GROUP_NORM, { group_size, 0, eps, 0.0f }, dryrun);
+ }
+ 
+ static uint32_t ggml_vk_rms_num_partials(ggml_backend_vk_context * ctx, const ggml_tensor *node) {
+@@ -9641,7 +9708,7 @@ static void ggml_vk_rms_norm(ggml_backend_vk_context * ctx, vk_context& subctx,
+ 
+     uint32_t param3 = ctx->do_add_rms_partials ? ggml_vk_rms_num_partials(ctx, dst) : 0;
+ 
+-    ggml_vk_op_f32<vk_op_binary_push_constants>(ctx, subctx, src0, src1, nullptr, dst, GGML_OP_RMS_NORM, {
++    ggml_vk_op_f32<vk_op_binary_push_constants>(ctx, subctx, src0, src1, nullptr, nullptr, dst, GGML_OP_RMS_NORM, {
+         (uint32_t)ggml_nelements(src0),
+         (uint32_t)src0->ne[0], (uint32_t)src0->ne[1], (uint32_t)src0->ne[2],(uint32_t)src0->ne[3], (uint32_t)src0->nb[0] / src0_type_size, (uint32_t)src0->nb[1] / src0_type_size, (uint32_t)src0->nb[2] / src0_type_size, (uint32_t)src0->nb[3] / src0_type_size,
+         (uint32_t)src1->ne[0], (uint32_t)src1->ne[1], (uint32_t)src1->ne[2],(uint32_t)src1->ne[3], (uint32_t)src1->nb[0] / src1_type_size, (uint32_t)src1->nb[1] / src1_type_size, (uint32_t)src1->nb[2] / src1_type_size, (uint32_t)src1->nb[3] / src1_type_size,
+@@ -9658,16 +9725,16 @@ static void ggml_vk_rms_norm(ggml_backend_vk_context * ctx, vk_context& subctx,
+ 
+ static void ggml_vk_rms_norm_back(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst, bool dryrun = false) {
+     float * op_params = (float *)dst->op_params;
+-    ggml_vk_op_f32<vk_op_push_constants>(ctx, subctx, src0, src1, nullptr, dst, GGML_OP_RMS_NORM_BACK, { (uint32_t)src0->ne[0], (uint32_t)src0->ne[1], op_params[0], 0.0f }, dryrun);
++    ggml_vk_op_f32<vk_op_push_constants>(ctx, subctx, src0, src1, nullptr, nullptr, dst, GGML_OP_RMS_NORM_BACK, { (uint32_t)src0->ne[0], (uint32_t)src0->ne[1], op_params[0], 0.0f }, dryrun);
+ }
+ 
+ static void ggml_vk_l2_norm(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, ggml_tensor * dst, bool dryrun = false) {
+     float * op_params = (float *)dst->op_params;
+-    ggml_vk_op_f32<vk_op_push_constants>(ctx, subctx, src0, nullptr, nullptr, dst, GGML_OP_L2_NORM, { (uint32_t)src0->ne[0], (uint32_t)src0->ne[1], op_params[0], 0.0f }, dryrun);
++    ggml_vk_op_f32<vk_op_push_constants>(ctx, subctx, src0, nullptr, nullptr, nullptr, dst, GGML_OP_L2_NORM, { (uint32_t)src0->ne[0], (uint32_t)src0->ne[1], op_params[0], 0.0f }, dryrun);
+ }
+ 
+ static void ggml_vk_unary(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, ggml_tensor * dst, bool dryrun = false) {
+-    ggml_vk_op_f32<vk_op_push_constants>(ctx, subctx, src0, nullptr, nullptr, dst, GGML_OP_UNARY, { (uint32_t)ggml_nelements(src0), 0, 0.0f, 0.0f }, dryrun);
++    ggml_vk_op_f32<vk_op_push_constants>(ctx, subctx, src0, nullptr, nullptr, nullptr, dst, GGML_OP_UNARY, { (uint32_t)ggml_nelements(src0), 0, 0.0f, 0.0f }, dryrun);
+ }
+ 
+ static void ggml_vk_glu(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst, bool dryrun = false) {
+@@ -9690,7 +9757,7 @@ static void ggml_vk_glu(ggml_backend_vk_context * ctx, vk_context& subctx, const
+ 
+     const uint32_t mode = split ? 2 : (swapped ? 1 : 0);
+ 
+-    ggml_vk_op_f32<vk_op_glu_push_constants>(ctx, subctx, src0, src1, nullptr, dst, GGML_OP_GLU,
++    ggml_vk_op_f32<vk_op_glu_push_constants>(ctx, subctx, src0, src1, nullptr, nullptr, dst, GGML_OP_GLU,
+         {
+             (uint32_t)ggml_nelements(dst),
+             (uint32_t)src0->ne[0],
+@@ -9703,7 +9770,7 @@ static void ggml_vk_glu(ggml_backend_vk_context * ctx, vk_context& subctx, const
+ 
+ static void ggml_vk_diag_mask_inf(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, ggml_tensor * dst, bool dryrun = false) {
+     int32_t * op_params = (int32_t *)dst->op_params;
+-    ggml_vk_op_f32<vk_op_diag_mask_push_constants>(ctx, subctx, src0, nullptr, nullptr, dst, GGML_OP_DIAG_MASK_INF, { (uint32_t)src0->ne[0], (uint32_t)src0->ne[1], op_params[0] }, dryrun);
++    ggml_vk_op_f32<vk_op_diag_mask_push_constants>(ctx, subctx, src0, nullptr, nullptr, nullptr, dst, GGML_OP_DIAG_MASK_INF, { (uint32_t)src0->ne[0], (uint32_t)src0->ne[1], op_params[0] }, dryrun);
+ }
+ 
+ static void ggml_vk_soft_max(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, const ggml_tensor * src1, const ggml_tensor * src2, ggml_tensor * dst, bool dryrun = false) {
+@@ -9728,7 +9795,7 @@ static void ggml_vk_soft_max(ggml_backend_vk_context * ctx, vk_context& subctx,
+     const float m0 = powf(2.0f, -(max_bias       ) / n_head_log2);
+     const float m1 = powf(2.0f, -(max_bias / 2.0f) / n_head_log2);
+ 
+-    ggml_vk_op_f32<vk_op_soft_max_push_constants>(ctx, subctx, src0, src1, src2, dst, GGML_OP_SOFT_MAX, {
++    ggml_vk_op_f32<vk_op_soft_max_push_constants>(ctx, subctx, src0, src1, src2, nullptr, dst, GGML_OP_SOFT_MAX, {
+         ncols,
+         src1 != nullptr ? nrows_y : (uint32_t)0,
+         (uint32_t)src0->ne[0], (uint32_t)src0->ne[1], (uint32_t)src0->ne[2],
+@@ -9744,7 +9811,7 @@ static void ggml_vk_soft_max(ggml_backend_vk_context * ctx, vk_context& subctx,
+ 
+ static void ggml_vk_soft_max_back(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst, bool dryrun = false) {
+     float * op_params = (float *)dst->op_params;
+-    ggml_vk_op_f32<vk_op_push_constants>(ctx, subctx, src0, src1, nullptr, dst, GGML_OP_SOFT_MAX_BACK, { (uint32_t)src0->ne[0], (uint32_t)ggml_nrows(src0), op_params[0], op_params[1] }, dryrun);
++    ggml_vk_op_f32<vk_op_push_constants>(ctx, subctx, src0, src1, nullptr, nullptr, dst, GGML_OP_SOFT_MAX_BACK, { (uint32_t)src0->ne[0], (uint32_t)ggml_nrows(src0), op_params[0], op_params[1] }, dryrun);
+ }
+ 
+ static void ggml_vk_topk_moe(ggml_backend_vk_context * ctx, vk_context& subctx, ggml_cgraph * cgraph, int node_idx, bool dryrun = false) {
+@@ -9835,7 +9902,12 @@ static void ggml_vk_topk_moe(ggml_backend_vk_context * ctx, vk_context& subctx,
+         }, pc, elements);
+ }
+ 
+-static void ggml_vk_rope(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, const ggml_tensor * src1, const ggml_tensor * src2, ggml_tensor * dst, bool backprop, bool dryrun = false) {
++static void ggml_vk_rope(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_cgraph * cgraph, int node_idx, bool backprop, bool dryrun = false) {
++    ggml_tensor * dst = cgraph->nodes[node_idx];
++    const ggml_tensor * src0 = dst->src[0];
++    const ggml_tensor * src1 = dst->src[1];
++    const ggml_tensor * src2 = dst->src[2];
++    const ggml_tensor * src3 = nullptr;
+     const int n_dims        = ((int32_t *) dst->op_params)[1];
+     const int mode          = ((int32_t *) dst->op_params)[2];
+     // const int n_ctx         = ((int32_t *) dst->op_params)[3];
+@@ -9859,11 +9931,20 @@ static void ggml_vk_rope(ggml_backend_vk_context * ctx, vk_context& subctx, cons
+     uint32_t s1 = src0->nb[1] / ggml_type_size(src0->type);
+     uint32_t s2 = src0->nb[2] / ggml_type_size(src0->type);
+ 
+-    ggml_vk_op_f32<vk_op_rope_push_constants>(ctx, subctx, src0, src1, src2, dst, GGML_OP_ROPE, {
++    uint32_t set_rows_stride = 0;
++    // Fused rope + view + set_rows passes the set_rows destination stride in set_rows_stride
++    // and overrides the dst and sets src3=row_indices
++    if (ctx->num_additional_fused_ops > 0) {
++        set_rows_stride = cgraph->nodes[node_idx + 2]->nb[1] / ggml_type_size(cgraph->nodes[node_idx + 2]->type);
++        src3 = cgraph->nodes[node_idx + 2]->src[1];
++        dst = cgraph->nodes[node_idx + 2];
++    }
++
++    ggml_vk_op_f32<vk_op_rope_push_constants>(ctx, subctx, src0, src1, src2, src3, dst, GGML_OP_ROPE, {
+         (uint32_t)src0->ne[0], (uint32_t)n_dims, freq_scale, (uint32_t)src0->ne[1],
+         freq_base, ext_factor, attn_factor, {corr_dims[0], corr_dims[1]}, theta_scale,
+         src2 != nullptr, (uint32_t)src0->ne[2], s1, s2,
+-        { sections[0], sections[1], sections[2], sections[3] }, backprop
++        { sections[0], sections[1], sections[2], sections[3] }, backprop, set_rows_stride,
+     }, dryrun);
+ }
+ 
+@@ -9872,7 +9953,7 @@ static void ggml_vk_argsort(ggml_backend_vk_context * ctx, vk_context& subctx, c
+ 
+     uint32_t ncols = src0->ne[0];
+ 
+-    ggml_vk_op_f32<vk_op_argsort_push_constants>(ctx, subctx, src0, nullptr, nullptr, dst, GGML_OP_ARGSORT, {
++    ggml_vk_op_f32<vk_op_argsort_push_constants>(ctx, subctx, src0, nullptr, nullptr, nullptr, dst, GGML_OP_ARGSORT, {
+         ncols,
+         op_params[0],
+     }, dryrun);
+@@ -9880,26 +9961,26 @@ static void ggml_vk_argsort(ggml_backend_vk_context * ctx, vk_context& subctx, c
+ 
+ static void ggml_vk_sum(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, ggml_tensor * dst, bool dryrun = false) {
+     vk_op_sum_rows_push_constants p = vk_op_sum_rows_push_constants_init(src0, dst, ggml_nelements(src0));
+-    ggml_vk_op_f32(ctx, subctx, src0, nullptr, nullptr, dst, GGML_OP_SUM, p, dryrun);
++    ggml_vk_op_f32(ctx, subctx, src0, nullptr, nullptr, nullptr, dst, GGML_OP_SUM, p, dryrun);
+ }
+ 
+ static void ggml_vk_sum_rows(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, ggml_tensor * dst, bool dryrun = false) {
+     vk_op_sum_rows_push_constants p = vk_op_sum_rows_push_constants_init(src0, dst, src0->ne[0]);
+-    ggml_vk_op_f32(ctx, subctx, src0, nullptr, nullptr, dst, GGML_OP_SUM_ROWS, p, dryrun);
++    ggml_vk_op_f32(ctx, subctx, src0, nullptr, nullptr, nullptr, dst, GGML_OP_SUM_ROWS, p, dryrun);
+ }
+ 
+ static void ggml_vk_mean(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, ggml_tensor * dst, bool dryrun = false) {
+     vk_op_sum_rows_push_constants p = vk_op_sum_rows_push_constants_init(src0, dst, src0->ne[0]);
+     p.weight = 1.0f / (float)src0->ne[0];
+-    ggml_vk_op_f32(ctx, subctx, src0, nullptr, nullptr, dst, GGML_OP_MEAN, p, dryrun);
++    ggml_vk_op_f32(ctx, subctx, src0, nullptr, nullptr, nullptr, dst, GGML_OP_MEAN, p, dryrun);
+ }
+ 
+ static void ggml_vk_argmax(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, ggml_tensor * dst, bool dryrun = false) {
+-    ggml_vk_op_f32<vk_op_push_constants>(ctx, subctx, src0, nullptr, nullptr, dst, GGML_OP_ARGMAX, { (uint32_t)src0->ne[0], (uint32_t)src0->ne[1], 0.0f, 0.0f }, dryrun);
++    ggml_vk_op_f32<vk_op_push_constants>(ctx, subctx, src0, nullptr, nullptr, nullptr, dst, GGML_OP_ARGMAX, { (uint32_t)src0->ne[0], (uint32_t)src0->ne[1], 0.0f, 0.0f }, dryrun);
+ }
+ 
+ static void ggml_vk_count_equal(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst, bool dryrun = false) {
+-    ggml_vk_op_f32<vk_op_push_constants>(ctx, subctx, src0, src1, nullptr, dst, GGML_OP_COUNT_EQUAL, { (uint32_t)ggml_nelements(src0), 0, 0.0f, 0.0f }, dryrun);
++    ggml_vk_op_f32<vk_op_push_constants>(ctx, subctx, src0, src1, nullptr, nullptr, dst, GGML_OP_COUNT_EQUAL, { (uint32_t)ggml_nelements(src0), 0, 0.0f, 0.0f }, dryrun);
+ }
+ 
+ static void ggml_vk_im2col(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst, bool dryrun = false) {
+@@ -9932,7 +10013,7 @@ static void ggml_vk_im2col(ggml_backend_vk_context * ctx, vk_context& subctx, co
+ 
+     const vk::DeviceAddress dst_addr = d_buf->bda_addr + vk_tensor_offset(dst) + dst->view_offs;
+ 
+-    ggml_vk_op_f32<vk_op_im2col_push_constants>(ctx, subctx, src0, src1, nullptr, dst, GGML_OP_IM2COL, {
++    ggml_vk_op_f32<vk_op_im2col_push_constants>(ctx, subctx, src0, src1, nullptr, nullptr, dst, GGML_OP_IM2COL, {
+         dst_addr,
+         batch_offset, offset_delta,
+         IC, IW, IH, OW, OH, KW, KH,
+@@ -10005,7 +10086,7 @@ static void ggml_vk_im2col_3d(ggml_backend_vk_context * ctx, vk_context& subctx,
+     pc.OH_OW_IC_KD_KH_KW = OH*OW*IC*KD*KH*KW;
+     pc.OW_IC_KD_KH_KW = OW*IC*KD*KH*KW;
+ 
+-    ggml_vk_op_f32<vk_op_im2col_3d_push_constants>(ctx, subctx, src0, src1, nullptr, dst, GGML_OP_IM2COL_3D, std::move(pc), dryrun);
++    ggml_vk_op_f32<vk_op_im2col_3d_push_constants>(ctx, subctx, src0, src1, nullptr, nullptr, dst, GGML_OP_IM2COL_3D, std::move(pc), dryrun);
+ }
+ 
+ static void ggml_vk_timestep_embedding(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, ggml_tensor * dst, bool dryrun = false) {
+@@ -10013,7 +10094,7 @@ static void ggml_vk_timestep_embedding(ggml_backend_vk_context * ctx, vk_context
+     const uint32_t max_period = dst->op_params[1];
+     const uint32_t nb1 = dst->nb[1] / ggml_type_size(dst->type);
+ 
+-    ggml_vk_op_f32<vk_op_timestep_embedding_push_constants>(ctx, subctx, src0, nullptr, nullptr, dst, GGML_OP_TIMESTEP_EMBEDDING, {
++    ggml_vk_op_f32<vk_op_timestep_embedding_push_constants>(ctx, subctx, src0, nullptr, nullptr, nullptr, dst, GGML_OP_TIMESTEP_EMBEDDING, {
+         nb1, dim, max_period,
+     }, dryrun);
+ }
+@@ -10046,7 +10127,7 @@ static void ggml_vk_conv_transpose_1d(ggml_backend_vk_context * ctx, vk_context&
+     p.nb1 = static_cast<uint32_t>(nb1 / nb0);
+     p.s0 = static_cast<uint32_t>(s0);
+ 
+-    ggml_vk_op_f32(ctx, subctx, src0, src1, nullptr, dst, GGML_OP_CONV_TRANSPOSE_1D, std::move(p), dryrun);
++    ggml_vk_op_f32(ctx, subctx, src0, src1, nullptr, nullptr, dst, GGML_OP_CONV_TRANSPOSE_1D, std::move(p), dryrun);
+ }
+ 
+ static void ggml_vk_pool_2d(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, ggml_tensor * dst, bool dryrun = false) {
+@@ -10069,7 +10150,7 @@ static void ggml_vk_pool_2d(ggml_backend_vk_context * ctx, vk_context& subctx, c
+ 
+     const uint32_t parallel_elements = N * OC * OH * OW;
+ 
+-    ggml_vk_op_f32<vk_op_pool2d_push_constants>(ctx, subctx, src0, nullptr, nullptr, dst, GGML_OP_POOL_2D, {
++    ggml_vk_op_f32<vk_op_pool2d_push_constants>(ctx, subctx, src0, nullptr, nullptr, nullptr, dst, GGML_OP_POOL_2D, {
+         IW, IH, OW, OH, OC,
+         parallel_elements,
+         op,
+@@ -10123,7 +10204,7 @@ static void ggml_vk_conv_2d(ggml_backend_vk_context * ctx, vk_context & subctx,
+     GGML_ASSERT(ne03 == ne2);
+     GGML_ASSERT(ne02 == ne12);
+ 
+-    ggml_vk_op_f32(ctx, subctx, src0, src1, nullptr, dst, GGML_OP_CONV_2D, std::move(p), dryrun);
++    ggml_vk_op_f32(ctx, subctx, src0, src1, nullptr, nullptr, dst, GGML_OP_CONV_2D, std::move(p), dryrun);
+ }
+ 
+ static void ggml_vk_conv_transpose_2d(ggml_backend_vk_context * ctx, vk_context & subctx, const ggml_tensor * src0,
+@@ -10172,7 +10253,7 @@ static void ggml_vk_conv_transpose_2d(ggml_backend_vk_context * ctx, vk_context
+     GGML_ASSERT(ne02 == ne2);
+     GGML_ASSERT(ne03 == ne12);
+ 
+-    ggml_vk_op_f32(ctx, subctx, src0, src1, nullptr, dst, GGML_OP_CONV_TRANSPOSE_2D, std::move(p), dryrun);
++    ggml_vk_op_f32(ctx, subctx, src0, src1, nullptr, nullptr, dst, GGML_OP_CONV_TRANSPOSE_2D, std::move(p), dryrun);
+ }
+ 
+ static void ggml_vk_conv_2d_dw(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst, bool dryrun = false) {
+@@ -10196,12 +10277,12 @@ static void ggml_vk_conv_2d_dw(ggml_backend_vk_context * ctx, vk_context& subctx
+     GGML_ASSERT(src0->ne[3] == p.channels);
+     GGML_ASSERT(src1->ne[3] == p.batches);
+ 
+-    ggml_vk_op_f32(ctx, subctx, src0, src1, nullptr, dst, GGML_OP_CONV_2D_DW, std::move(p), dryrun);
++    ggml_vk_op_f32(ctx, subctx, src0, src1, nullptr, nullptr, dst, GGML_OP_CONV_2D_DW, std::move(p), dryrun);
+ }
+ 
+ static void ggml_vk_leaky_relu(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, ggml_tensor * dst, bool dryrun = false) {
+     const float * op_params = (const float *)dst->op_params;
+-    ggml_vk_op_f32<vk_op_push_constants>(ctx, subctx, src0, nullptr, nullptr, dst, GGML_OP_LEAKY_RELU, { (uint32_t)ggml_nelements(src0), 0, op_params[0], 0.0f }, dryrun);
++    ggml_vk_op_f32<vk_op_push_constants>(ctx, subctx, src0, nullptr, nullptr, nullptr, dst, GGML_OP_LEAKY_RELU, { (uint32_t)ggml_nelements(src0), 0, op_params[0], 0.0f }, dryrun);
+ }
+ 
+ #ifdef GGML_VULKAN_RUN_TESTS
+@@ -11327,7 +11408,6 @@ static bool ggml_vk_build_graph(ggml_backend_vk_context * ctx, ggml_cgraph * cgr
+         case GGML_OP_DIAG_MASK_INF:
+         case GGML_OP_SOFT_MAX:
+         case GGML_OP_SOFT_MAX_BACK:
+-        case GGML_OP_ROPE:
+         case GGML_OP_ROPE_BACK:
+         case GGML_OP_ARGSORT:
+         case GGML_OP_SUM:
+@@ -11401,9 +11481,12 @@ static bool ggml_vk_build_graph(ggml_backend_vk_context * ctx, ggml_cgraph * cgr
+         // nodes require synchronization.
+         for (int32_t i = 0; i < ctx->num_additional_fused_ops + 1 && !need_sync; ++i) {
+             const ggml_tensor *cur_node = cgraph->nodes[node_idx + i];
+-            if (overlaps_unsynced(cur_node, ctx->unsynced_nodes_read) || overlaps_unsynced(cur_node, ctx->unsynced_nodes_written)) {
+-                need_sync = true;
+-                break;
++            // If the node actually writes to memory, then check if it needs to sync
++            if (ctx->fused_ops_write_mask & (1 << i)) {
++                if (overlaps_unsynced(cur_node, ctx->unsynced_nodes_read) || overlaps_unsynced(cur_node, ctx->unsynced_nodes_written)) {
++                    need_sync = true;
++                    break;
++                }
+             }
+             for (uint32_t j = 0; j < GGML_MAX_SRC; ++j) {
+                 if (!cur_node->src[j]) {
+@@ -11430,7 +11513,9 @@ static bool ggml_vk_build_graph(ggml_backend_vk_context * ctx, ggml_cgraph * cgr
+         for (int32_t i = 0; i < ctx->num_additional_fused_ops + 1; ++i) {
+             const ggml_tensor *cur_node = cgraph->nodes[node_idx + i];
+             // Multiple outputs could be written, e.g. in topk_moe. Add them all to the list.
+-            ctx->unsynced_nodes_written.push_back(cur_node);
++            if (ctx->fused_ops_write_mask & (1 << i)) {
++                ctx->unsynced_nodes_written.push_back(cur_node);
++            }
+             for (uint32_t j = 0; j < GGML_MAX_SRC; ++j) {
+                 if (!cur_node->src[j]) {
+                     continue;
+@@ -11621,11 +11706,11 @@ static bool ggml_vk_build_graph(ggml_backend_vk_context * ctx, ggml_cgraph * cgr
+ 
+         break;
+     case GGML_OP_ROPE:
+-        ggml_vk_rope(ctx, compute_ctx, src0, src1, src2, node, false, dryrun);
++        ggml_vk_rope(ctx, compute_ctx, cgraph, node_idx, false, dryrun);
+ 
+         break;
+     case GGML_OP_ROPE_BACK:
+-        ggml_vk_rope(ctx, compute_ctx, src0, src1, src2, node, true, dryrun);
++        ggml_vk_rope(ctx, compute_ctx, cgraph, node_idx, true, dryrun);
+ 
+         break;
+     case GGML_OP_ARGSORT:
+@@ -12487,6 +12572,41 @@ static bool ggml_vk_can_fuse_topk_moe(ggml_backend_vk_context * ctx, const struc
+     return true;
+ }
+ 
++static bool ggml_vk_can_fuse_rope_set_rows(ggml_backend_vk_context * ctx, const struct ggml_cgraph * cgraph,
++                                           int node_idx) {
++    GGML_UNUSED(ctx);
++    const ggml_tensor *rope = cgraph->nodes[node_idx + 0];
++    const ggml_tensor *view = cgraph->nodes[node_idx + 1];
++    const ggml_tensor *set_rows = cgraph->nodes[node_idx + 2];
++
++    // ne3 not tested
++    if (rope->src[0]->ne[3] != 1) {
++        return false;
++    }
++
++    if (set_rows->type != GGML_TYPE_F32 && set_rows->type != GGML_TYPE_F16) {
++        return false;
++    }
++
++    if (set_rows->src[1]->type != GGML_TYPE_I64) {
++        return false;
++    }
++
++    // The view should flatten two dims of rope into one dim
++    if (!ggml_is_contiguous(view) ||
++        view->ne[0] != rope->ne[0] * rope->ne[1]) {
++        return false;
++    }
++
++    // Only norm/neox shaders have the fusion code
++    const int mode = ((const int32_t *) rope->op_params)[2];
++    if (mode != GGML_ROPE_TYPE_NORMAL && mode != GGML_ROPE_TYPE_NEOX) {
++        return false;
++    }
++
++    return true;
++}
++
+ static uint32_t ggml_vk_fuse_multi_add(ggml_backend_vk_context * ctx, const struct ggml_cgraph * cgraph, int node_idx) {
+ 
+     const ggml_tensor *first_node = cgraph->nodes[node_idx];
+@@ -12562,6 +12682,10 @@ static ggml_status ggml_backend_vk_graph_compute(ggml_backend_t backend, ggml_cg
+                 ctx->num_additional_fused_ops = num_adds - 1;
+             } else if (ggml_vk_can_fuse(cgraph, i, { GGML_OP_RMS_NORM, GGML_OP_MUL })) {
+                 ctx->num_additional_fused_ops = 1;
++            } else if (ggml_can_fuse_subgraph(cgraph, i, { GGML_OP_ROPE, GGML_OP_VIEW, GGML_OP_SET_ROWS }, { i + 2 }) &&
++                       ggml_check_edges(cgraph, i, rope_view_set_rows_edges) &&
++                       ggml_vk_can_fuse_rope_set_rows(ctx, cgraph, i)) {
++                ctx->num_additional_fused_ops = 2;
+             } else if (ggml_can_fuse_subgraph(cgraph, i, topk_moe_early_softmax_norm, { i + 3, i + 9 }) &&
+                        ggml_check_edges(cgraph, i, topk_moe_early_softmax_norm_edges) &&
+                        ggml_vk_can_fuse_topk_moe(ctx, cgraph, i, TOPK_MOE_EARLY_SOFTMAX_NORM)) {
+@@ -12671,20 +12795,31 @@ static ggml_status ggml_backend_vk_graph_compute(ggml_backend_t backend, ggml_cg
+                 ctx->num_additional_fused_ops = num_adds - 1;
+             } else if (ggml_vk_can_fuse(cgraph, i, { GGML_OP_RMS_NORM, GGML_OP_MUL })) {
+                 ctx->num_additional_fused_ops = 1;
++            } else if (ggml_can_fuse_subgraph(cgraph, i, { GGML_OP_ROPE, GGML_OP_VIEW, GGML_OP_SET_ROWS }, { i + 2 }) &&
++                       ggml_check_edges(cgraph, i, rope_view_set_rows_edges) &&
++                       ggml_vk_can_fuse_rope_set_rows(ctx, cgraph, i)) {
++                ctx->num_additional_fused_ops = 2;
+             } else if (ggml_can_fuse_subgraph(cgraph, i, topk_moe_early_softmax_norm, { i + 3, i + 9 }) &&
+                        ggml_check_edges(cgraph, i, topk_moe_early_softmax_norm_edges) &&
+                        ggml_vk_can_fuse_topk_moe(ctx, cgraph, i, TOPK_MOE_EARLY_SOFTMAX_NORM)) {
+                 ctx->num_additional_fused_ops = topk_moe_early_softmax_norm.size() - 1;
++                // view of argsort writes to memory
++                ctx->fused_ops_write_mask |= 1 << 3;
+             } else if (ggml_can_fuse_subgraph(cgraph, i, topk_moe_early_softmax, { i + 3, i + 4 }) &&
+                        ggml_check_edges(cgraph, i, topk_moe_early_softmax_edges) &&
+                        ggml_vk_can_fuse_topk_moe(ctx, cgraph, i, TOPK_MOE_EARLY_SOFTMAX)) {
+                 ctx->num_additional_fused_ops = topk_moe_early_softmax.size() - 1;
++                // view of argsort writes to memory
++                ctx->fused_ops_write_mask |= 1 << 3;
+             } else if (ggml_can_fuse_subgraph(cgraph, i, topk_moe_late_softmax, { i + 1, i + 5 }) &&
+                        ggml_check_edges(cgraph, i, topk_moe_late_softmax_edges) &&
+                        ggml_vk_can_fuse_topk_moe(ctx, cgraph, i, TOPK_MOE_LATE_SOFTMAX)) {
+                 ctx->num_additional_fused_ops = topk_moe_late_softmax.size() - 1;
++                // view of argsort writes to memory
++                ctx->fused_ops_write_mask |= 1 << 1;
+             }
+         }
++        ctx->fused_ops_write_mask |= 1 << ctx->num_additional_fused_ops;
+ 
+         // Signal the almost_ready fence when the graph is mostly complete (< 20% remaining)
+         bool almost_ready = (cgraph->n_nodes - i) < cgraph->n_nodes / 5;
+@@ -12730,6 +12865,7 @@ static ggml_status ggml_backend_vk_graph_compute(ggml_backend_t backend, ggml_cg
+         }
+         i += ctx->num_additional_fused_ops;
+         ctx->num_additional_fused_ops = 0;
++        ctx->fused_ops_write_mask = 0;
+     }
+ 
+     if (vk_perf_logger_enabled) {
+@@ -12887,6 +13023,32 @@ static void ggml_vk_graph_optimize(ggml_backend_t backend, struct ggml_cgraph *
+             }
+             if (ok) {
+                 current_set.push_back(j);
++                // Look for ROPE + VIEW + SET_ROWS and make them consecutive
++                if (graph->nodes[j]->op == GGML_OP_ROPE) {
++                    int view_idx = -1;
++                    int set_rows_idx = -1;
++                    for (int k = j+1; k < std::min(j + 10, graph->n_nodes); ++k) {
++                        if (view_idx == -1 &&
++                            graph->nodes[k]->op == GGML_OP_VIEW &&
++                            graph->nodes[k]->src[0] == graph->nodes[j]) {
++                            view_idx = k;
++                            continue;
++                        }
++                        if (view_idx != -1 &&
++                            set_rows_idx == -1 &&
++                            graph->nodes[k]->op == GGML_OP_SET_ROWS &&
++                            graph->nodes[k]->src[0] == graph->nodes[view_idx]) {
++                            set_rows_idx = k;
++                            break;
++                        }
++                    }
++                    if (set_rows_idx != -1) {
++                        current_set.push_back(view_idx);
++                        current_set.push_back(set_rows_idx);
++                        used[view_idx] = true;
++                        used[set_rows_idx] = true;
++                    }
++                }
+             }
+         }
+         // Second pass grabs view nodes.
+diff --git a/ggml/src/ggml-vulkan/vulkan-shaders/rope_head.glsl b/ggml/src/ggml-vulkan/vulkan-shaders/rope_head.glsl
+index 50fc1f1e2..0eda186c8 100644
+--- a/ggml/src/ggml-vulkan/vulkan-shaders/rope_head.glsl
++++ b/ggml/src/ggml-vulkan/vulkan-shaders/rope_head.glsl
+@@ -10,6 +10,7 @@ layout (binding = 0) readonly buffer X {A_TYPE data_a[];};
+ layout (binding = 1) readonly buffer Y {int data_pos[];};
+ layout (binding = 2) readonly buffer Z {float data_ff[];};
+ layout (binding = 3) writeonly buffer D {D_TYPE data_d[];};
++layout (binding = 4) readonly buffer I {uvec2 data_i[];}; // indices for set_rows
+ 
+ layout (push_constant) uniform parameter {
+     uint ncols;
+@@ -27,6 +28,7 @@ layout (push_constant) uniform parameter {
+     uint s2;
+     int sections[4];
+     uint is_back;
++    uint set_rows_stride;
+ } p;
+ 
+ float rope_yarn_ramp(const float low, const float high, const uint i0) {
+diff --git a/ggml/src/ggml-vulkan/vulkan-shaders/rope_neox.comp b/ggml/src/ggml-vulkan/vulkan-shaders/rope_neox.comp
+index 06e095bef..9f4538155 100644
+--- a/ggml/src/ggml-vulkan/vulkan-shaders/rope_neox.comp
++++ b/ggml/src/ggml-vulkan/vulkan-shaders/rope_neox.comp
+@@ -16,12 +16,19 @@ void main() {
+     const uint row_x     = row_dst % ne1;
+     const uint channel_x = row_dst / ne1;
+ 
+-    const uint idst = row_dst*ne0 + i0/2;
++    uint idst = row_dst*ne0 + i0/2;
+     const uint ix   = channel_x*p.s2 + row_x*p.s1 + i0/2;
+ 
++    // Fusion optimization: ROPE + VIEW + SET_ROWS..
++    // The rope output is viewed as a 1D tensor and offset based on a row index in data_i.
++    if (p.set_rows_stride != 0) {
++        idst = row_x*ne0 + i0/2;
++        idst += data_i[channel_x].x * p.set_rows_stride;
++    }
++
+     if (i0 >= p.n_dims) {
+-        data_d[idst + i0/2 + 0] = data_a[ix + i0/2 + 0];
+-        data_d[idst + i0/2 + 1] = data_a[ix + i0/2 + 1];
++        data_d[idst + i0/2 + 0] = D_TYPE(data_a[ix + i0/2 + 0]);
++        data_d[idst + i0/2 + 1] = D_TYPE(data_a[ix + i0/2 + 1]);
+ 
+         return;
+     }
+diff --git a/ggml/src/ggml-vulkan/vulkan-shaders/rope_norm.comp b/ggml/src/ggml-vulkan/vulkan-shaders/rope_norm.comp
+index 6ba957540..f4209ed95 100644
+--- a/ggml/src/ggml-vulkan/vulkan-shaders/rope_norm.comp
++++ b/ggml/src/ggml-vulkan/vulkan-shaders/rope_norm.comp
+@@ -16,12 +16,19 @@ void main() {
+     const uint row_x     = row_dst % ne1;
+     const uint channel_x = row_dst / ne1;
+ 
+-    const uint idst = row_dst*ne0 + i0;
++    uint idst = row_dst*ne0 + i0;
+     const uint ix   = channel_x*p.s2 + row_x*p.s1 + i0;
+ 
++    // Fusion optimization: ROPE + VIEW + SET_ROWS..
++    // The rope output is viewed as a 1D tensor and offset based on a row index in data_i.
++    if (p.set_rows_stride != 0) {
++        idst = row_x*ne0 + i0;
++        idst += data_i[channel_x].x * p.set_rows_stride;
++    }
++
+     if (i0 >= p.n_dims) {
+-        data_d[idst + 0] = data_a[ix + 0];
+-        data_d[idst + 1] = data_a[ix + 1];
++        data_d[idst + 0] = D_TYPE(data_a[ix + 0]);
++        data_d[idst + 1] = D_TYPE(data_a[ix + 1]);
+ 
+         return;
+     }
+diff --git a/ggml/src/ggml-vulkan/vulkan-shaders/vulkan-shaders-gen.cpp b/ggml/src/ggml-vulkan/vulkan-shaders/vulkan-shaders-gen.cpp
+index 03fa01639..e6ec589fb 100644
+--- a/ggml/src/ggml-vulkan/vulkan-shaders/vulkan-shaders-gen.cpp
++++ b/ggml/src/ggml-vulkan/vulkan-shaders/vulkan-shaders-gen.cpp
+@@ -842,10 +842,14 @@ void process_shaders() {
+     string_to_spv("rope_norm_f32", "rope_norm.comp", {{"A_TYPE", "float"}, {"D_TYPE", "float"}});
+     string_to_spv("rope_norm_f16", "rope_norm.comp", {{"A_TYPE", "float16_t"}, {"D_TYPE", "float16_t"}});
+     string_to_spv("rope_norm_f16_rte", "rope_norm.comp", {{"A_TYPE", "float16_t"}, {"D_TYPE", "float16_t"}, {"RTE16", "1"}});
++    string_to_spv("rope_norm_f32_f16", "rope_norm.comp", {{"A_TYPE", "float"}, {"D_TYPE", "float16_t"}});
++    string_to_spv("rope_norm_f32_f16_rte", "rope_norm.comp", {{"A_TYPE", "float"}, {"D_TYPE", "float16_t"}, {"RTE16", "1"}});
+ 
+     string_to_spv("rope_neox_f32", "rope_neox.comp", {{"A_TYPE", "float"}, {"D_TYPE", "float"}});
+     string_to_spv("rope_neox_f16", "rope_neox.comp", {{"A_TYPE", "float16_t"}, {"D_TYPE", "float16_t"}});
+     string_to_spv("rope_neox_f16_rte", "rope_neox.comp", {{"A_TYPE", "float16_t"}, {"D_TYPE", "float16_t"}, {"RTE16", "1"}});
++    string_to_spv("rope_neox_f32_f16", "rope_neox.comp", {{"A_TYPE", "float"}, {"D_TYPE", "float16_t"}});
++    string_to_spv("rope_neox_f32_f16_rte", "rope_neox.comp", {{"A_TYPE", "float"}, {"D_TYPE", "float16_t"}, {"RTE16", "1"}});
+ 
+     string_to_spv("rope_multi_f32", "rope_multi.comp", {{"A_TYPE", "float"}, {"D_TYPE", "float"}});
+     string_to_spv("rope_multi_f16", "rope_multi.comp", {{"A_TYPE", "float16_t"}, {"D_TYPE", "float16_t"}});
+diff --git a/tests/test-backend-ops.cpp b/tests/test-backend-ops.cpp
+index 9eb2b6687..657b6cc2f 100644
+--- a/tests/test-backend-ops.cpp
++++ b/tests/test-backend-ops.cpp
+@@ -2105,6 +2105,34 @@ struct test_get_rows_back : public test_case {
+     }
+ };
+ 
++static void init_set_rows_row_ids(ggml_tensor * t, int num_rows) {
++    std::random_device rd;
++    std::default_random_engine rng(rd());
++    for (int i2 = 0; i2 < t->ne[2]; i2++) {
++        for (int i1 = 0; i1 < t->ne[1]; i1++) {
++            // generate a shuffled subset of row indices
++            std::vector<int64_t> data(num_rows);
++            for (int i = 0; i < num_rows; i++) {
++                data[i] = i;
++            }
++            std::shuffle(data.begin(), data.end(), rng);
++            data.resize(t->ne[0]);
++
++            const size_t offs = i1*t->nb[1] + i2*t->nb[2];
++            if (t->type == GGML_TYPE_I32) {
++                // TODO: Make a template or something
++                std::vector<int32_t> data_i32(t->ne[0]);
++                for (int i = 0; i < t->ne[0]; i++) {
++                    data_i32[i] = static_cast<int32_t>(data[i]);
++                }
++                ggml_backend_tensor_set(t, data_i32.data(), offs, t->ne[0]*sizeof(int32_t));
++            } else {
++                ggml_backend_tensor_set(t, data.data(), offs, t->ne[0]*sizeof(int64_t));
++            }
++        }
++    }
++}
++
+ // GGML_OP_SET_ROWS
+ struct test_set_rows : public test_case {
+     const ggml_type type;
+@@ -2148,37 +2176,13 @@ struct test_set_rows : public test_case {
+     }
+ 
+     void initialize_tensors(ggml_context * ctx) override {
+-        std::random_device rd;
+-        std::default_random_engine rng(rd());
+         for (ggml_tensor * t = ggml_get_first_tensor(ctx); t != NULL; t = ggml_get_next_tensor(ctx, t)) {
+             if (t->type == GGML_TYPE_I64 || t->type == GGML_TYPE_I32) {
+                 if (ggml_is_view_op(t->op)) {
+                     continue;
+                 }
+ 
+-                for (int i2 = 0; i2 < t->ne[2]; i2++) {
+-                    for (int i1 = 0; i1 < t->ne[1]; i1++) {
+-                        // generate a shuffled subset of row indices
+-                        std::vector<int64_t> data(ne[1]);
+-                        for (int i = 0; i < ne[1]; i++) {
+-                            data[i] = i;
+-                        }
+-                        std::shuffle(data.begin(), data.end(), rng);
+-                        data.resize(t->ne[0]);
+-
+-                        const size_t offs = i1*t->nb[1] + i2*t->nb[2];
+-                        if (t->type == GGML_TYPE_I32) {
+-                            // TODO: Make a template or something
+-                            std::vector<int32_t> data_i32(t->ne[0]);
+-                            for (int i = 0; i < t->ne[0]; i++) {
+-                                data_i32[i] = static_cast<int32_t>(data[i]);
+-                            }
+-                            ggml_backend_tensor_set(t, data_i32.data(), offs, t->ne[0]*sizeof(int32_t));
+-                        } else {
+-                            ggml_backend_tensor_set(t, data.data(), offs, t->ne[0]*sizeof(int64_t));
+-                        }
+-                    }
+-                }
++                init_set_rows_row_ids(t, ne[1]);
+             } else {
+                 init_tensor_uniform(t);
+             }
+@@ -2207,6 +2211,67 @@ struct test_set_rows : public test_case {
+     }
+ };
+ 
++// GGML_OP_ROPE + GGML_OP_VIEW + GGML_OP_SET_ROWS
++struct test_rope_set_rows : public test_case {
++    const ggml_type type;
++    const ggml_type type_idx;
++    const std::array<int64_t, 4> ne;
++    int mode;
++
++    std::string vars() override {
++        return VARS_TO_STR4(type, type_idx, ne, mode);
++    }
++
++    std::string op_desc(ggml_tensor * t) override {
++        GGML_UNUSED(t);
++        return "ROPE_SET_ROWS";
++    }
++
++    bool run_whole_graph() override { return true; }
++
++    test_rope_set_rows(ggml_type type,
++            ggml_type type_idx,
++            std::array<int64_t, 4> ne,
++            int mode)
++        : type(type), type_idx(type_idx), ne(ne), mode(mode) {}
++
++    ggml_tensor * build_graph(ggml_context * ctx) override {
++        ggml_tensor * src = ggml_new_tensor_4d(ctx, GGML_TYPE_F32, ne[0], ne[1], ne[2], 1);
++        ggml_set_name(src, "src");
++
++        ggml_tensor * pos = ggml_new_tensor_1d(ctx, GGML_TYPE_I32, ne[2]);
++
++        ggml_tensor * rope = ggml_rope(ctx, src, pos, ne[0], mode);
++
++        ggml_tensor * view = ggml_view_2d(ctx, rope, ne[0] * ne[1], ne[2], rope->nb[2], 0);
++
++        ggml_tensor * dst = ggml_new_tensor_4d(ctx, type, ne[0] * ne[1], ne[2] * ne[3], 1, 1);
++        ggml_set_name(dst, "dst");
++
++        ggml_tensor * row_idxs = ggml_new_tensor_3d(ctx, type_idx, ne[2], 1, 1);
++        ggml_set_name(row_idxs, "row_idxs");
++
++        ggml_tensor * out = ggml_set_rows(ctx, dst, view, row_idxs);
++        ggml_set_name(out, "out");
++
++        return out;
++    }
++
++    void initialize_tensors(ggml_context * ctx) override {
++        for (ggml_tensor * t = ggml_get_first_tensor(ctx); t != NULL; t = ggml_get_next_tensor(ctx, t)) {
++            if (t->type == GGML_TYPE_I64 || t->type == GGML_TYPE_I32) {
++                if (ggml_is_view_op(t->op)) {
++                    continue;
++                }
++
++                init_set_rows_row_ids(t, ne[2]);
++            } else {
++                init_tensor_uniform(t);
++            }
++        }
++    }
++};
++
+ // GGML_OP_ARGMAX
+ struct test_argmax : public test_case {
+     const ggml_type type;
+@@ -6008,6 +6073,13 @@ static std::vector<std::unique_ptr<test_case>> make_test_cases_eval() {
+         }
+     }
+ 
++    for (int mode : { GGML_ROPE_TYPE_NORMAL, GGML_ROPE_TYPE_NEOX }) {
++        for (ggml_type type : {GGML_TYPE_F16, GGML_TYPE_F32}) {
++            test_cases.emplace_back(new test_rope_set_rows(type, GGML_TYPE_I64, { 128, 32, 1, 100 }, mode));
++            test_cases.emplace_back(new test_rope_set_rows(type, GGML_TYPE_I64, { 128, 32, 512, 1 }, mode));
++        }
++    }
++
+     for (ggml_type type_input : {GGML_TYPE_F32}) {
+         for (ggml_op_pool pool_type : {GGML_OP_POOL_AVG, GGML_OP_POOL_MAX}) {
+             for (int k0 : {1, 3}) {
diff --git a/llama/patches/0033-vulkan-Handle-argsort-with-a-large-number-of-rows-16.patch b/llama/patches/0033-vulkan-Handle-argsort-with-a-large-number-of-rows-16.patch
new file mode 100644
index 00000000..27a50a5f
--- /dev/null
+++ b/llama/patches/0033-vulkan-Handle-argsort-with-a-large-number-of-rows-16.patch
@@ -0,0 +1,85 @@
+From 0000000000000000000000000000000000000000 Mon Sep 17 00:00:00 2001
+From: Jeff Bolz <jbolz@nvidia.com>
+Date: Thu, 30 Oct 2025 01:27:41 -0500
+Subject: [PATCH] vulkan: Handle argsort with a large number of rows (#16851)
+
+---
+ ggml/src/ggml-vulkan/ggml-vulkan.cpp             |  4 ++++
+ ggml/src/ggml-vulkan/vulkan-shaders/argsort.comp | 16 ++++++++++++----
+ 2 files changed, 16 insertions(+), 4 deletions(-)
+
+diff --git a/ggml/src/ggml-vulkan/ggml-vulkan.cpp b/ggml/src/ggml-vulkan/ggml-vulkan.cpp
+index aaf4334b5..3604ceb04 100644
+--- a/ggml/src/ggml-vulkan/ggml-vulkan.cpp
++++ b/ggml/src/ggml-vulkan/ggml-vulkan.cpp
+@@ -1084,6 +1084,7 @@ struct vk_op_soft_max_push_constants {
+ 
+ struct vk_op_argsort_push_constants {
+     uint32_t ncols;
++    uint32_t nrows;
+     int32_t order;
+ };
+ 
+@@ -8710,6 +8711,7 @@ static void ggml_vk_op_f32(ggml_backend_vk_context * ctx, vk_context& subctx, co
+         break;
+     case GGML_OP_ARGSORT:
+         elements = { (uint32_t)ne00, (uint32_t)ggml_nrows(src0), 1 };
++        elements[1] = std::min(elements[1], ctx->device->properties.limits.maxComputeWorkGroupCount[1]);
+         break;
+     case GGML_OP_IM2COL:
+         {
+@@ -9952,9 +9954,11 @@ static void ggml_vk_argsort(ggml_backend_vk_context * ctx, vk_context& subctx, c
+     int32_t * op_params = (int32_t *)dst->op_params;
+ 
+     uint32_t ncols = src0->ne[0];
++    uint32_t nrows = ggml_nrows(src0);
+ 
+     ggml_vk_op_f32<vk_op_argsort_push_constants>(ctx, subctx, src0, nullptr, nullptr, nullptr, dst, GGML_OP_ARGSORT, {
+         ncols,
++        nrows,
+         op_params[0],
+     }, dryrun);
+ }
+diff --git a/ggml/src/ggml-vulkan/vulkan-shaders/argsort.comp b/ggml/src/ggml-vulkan/vulkan-shaders/argsort.comp
+index c81b84452..c4e68bc02 100644
+--- a/ggml/src/ggml-vulkan/vulkan-shaders/argsort.comp
++++ b/ggml/src/ggml-vulkan/vulkan-shaders/argsort.comp
+@@ -14,6 +14,7 @@ layout (binding = 1)          buffer D {int data_d[];};
+ 
+ layout (push_constant) uniform parameter {
+     uint ncols;
++    uint nrows;
+     uint order;
+ } p;
+ 
+@@ -26,10 +27,9 @@ void swap(uint idx0, uint idx1) {
+     dst_row[idx1] = tmp;
+ }
+ 
+-void argsort(bool needs_bounds_check) {
++void argsort(bool needs_bounds_check, const uint row) {
+     // bitonic sort
+     const int col = int(gl_LocalInvocationID.x);
+-    const uint row = gl_WorkGroupID.y;
+ 
+     const uint row_offset = row * p.ncols;
+ 
+@@ -72,8 +72,16 @@ void argsort(bool needs_bounds_check) {
+ 
+ void main() {
+     if (p.ncols == BLOCK_SIZE) {
+-        argsort(false);
++        uint row = gl_WorkGroupID.y;
++        while (row < p.nrows) {
++            argsort(false, row);
++            row += gl_WorkGroupSize.y * gl_NumWorkGroups.y;
++        }
+     } else {
+-        argsort(true);
++        uint row = gl_WorkGroupID.y;
++        while (row < p.nrows) {
++            argsort(true, row);
++            row += gl_WorkGroupSize.y * gl_NumWorkGroups.y;
++        }
+     }
+ }
diff --git a/llama/patches/0034-vulkan-fix-shmem-overrun-in-mmq-id-shader-16873.patch b/llama/patches/0034-vulkan-fix-shmem-overrun-in-mmq-id-shader-16873.patch
new file mode 100644
index 00000000..73dad676
--- /dev/null
+++ b/llama/patches/0034-vulkan-fix-shmem-overrun-in-mmq-id-shader-16873.patch
@@ -0,0 +1,77 @@
+From 0000000000000000000000000000000000000000 Mon Sep 17 00:00:00 2001
+From: Ruben Ortlam <picard12@live.de>
+Date: Fri, 31 Oct 2025 08:14:49 +0100
+Subject: [PATCH] vulkan: fix shmem overrun in mmq id shader (#16873)
+
+* vulkan: fix shmem overrun in mmq id shader
+
+* metal : fix mul_mm_id
+
+---------
+
+Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
+---
+ ggml/src/ggml-metal/ggml-metal-device.cpp                    | 2 +-
+ ggml/src/ggml-vulkan/vulkan-shaders/mul_mmq.comp             | 4 ++++
+ ggml/src/ggml-vulkan/vulkan-shaders/mul_mmq_shmem_types.glsl | 2 +-
+ tests/test-backend-ops.cpp                                   | 3 +++
+ 4 files changed, 9 insertions(+), 2 deletions(-)
+
+diff --git a/ggml/src/ggml-metal/ggml-metal-device.cpp b/ggml/src/ggml-metal/ggml-metal-device.cpp
+index 758116342..c78082ac3 100644
+--- a/ggml/src/ggml-metal/ggml-metal-device.cpp
++++ b/ggml/src/ggml-metal/ggml-metal-device.cpp
+@@ -677,7 +677,7 @@ ggml_metal_pipeline_t ggml_metal_library_get_pipeline_mul_mm_id_map0(ggml_metal_
+     char name[256];
+ 
+     snprintf(base, 256, "kernel_mul_mm_id_map0_ne20_%d", ne20);
+-    snprintf(name, 256, "%s", base);
++    snprintf(name, 256, "%s_ne02=%d", base, ne02);
+ 
+     ggml_metal_pipeline_t res = ggml_metal_library_get_pipeline(lib, name);
+     if (res) {
+diff --git a/ggml/src/ggml-vulkan/vulkan-shaders/mul_mmq.comp b/ggml/src/ggml-vulkan/vulkan-shaders/mul_mmq.comp
+index 8b238ac4b..d955b4fc7 100644
+--- a/ggml/src/ggml-vulkan/vulkan-shaders/mul_mmq.comp
++++ b/ggml/src/ggml-vulkan/vulkan-shaders/mul_mmq.comp
+@@ -82,9 +82,13 @@ layout (constant_id = 10) const uint WARP = 32;
+ 
+ #include "mul_mmq_shmem_types.glsl"
+ 
++#ifdef MUL_MAT_ID
++#define BK_STEP 1
++#else
+ #ifndef BK_STEP
+ #define BK_STEP 4
+ #endif
++#endif
+ 
+ // Shared memory cache
+ shared block_a_cache buf_a[BM * BK_STEP];
+diff --git a/ggml/src/ggml-vulkan/vulkan-shaders/mul_mmq_shmem_types.glsl b/ggml/src/ggml-vulkan/vulkan-shaders/mul_mmq_shmem_types.glsl
+index 72fec4404..1c0f5306f 100644
+--- a/ggml/src/ggml-vulkan/vulkan-shaders/mul_mmq_shmem_types.glsl
++++ b/ggml/src/ggml-vulkan/vulkan-shaders/mul_mmq_shmem_types.glsl
+@@ -27,7 +27,7 @@ struct block_a_cache {
+ #elif defined(DATA_A_Q8_0)
+ #define QUANT_R_MMQ 1
+ // AMD likes 4, Intel likes 1 and Nvidia likes 2
+-#define BK_STEP 1
++// #define BK_STEP 1
+ struct block_a_cache {
+     int32_t qs[32/4];
+     FLOAT_TYPE dm;
+diff --git a/tests/test-backend-ops.cpp b/tests/test-backend-ops.cpp
+index 657b6cc2f..1f8dda383 100644
+--- a/tests/test-backend-ops.cpp
++++ b/tests/test-backend-ops.cpp
+@@ -6722,6 +6722,9 @@ static std::vector<std::unique_ptr<test_case>> make_test_cases_eval() {
+     test_cases.emplace_back(new test_mul_mat_id(GGML_TYPE_F16, GGML_TYPE_F32, 1, 1, false, 8, 16, 1));
+     test_cases.emplace_back(new test_mul_mat_id(GGML_TYPE_F16, GGML_TYPE_F32, 16, 16, false, 32, 32, 32, 3));
+ 
++    // gpt-oss issue with Vulkan mmq_id
++    test_cases.emplace_back(new test_mul_mat_id(GGML_TYPE_MXFP4, GGML_TYPE_F32, 32, 2, false, 2880, 32, 2880));
++
+     for (ggml_type type_a : base_types) {
+         for (ggml_type type_b : {GGML_TYPE_F32 /*, GGML_TYPE_F16 */}) {
+             for (int n_mats : {4, 8}) {
diff --git a/llama/patches/0035-vulkan-Fix-crash-when-FP16-mul_mat-accumulation-is-n.patch b/llama/patches/0035-vulkan-Fix-crash-when-FP16-mul_mat-accumulation-is-n.patch
new file mode 100644
index 00000000..dfa46916
--- /dev/null
+++ b/llama/patches/0035-vulkan-Fix-crash-when-FP16-mul_mat-accumulation-is-n.patch
@@ -0,0 +1,80 @@
+From 0000000000000000000000000000000000000000 Mon Sep 17 00:00:00 2001
+From: Masato Nakasaka <masato.nakasaka@intel.com>
+Date: Fri, 31 Oct 2025 16:18:59 +0900
+Subject: [PATCH] vulkan: Fix crash when FP16 mul_mat accumulation is not
+ supported (#16796)
+
+* Experimenting crash fix
+
+* added assert for aborting and fixed comment
+
+* changed to check if a pipeline is empty or not
+
+* Moved function in class definition
+
+* replaced with is_empty
+
+* Modified is_empty to check only unaligned pipelines
+---
+ ggml/src/ggml-vulkan/ggml-vulkan.cpp | 20 +++++++++++++-------
+ 1 file changed, 13 insertions(+), 7 deletions(-)
+
+diff --git a/ggml/src/ggml-vulkan/ggml-vulkan.cpp b/ggml/src/ggml-vulkan/ggml-vulkan.cpp
+index 3604ceb04..80185d9f0 100644
+--- a/ggml/src/ggml-vulkan/ggml-vulkan.cpp
++++ b/ggml/src/ggml-vulkan/ggml-vulkan.cpp
+@@ -146,8 +146,13 @@ static void ggml_vk_destroy_pipeline(vk::Device& device, vk_pipeline& pipeline);
+ struct vk_matmul_pipeline_struct {
+     vk_pipeline l, m, s;
+     vk_pipeline a_l, a_m, a_s;
++    // Returns true when all unaligned pipelines are null.
++    // We only check for unaligned variants since one of the unaligned pipelines must exist
++    // while aligned pipelines are optional
++    bool is_empty() const {
++        return l == nullptr && m == nullptr && s == nullptr;
++    }
+ };
+-
+ typedef std::shared_ptr<vk_matmul_pipeline_struct> vk_matmul_pipeline;
+ 
+ struct vk_matmul_pipeline2 {
+@@ -5080,7 +5085,7 @@ static vk_matmul_pipeline ggml_vk_get_mul_mat_mat_pipeline(ggml_backend_vk_conte
+     if (src1_type == GGML_TYPE_Q8_1) {
+         vk_matmul_pipeline pipelines = ctx->device->pipeline_dequant_mul_mat_mat_q8_1[src0_type].f32acc;
+ 
+-        if (pipelines->s == nullptr && pipelines->m == nullptr && pipelines->l == nullptr) {
++        if (pipelines->is_empty()) {
+             return nullptr;
+         }
+ 
+@@ -5229,7 +5234,7 @@ static vk_matmul_pipeline ggml_vk_get_mul_mat_mat_id_pipeline(ggml_backend_vk_co
+     if (src1_type == GGML_TYPE_Q8_1) {
+         vk_matmul_pipeline pipelines = ctx->device->pipeline_dequant_mul_mat_mat_id_q8_1[src0_type].f32acc;
+ 
+-        if (pipelines->s == nullptr && pipelines->m == nullptr && pipelines->l == nullptr) {
++        if (pipelines->is_empty()) {
+             return nullptr;
+         }
+ 
+@@ -5264,16 +5269,17 @@ static vk_matmul_pipeline ggml_vk_get_mul_mat_mat_id_pipeline(ggml_backend_vk_co
+             return nullptr;
+     }
+ 
++    vk_matmul_pipeline2& mmp = ctx->device->pipeline_dequant_mul_mat_mat_id[src0_type];
+     // XXX TODO 'prec' is not actually allowed in mul_mat_id.
+     bool prefer_fp16acc = ctx->device->fp16 /*&& prec == GGML_PREC_DEFAULT*/;
+-    bool support_fp16acc = ctx->device->pipeline_dequant_mul_mat_mat_id[src0_type].f16acc != nullptr;
+-    bool support_fp32acc = ctx->device->pipeline_dequant_mul_mat_mat_id[src0_type].f32acc != nullptr;
++    bool support_fp16acc = !mmp.f16acc->is_empty();
++    bool support_fp32acc = !mmp.f32acc->is_empty();
+ 
+     if (support_fp16acc && (prefer_fp16acc || !support_fp32acc)) {
+-        return ctx->device->pipeline_dequant_mul_mat_mat_id[src0_type].f16acc;
++        return mmp.f16acc;
+     } else {
+         GGML_ASSERT(support_fp32acc);
+-        return ctx->device->pipeline_dequant_mul_mat_mat_id[src0_type].f32acc;
++        return mmp.f32acc;
+     }
+ }
+ 
diff --git a/llm/memory.go b/llm/memory.go
deleted file mode 100644
index 15558109..00000000
--- a/llm/memory.go
+++ /dev/null
@@ -1,516 +0,0 @@
-package llm
-
-import (
-	"fmt"
-	"log/slog"
-	"os"
-	"slices"
-	"sort"
-	"strings"
-
-	"github.com/ollama/ollama/api"
-	"github.com/ollama/ollama/envconfig"
-	"github.com/ollama/ollama/format"
-	"github.com/ollama/ollama/fs/ggml"
-	"github.com/ollama/ollama/ml"
-)
-
-// pickBestFullFitByLibrary will try to find the optimal placement of the model in the available GPUs where the model fully fits
-// The list of GPUs returned will always be the same brand (library)
-// If the model can not be fit fully within the available GPU(s) nil is returned
-func pickBestFullFitByLibrary(f *ggml.GGML, modelPath string, projectors []string, adapters []string, opts api.Options, gpus []ml.DeviceInfo, numParallel int) []ml.DeviceInfo {
-	for _, gl := range ml.ByLibrary(gpus) {
-		sgl := append(make([]ml.DeviceInfo, 0, len(gl)), gl...)
-
-		// TODO - potentially sort by performance capability, existing models loaded, etc.
-		// TODO - Eliminate any GPUs that already have envconfig.MaxRunners loaded on them
-		// Note: at present, this will favor most current available VRAM descending and ignoring faster GPU speed in mixed setups
-		sort.Sort(sort.Reverse(ml.ByFreeMemory(sgl)))
-
-		if !envconfig.SchedSpread() {
-			// Try to pack into as few GPUs as possible, starting from 1 GPU
-			for numGPUs := 1; numGPUs <= len(sgl); numGPUs++ {
-				gpuSubset := sgl[:numGPUs]
-				ok, estimatedVRAM := predictServerFit(gpuSubset, f, adapters, projectors, opts, numParallel)
-
-				if ok {
-					slog.Info("new model will fit in available VRAM across minimum required GPUs, loading",
-						"model", modelPath,
-						"library", sgl[0].Library,
-						"parallel", numParallel,
-						"required", format.HumanBytes2(estimatedVRAM),
-						"gpus", numGPUs)
-					return gpuSubset
-				}
-			}
-		} else {
-			// TODO future refinements
-			// - if multiple Libraries, see if any single GPU in any Library will fit
-			// - try subsets of GPUs instead of just falling back to 1 or all in a family
-
-			// Now try all the GPUS (OLLAMA_SCHED_SPREAD is set)
-			if ok, estimatedVRAM := predictServerFit(sgl, f, adapters, projectors, opts, numParallel); ok {
-				slog.Info("new model will fit in available VRAM, loading",
-					"model", modelPath,
-					"library", sgl[0].Library,
-					"parallel", numParallel,
-					"required", format.HumanBytes2(estimatedVRAM),
-					"gpus", len(sgl))
-				return sgl
-			}
-		}
-	}
-	return nil
-}
-
-// If multiple Libraries are detected, pick the Library which loads the most layers for the model
-func pickBestPartialFitByLibrary(f *ggml.GGML, projectors []string, adapters []string, opts api.Options, gpus []ml.DeviceInfo, numParallel int) []ml.DeviceInfo {
-	byLibrary := ml.ByLibrary(gpus)
-	if len(byLibrary) <= 1 {
-		return gpus
-	}
-	var bestEstimate uint64
-	var bestFit int
-	for i, gl := range byLibrary {
-		_, estimatedVRAM := predictServerFit(gl, f, adapters, projectors, opts, numParallel)
-		if estimatedVRAM > bestEstimate {
-			bestEstimate = estimatedVRAM
-			bestFit = i
-		}
-	}
-	return byLibrary[bestFit]
-}
-
-// This algorithm looks for a complete fit to determine if we need to unload other models
-func predictServerFit(allGpus []ml.DeviceInfo, f *ggml.GGML, adapters, projectors []string, opts api.Options, numParallel int) (bool, uint64) {
-	// Split up the GPUs by type and try them
-	var estimatedVRAM uint64
-	for _, gpus := range ml.ByLibrary(allGpus) {
-		var layerCount int
-		estimate := estimateGPULayers(gpus, f, projectors, opts, numParallel)
-		layerCount, estimatedVRAM = estimate.Layers, estimate.VRAMSize
-		if opts.NumGPU < 0 {
-			if layerCount > 0 && layerCount >= int(f.KV().BlockCount()+1) {
-				return true, estimatedVRAM
-			}
-		} else {
-			if layerCount > 0 && layerCount >= opts.NumGPU {
-				return true, estimatedVRAM
-			}
-		}
-	}
-	return false, estimatedVRAM
-}
-
-func verifyCPUFit(f *ggml.GGML, modelPath string, projectors []string, adapters []string, opts api.Options, systemInfo ml.SystemInfo, numParallel int) bool {
-	estimate := estimateGPULayers(nil, f, projectors, opts, numParallel)
-	if estimate.TotalSize > systemInfo.FreeMemory {
-		return false
-	}
-	slog.Info("new model will fit in available system memory for CPU inference, loading",
-		"model", modelPath,
-		"parallel", numParallel,
-		"required", format.HumanBytes2(estimate.TotalSize),
-	)
-	return true
-}
-
-type MemoryEstimate struct {
-	// How many layers we predict we can load
-	Layers int
-
-	// The size of the graph which occupies the main GPU
-	Graph uint64
-
-	// How much VRAM will be allocated given the number of layers we predict
-	VRAMSize uint64
-
-	// The total size of the model if loaded into VRAM.  If all layers are loaded, VRAMSize == TotalSize
-	TotalSize uint64
-
-	// For multi-GPU scenarios, this provides the tensor split parameter
-	TensorSplit []int
-
-	// For multi-GPU scenarios, this is the size in bytes per GPU
-	GPUSizes []uint64
-
-	// internal fields for logging purposes
-	inferenceLibrary    string
-	layersRequested     int
-	layersModel         int
-	availableList       []string
-	kv                  uint64
-	allocationsList     []string
-	memoryWeights       uint64
-	memoryLayerOutput   uint64
-	graphFullOffload    uint64
-	graphPartialOffload uint64
-
-	projectorWeights, projectorGraph uint64
-}
-
-// Given a model and one or more GPU targets, predict how many layers and bytes we can load, and the total size
-// The GPUs provided must all be the same Library
-func estimateGPULayers(gpus []ml.DeviceInfo, f *ggml.GGML, projectors []string, opts api.Options, numParallel int) MemoryEstimate {
-	// Graph size for a partial offload, applies to all GPUs
-	var graphPartialOffload uint64
-
-	// Graph size when all layers are offloaded, applies to all GPUs
-	var graphFullOffload uint64
-
-	// Final graph offload once we know full or partial
-	var graphOffload uint64
-
-	// Projectors loaded into GPU0 only
-	var llamaEngineProjectorWeights uint64
-
-	// Projectors loaded with output layer
-	var ollamaEngineProjectorWeights uint64
-	var ollamaEngineProjectorGraph uint64
-
-	// Conditional output size on GPU 0
-	var memoryLayerOutput uint64
-
-	// The sizes of a layer
-	var layerSize uint64
-
-	// The sum of all the layer sizes (just for logging)
-	var memoryWeights uint64
-
-	// True if all the layers are loaded
-	var fullyLoaded bool
-
-	// Overflow that didn't fit into the GPU
-	var overflow uint64
-
-	overhead := envconfig.GpuOverhead()
-	availableList := make([]string, len(gpus))
-	libraries := []string{}
-	for i, gpu := range gpus {
-		availableList[i] = format.HumanBytes2(gpu.FreeMemory)
-		if !slices.Contains(libraries, gpu.Library) {
-			libraries = append(libraries, gpu.Library)
-		}
-	}
-	if len(libraries) == 0 {
-		libraries = []string{"cpu"}
-	}
-	slog.Debug("evaluating", "library", strings.Join(libraries, ","), "gpu_count", len(gpus), "available", availableList)
-
-	for _, projector := range projectors {
-		llamaEngineProjectorWeights += projectorMemoryRequirements(projector)
-	}
-	if llamaEngineProjectorWeights == 0 {
-		ollamaEngineProjectorWeights, ollamaEngineProjectorGraph = f.VisionGraphSize()
-	}
-
-	layers := f.Tensors().GroupLayers()
-	// add one layer worth of memory as a buffer
-	if blk0, ok := layers["blk.0"]; ok {
-		layerSize = blk0.Size()
-	} else {
-		slog.Warn("model missing blk.0 layer size")
-	}
-
-	useFlashAttention := envconfig.FlashAttention(f.FlashAttention()) &&
-		ml.FlashAttentionSupported(gpus) &&
-		f.SupportsFlashAttention()
-
-	var kvct string
-	if useFlashAttention {
-		requested := strings.ToLower(envconfig.KvCacheType())
-		if f.SupportsKVCacheType(requested) {
-			kvct = requested
-		}
-	}
-
-	kv, graphPartialOffload, graphFullOffload := f.GraphSize(uint64(opts.NumCtx), uint64(min(opts.NumCtx, opts.NumBatch)), numParallel, kvct, useFlashAttention)
-
-	if len(kv) > 0 {
-		layerSize += kv[0]
-	}
-
-	var kvTotal uint64
-	for _, kvLayer := range kv {
-		kvTotal += kvLayer
-	}
-
-	if graphPartialOffload == 0 {
-		headsKV := f.KV().HeadCountKVMin()
-		if headsKV == 0 {
-			headsKV = 1
-		}
-		gqa := f.KV().HeadCountMax() / headsKV
-		graphPartialOffload = gqa * kvTotal / 6
-	}
-	if graphFullOffload == 0 {
-		graphFullOffload = graphPartialOffload
-	}
-
-	// on metal there's no partial offload overhead
-	if len(gpus) > 0 && gpus[0].Library == "Metal" {
-		graphPartialOffload = graphFullOffload
-	} else if len(gpus) > 1 {
-		// multigpu should always use the partial graph size
-		graphFullOffload = graphPartialOffload
-	}
-
-	// Output layer handled at the end if we have space
-	if layer, ok := layers["output_norm"]; ok {
-		memoryLayerOutput += layer.Size()
-	}
-	if layer, ok := layers["output"]; ok {
-		memoryLayerOutput += layer.Size()
-	} else if layer, ok := layers["token_embd"]; ok {
-		memoryLayerOutput += layer.Size()
-	}
-
-	gpuZeroOverhead := llamaEngineProjectorWeights
-
-	// Reduce set of GPUs to only those that have sufficient space to fit overhead and at least one layer
-	var layerCount int
-	tensorSplit := make([]int, len(gpus))
-	gpuAllocations := make([]uint64, len(gpus))
-	type gs struct {
-		i int
-		g *ml.DeviceInfo
-	}
-	gpusWithSpace := []gs{}
-	for i := range gpus {
-		var gzo uint64
-		if len(gpusWithSpace) == 0 {
-			gzo = gpuZeroOverhead
-		}
-		// Only include GPUs that can fit the graph, gpu minimum, the layer buffer and at least more layer
-		if gpus[i].FreeMemory < overhead+gzo+max(graphPartialOffload, graphFullOffload)+gpus[i].MinimumMemory()+2*layerSize {
-			slog.Debug("gpu has too little memory to allocate any layers",
-				"id", gpus[i].ID,
-				"library", gpus[i].Library,
-				"compute", gpus[i].Compute(),
-				"driver", fmt.Sprintf("%d.%d", gpus[i].DriverMajor, gpus[i].DriverMinor),
-				"name", gpus[i].Name,
-				"total", format.HumanBytes2(gpus[i].TotalMemory),
-				"available", format.HumanBytes2(gpus[i].FreeMemory),
-				"minimum_memory", gpus[i].MinimumMemory,
-				"layer_size", format.HumanBytes2(layerSize),
-				"gpu_zer_overhead", format.HumanBytes2(gzo),
-				"partial_offload", format.HumanBytes2(graphPartialOffload),
-				"full_offload", format.HumanBytes2(graphFullOffload),
-			)
-			continue
-		}
-		gpusWithSpace = append(gpusWithSpace, gs{i, &gpus[i]})
-		gpuAllocations[i] += gpus[i].MinimumMemory() + layerSize // We hold off on graph until we know partial vs. full
-	}
-
-	var gpuZeroID int
-	if len(gpusWithSpace) > 0 {
-		gpuZeroID = gpusWithSpace[0].i
-		gpuAllocations[gpuZeroID] += gpuZeroOverhead
-	} else {
-		overflow += gpuZeroOverhead
-	}
-
-	// For all the layers, find where they can fit on the GPU(s)
-	for i := int(f.KV().BlockCount()) - 1; i >= 0; i-- {
-		// Some models have inconsistent layer sizes
-		if blk, ok := layers[fmt.Sprintf("blk.%d", i)]; ok {
-			layerSize = blk.Size()
-			layerSize += kv[i]
-			memoryWeights += blk.Size()
-		}
-
-		if opts.NumGPU >= 0 && layerCount >= opts.NumGPU {
-			// Stop allocating on GPU(s) once we hit the users target NumGPU
-			overflow += layerSize
-			continue
-		}
-
-		// distribute the layers across the GPU(s) that have space
-		for j := len(gpusWithSpace); j > 0; j-- {
-			g := gpusWithSpace[i%j]
-			used := gpuAllocations[g.i] + max(graphPartialOffload, graphFullOffload)
-			if g.g.FreeMemory > overhead+used+layerSize {
-				gpuAllocations[g.i] += layerSize
-				tensorSplit[g.i]++
-				layerCount++
-				break
-			} else {
-				gpusWithSpace = append(gpusWithSpace[:i%j], gpusWithSpace[i%j+1:]...)
-			}
-		}
-
-		if len(gpusWithSpace) == 0 {
-			overflow += layerSize
-		}
-	}
-	if layerCount >= int(f.KV().BlockCount()) {
-		fullyLoaded = true
-	}
-
-	// Determine if we need to consider output then find where it fits
-	memoryLastLayer := memoryLayerOutput + ollamaEngineProjectorWeights + ollamaEngineProjectorGraph
-	if memoryLastLayer > 0 {
-		if opts.NumGPU < 0 || layerCount < opts.NumGPU {
-			for j := len(gpusWithSpace); j > 0; j-- {
-				g := gpusWithSpace[layerCount%j]
-				used := gpuAllocations[g.i] + max(graphPartialOffload, graphFullOffload)
-				if g.g.FreeMemory > overhead+used+memoryLastLayer {
-					gpuAllocations[g.i] += memoryLastLayer
-					tensorSplit[g.i]++
-					layerCount++
-					break
-				}
-			}
-		}
-
-		if layerCount < int(f.KV().BlockCount())+1 {
-			fullyLoaded = false
-			overflow += memoryLastLayer
-		}
-	}
-
-	// Add the applicable (full or partial) graph allocations
-	for i := range gpus {
-		if tensorSplit[i] <= 0 {
-			continue
-		}
-		if fullyLoaded {
-			gpuAllocations[i] += graphFullOffload
-		} else {
-			gpuAllocations[i] += graphPartialOffload
-		}
-	}
-	if fullyLoaded {
-		graphOffload = graphFullOffload
-	} else {
-		graphOffload = graphPartialOffload
-	}
-
-	// Summaries for the log
-	var memoryRequiredPartial, memoryRequiredTotal uint64
-	for i := range gpuAllocations {
-		memoryRequiredPartial += gpuAllocations[i]
-	}
-	memoryRequiredTotal = memoryRequiredPartial + overflow
-
-	allocationsList := []string{}
-	for _, a := range gpuAllocations {
-		allocationsList = append(allocationsList, format.HumanBytes2(a))
-	}
-
-	estimate := MemoryEstimate{
-		TotalSize: memoryRequiredTotal,
-		Layers:    0,
-		Graph:     0,
-		VRAMSize:  0,
-		GPUSizes:  []uint64{},
-
-		inferenceLibrary:    strings.Join(libraries, ","),
-		layersRequested:     opts.NumGPU,
-		layersModel:         int(f.KV().BlockCount()) + 1,
-		availableList:       availableList,
-		kv:                  kvTotal,
-		allocationsList:     allocationsList,
-		memoryWeights:       memoryWeights,
-		memoryLayerOutput:   memoryLayerOutput,
-		graphFullOffload:    graphFullOffload,
-		graphPartialOffload: graphPartialOffload,
-		projectorWeights:    llamaEngineProjectorWeights + ollamaEngineProjectorWeights,
-		projectorGraph:      ollamaEngineProjectorGraph,
-	}
-
-	if len(gpus) == 0 {
-		return estimate
-	}
-	if layerCount == 0 {
-		slog.Debug("insufficient VRAM to load any model layers")
-		return estimate
-	}
-	estimate.Layers = layerCount
-	estimate.Graph = graphOffload
-	estimate.VRAMSize = memoryRequiredPartial
-	estimate.TotalSize = memoryRequiredTotal
-	estimate.TensorSplit = tensorSplit
-	estimate.GPUSizes = gpuAllocations
-	return estimate
-}
-
-func (m MemoryEstimate) LogValue() slog.Value {
-	attrs := []slog.Attr{
-		slog.String("library", m.inferenceLibrary),
-		slog.Group(
-			"layers",
-			// requested number of layers to offload
-			"requested", m.layersRequested,
-			// The number of layers the model has (including output)
-			"model", m.layersModel,
-			// estimated number of layers that can be offloaded
-			"offload", m.Layers,
-			// multi-gpu split for tensors
-			"split", m.TensorSplit,
-		),
-		slog.Group(
-			"memory",
-			// memory available by GPU for offloading
-			"available", m.availableList,
-			"gpu_overhead", format.HumanBytes2(envconfig.GpuOverhead()),
-			slog.Group(
-				"required",
-				// memory required for full offloading
-				"full", format.HumanBytes2(m.TotalSize),
-				// memory required to offload layers.estimate layers
-				"partial", format.HumanBytes2(m.VRAMSize),
-				// memory of KV cache
-				"kv", format.HumanBytes2(m.kv),
-				// Allocations across the GPUs
-				"allocations", m.allocationsList,
-			),
-			slog.Group(
-				"weights",
-				// memory of the weights
-				"total", format.HumanBytes2(m.memoryWeights+m.memoryLayerOutput),
-				// memory of repeating layers
-				"repeating", format.HumanBytes2(m.memoryWeights),
-				// memory of non-repeating layers
-				"nonrepeating", format.HumanBytes2(m.memoryLayerOutput),
-			),
-			slog.Group(
-				"graph",
-				// memory of graph when fully offloaded
-				"full", format.HumanBytes2(m.graphFullOffload),
-				// memory of graph when not fully offloaded
-				"partial", format.HumanBytes2(m.graphPartialOffload),
-			),
-		),
-	}
-
-	if m.projectorWeights > 0 {
-		attrs = append(attrs, slog.Group(
-			"projector",
-			"weights", format.HumanBytes2(m.projectorWeights),
-			"graph", format.HumanBytes2(m.projectorGraph),
-		))
-	}
-
-	return slog.GroupValue(attrs...)
-}
-
-func projectorMemoryRequirements(filename string) (weights uint64) {
-	file, err := os.Open(filename)
-	if err != nil {
-		return 0
-	}
-	defer file.Close()
-
-	ggml, err := ggml.Decode(file, 1024)
-	if err != nil {
-		return 0
-	}
-
-	for _, layer := range ggml.Tensors().GroupLayers() {
-		weights += layer.Size()
-	}
-
-	return weights
-}
diff --git a/llm/memory_test.go b/llm/memory_test.go
deleted file mode 100644
index fce17b9c..00000000
--- a/llm/memory_test.go
+++ /dev/null
@@ -1,130 +0,0 @@
-package llm
-
-import (
-	"bytes"
-	"fmt"
-	"os"
-	"testing"
-
-	"github.com/stretchr/testify/assert"
-	"github.com/stretchr/testify/require"
-
-	"github.com/ollama/ollama/api"
-	"github.com/ollama/ollama/format"
-	"github.com/ollama/ollama/fs/ggml"
-	"github.com/ollama/ollama/ml"
-)
-
-func TestEstimateGPULayers(t *testing.T) {
-	t.Setenv("OLLAMA_DEBUG", "1")
-	t.Setenv("OLLAMA_KV_CACHE_TYPE", "") // Ensure default f16
-	t.Setenv("OLLAMA_CONTEXT_LENGTH", "2048")
-
-	modelName := "dummy"
-	f, err := os.CreateTemp(t.TempDir(), modelName)
-	require.NoError(t, err)
-	defer f.Close()
-	inputLayerCount := 5
-
-	tensors := []*ggml.Tensor{
-		{Name: "blk.0.attn.weight", Kind: uint32(0), Offset: uint64(0), Shape: []uint64{1, 1, 1, 1}, WriterTo: bytes.NewReader(make([]byte, 32))},
-		{Name: "blk.1.attn.weight", Kind: uint32(0), Offset: uint64(0), Shape: []uint64{1, 1, 1, 1}, WriterTo: bytes.NewReader(make([]byte, 32))},
-		{Name: "blk.2.attn.weight", Kind: uint32(0), Offset: uint64(0), Shape: []uint64{1, 1, 1, 1}, WriterTo: bytes.NewReader(make([]byte, 32))},
-		{Name: "blk.3.attn.weight", Kind: uint32(0), Offset: uint64(0), Shape: []uint64{1, 1, 1, 1}, WriterTo: bytes.NewReader(make([]byte, 32))},
-		{Name: "blk.4.attn.weight", Kind: uint32(0), Offset: uint64(0), Shape: []uint64{1, 1, 1, 1}, WriterTo: bytes.NewReader(make([]byte, 32))},
-		{Name: "output.weight", Kind: uint32(0), Offset: uint64(0), Shape: []uint64{1, 1, 1, 1}, WriterTo: bytes.NewReader(make([]byte, 32))},
-	}
-	assert.Len(t, tensors, inputLayerCount+1)
-	err = ggml.WriteGGUF(f, ggml.KV{
-		"general.architecture":          "llama",
-		"llama.context_length":          uint32(32),
-		"llama.embedding_length":        uint32(4096),
-		"llama.block_count":             uint32(inputLayerCount),
-		"llama.attention.head_count":    uint32(32),
-		"llama.attention.head_count_kv": uint32(32),
-		"tokenizer.ggml.tokens":         []string{" "},
-		"tokenizer.ggml.scores":         []float32{0},
-		"tokenizer.ggml.token_type":     []int32{0},
-	}, tensors)
-	require.NoError(t, err)
-
-	ggml, err := LoadModel(f.Name(), 0)
-	if err != nil {
-		t.Fatal(err)
-	}
-
-	// Simple CPU scenario
-	gpus := []ml.DeviceInfo{}
-	projectors := []string{}
-	opts := api.DefaultOptions()
-	t.Run("cpu", func(t *testing.T) {
-		estimate := estimateGPULayers(gpus, ggml, projectors, opts, 1)
-		assert.Equal(t, 0, estimate.Layers)
-		assert.Equal(t, uint64(0), estimate.Graph)
-	})
-
-	// derived from the dummy ggml file above
-	graphPartialOffload := uint64(202377216)
-	graphFullOffload := uint64(171968512)
-	layerSize := uint64(33554436)
-	projectorSize := uint64(0)
-	memoryLayerOutput := uint64(4)
-
-	// Dual CUDA scenario with asymmetry
-	gpuMinimumMemory := uint64(457 * format.MebiByte)
-	gpus = []ml.DeviceInfo{
-		{
-			DeviceID: ml.DeviceID{
-				Library: "CUDA",
-			},
-		},
-		{
-			DeviceID: ml.DeviceID{
-				Library: "CUDA",
-			},
-		},
-	}
-	// Nested array: GPU0 layer space, GPU1 layer space, expected gpu0, expected gpu1
-	for i, s := range []struct {
-		layer0, layer1   uint64
-		expect0, expect1 int
-	}{
-		{1, 1, 1, 1},
-		{2, 1, 2, 1},
-		{2, 2, 2, 2},
-		{1, 2, 1, 2},
-		{3, 3, 3, 3},
-		{4, 4, 3, 3},
-		{6, 6, 3, 3},
-		{0, 3, 0, 3},
-	} {
-		t.Run(fmt.Sprintf("%v", s), func(t *testing.T) {
-			gpus[0].FreeMemory = 0
-			gpus[1].FreeMemory = 0
-			gpus[0].FreeMemory += projectorSize
-			if s.layer0 > 0 {
-				gpus[0].FreeMemory += memoryLayerOutput
-			} else {
-				gpus[1].FreeMemory += memoryLayerOutput
-			}
-			gpus[0].FreeMemory += gpuMinimumMemory + layerSize + s.layer0*layerSize + 1
-			gpus[1].FreeMemory += gpuMinimumMemory + layerSize + s.layer1*layerSize + 1
-			gpus[0].FreeMemory += max(graphFullOffload, graphPartialOffload)
-			gpus[1].FreeMemory += max(graphFullOffload, graphPartialOffload)
-			estimate := estimateGPULayers(gpus, ggml, projectors, opts, 1)
-			assert.Equal(t, s.expect0+s.expect1, estimate.Layers, "scenario %d: %v", i, s)
-			assert.Equal(t, []int{s.expect0, s.expect1}, estimate.TensorSplit, "scenario %d: %v", i, s)
-			var layerSums uint64
-			for _, b := range estimate.GPUSizes {
-				layerSums += b
-			}
-			if estimate.Layers < inputLayerCount+1 {
-				assert.Less(t, estimate.VRAMSize, estimate.TotalSize, "scenario %d: %v %+v", i, s, estimate)
-				assert.Equal(t, estimate.VRAMSize, layerSums, "scenario %d: %v %+v", i, s, estimate)
-			} else {
-				assert.Equal(t, estimate.VRAMSize, estimate.TotalSize, "scenario %d: %v %+v", i, s, estimate)
-				assert.Equal(t, estimate.TotalSize, layerSums, "scenario %d: %v %+v", i, s, estimate)
-			}
-		})
-	}
-}
diff --git a/llm/server.go b/llm/server.go
index 4f7c3760..4eaa88df 100644
--- a/llm/server.go
+++ b/llm/server.go
@@ -84,25 +84,21 @@ type LlamaServer interface {
 
 // llmServer is an instance of a runner hosting a single model
 type llmServer struct {
-	port        int
-	cmd         *exec.Cmd
-	done        chan error // Channel to signal when the process exits
-	status      *StatusWriter
-	options     api.Options
-	numParallel int
-	modelPath   string
+	port      int
+	cmd       *exec.Cmd
+	done      chan error // Channel to signal when the process exits
+	status    *StatusWriter
+	options   api.Options
+	modelPath string
 
-	loadRequest LoadRequest // Parameters used to initialize the runner
+	loadRequest LoadRequest       // Parameters used to initialize the runner
+	mem         *ml.BackendMemory // Memory allocations for this model
 
 	// llamaModel is an instance of the cgo llama.cpp model definition
 	// nil if this server is running the new engine
 	llamaModel     *llama.Model
 	llamaModelLock *sync.Mutex
 
-	// textProcessor handles text encoding/decoding for the model in the Ollama engine
-	// nil if this server is running the llama.cpp based engine
-	textProcessor model.TextProcessor
-
 	totalLayers  uint64
 	loadStart    time.Time // Record how long it took the model to load
 	loadProgress float32
@@ -113,15 +109,13 @@ type llmServer struct {
 type llamaServer struct {
 	llmServer
 
-	ggml     *ggml.GGML
-	gpus     []ml.DeviceInfo // The set of GPUs covered by the memory estimate
-	estimate MemoryEstimate
+	ggml *ggml.GGML
 }
 
 type ollamaServer struct {
 	llmServer
 
-	mem *ml.BackendMemory
+	textProcessor model.TextProcessor // textProcessor handles text encoding/decoding
 }
 
 // LoadModel will load a model from disk. The model must be in the GGML format.
@@ -245,8 +239,6 @@ func NewLlamaServer(systemInfo ml.SystemInfo, gpus []ml.DeviceInfo, modelPath st
 		loadRequest:    loadRequest,
 		llamaModel:     llamaModel,
 		llamaModelLock: &sync.Mutex{},
-		textProcessor:  textProcessor,
-		numParallel:    numParallel,
 		sem:            semaphore.NewWeighted(int64(numParallel)),
 		totalLayers:    f.KV().BlockCount() + 1,
 		loadStart:      time.Now(),
@@ -281,7 +273,7 @@ func NewLlamaServer(systemInfo ml.SystemInfo, gpus []ml.DeviceInfo, modelPath st
 	}()
 
 	if textProcessor != nil {
-		return &ollamaServer{llmServer: s}, nil
+		return &ollamaServer{llmServer: s, textProcessor: textProcessor}, nil
 	} else {
 		return &llamaServer{llmServer: s, ggml: f}, nil
 	}
@@ -463,169 +455,226 @@ type LoadResponse struct {
 
 var ErrLoadRequiredFull = errors.New("unable to load full model on GPU")
 
-func (s *llamaServer) Load(ctx context.Context, systemInfo ml.SystemInfo, gpus []ml.DeviceInfo, requireFull bool) ([]ml.DeviceID, error) {
-	systemTotalMemory := systemInfo.TotalMemory
-	systemFreeMemory := systemInfo.FreeMemory
-	systemSwapFreeMemory := systemInfo.FreeSwap
-	slog.Info("system memory", "total", format.HumanBytes2(systemTotalMemory), "free", format.HumanBytes2(systemFreeMemory), "free_swap", format.HumanBytes2(systemSwapFreeMemory))
+func (s *llamaServer) Load(ctx context.Context, systemInfo ml.SystemInfo, systemGPUs []ml.DeviceInfo, requireFull bool) ([]ml.DeviceID, error) {
+	slog.Info("loading model", "model layers", s.totalLayers, "requested", s.options.NumGPU)
 
-	if len(gpus) == 0 || s.options.NumGPU == 0 {
-		if !verifyCPUFit(s.ggml, s.modelPath, []string{s.loadRequest.ProjectorPath}, s.loadRequest.LoraPath, s.options, systemInfo, s.numParallel) {
-			slog.Info("model requires more memory than is currently available, evicting a model to make space", "estimate", s.estimate)
-			return nil, fmt.Errorf("model requires more system memory than is currently available %w", ErrLoadRequiredFull)
+	gpus := append(make([]ml.DeviceInfo, 0, len(systemGPUs)), systemGPUs...)
+
+	// Synthesize memory allocation information based on our estimates
+	s.mem = &ml.BackendMemory{CPU: ml.DeviceMemory{
+		Name:    "CPU",
+		Weights: make([]uint64, s.totalLayers),
+		Cache:   make([]uint64, s.totalLayers),
+	}, GPUs: make([]ml.DeviceMemory, len(gpus))}
+
+	for i := range s.mem.GPUs {
+		s.mem.GPUs[i].Name = gpus[i].Name
+		s.mem.GPUs[i].DeviceID = gpus[i].DeviceID
+		s.mem.GPUs[i].Weights = make([]uint64, s.totalLayers)
+		s.mem.GPUs[i].Cache = make([]uint64, s.totalLayers)
+	}
+
+	kv, graphPartialOffload, graphFullOffload := s.ggml.GraphSize(uint64(s.options.NumCtx), uint64(s.loadRequest.BatchSize),
+		s.loadRequest.Parallel, s.loadRequest.KvCacheType, s.loadRequest.FlashAttention)
+
+	// Use the size of one layer as a buffer
+	layers := s.ggml.Tensors().GroupLayers()
+	if blk0, ok := layers["blk.0"]; ok {
+		for i := range gpus {
+			gpus[i].FreeMemory -= blk0.Size() + kv[0]
 		}
 	} else {
-		g := pickBestFullFitByLibrary(s.ggml, s.modelPath, []string{s.loadRequest.ProjectorPath}, s.loadRequest.LoraPath, s.options, gpus, s.numParallel)
-		if g == nil {
-			if !requireFull {
-				g = pickBestPartialFitByLibrary(s.ggml, []string{s.loadRequest.ProjectorPath}, s.loadRequest.LoraPath, s.options, gpus, s.numParallel)
-			} else {
-				slog.Info("model requires more memory than is currently available, evicting a model to make space", "estimate", s.estimate)
-				return nil, ErrLoadRequiredFull
+		slog.Warn("model missing blk.0 layer size")
+	}
+
+	// Assign all the layers to the CPU for now, they will get reassigned later
+	for i := range s.ggml.KV().BlockCount() {
+		if blk, ok := layers[fmt.Sprintf("blk.%d", i)]; ok {
+			s.mem.CPU.Weights[i] = blk.Size()
+			s.mem.CPU.Cache[i] += kv[i]
+		}
+	}
+
+	// We historically haven't included InputWeights in the model size
+	var outputWeights uint64
+	if layer, ok := layers["output_norm"]; ok {
+		outputWeights += layer.Size()
+	}
+	if layer, ok := layers["output"]; ok {
+		outputWeights += layer.Size()
+	} else if layer, ok := layers["token_embd"]; ok {
+		outputWeights += layer.Size()
+	}
+	s.mem.CPU.Weights[s.totalLayers-1] = outputWeights
+
+	// The vision projector is always loaded on the first GPU if available.
+	// This can't be assigned by us, so just subtract it from free space
+	projectorGPU := -1
+	var projectorWeights uint64
+	if len(gpus) > 0 {
+		for _, projector := range s.loadRequest.LoraPath {
+			projectorWeights += projectorMemoryRequirements(projector)
+		}
+
+		// llama.cpp uses the first discrete GPU if available, otherwise the first iGPU
+		firstIntegrated := -1
+		for i := range gpus {
+			if !gpus[i].Integrated {
+				projectorGPU = i
+				break
+			}
+			if firstIntegrated == -1 {
+				firstIntegrated = i
 			}
 		}
-		gpus = g
-	}
-
-	s.estimate = estimateGPULayers(gpus, s.ggml, []string{s.loadRequest.ProjectorPath}, s.options, s.numParallel)
-
-	if len(gpus) >= 1 {
-		switch {
-		case s.options.NumGPU == 0:
-			gpus = []ml.DeviceInfo{}
-		case gpus[0].Library == "Metal" && s.estimate.VRAMSize > systemInfo.TotalMemory:
-			// disable partial offloading when model is greater than total system memory as this
-			// can lead to locking up the system
-			s.options.NumGPU = 0
-			gpus = []ml.DeviceInfo{}
-		case gpus[0].Library != "Metal" && s.estimate.Layers == 0:
-			// Don't bother loading into the GPU if no layers can fit
-			gpus = []ml.DeviceInfo{}
-		case s.options.NumGPU < 0 && s.estimate.Layers > 0:
-			s.options.NumGPU = s.estimate.Layers
+		if projectorGPU == -1 {
+			projectorGPU = firstIntegrated
 		}
-	} else {
-		s.options.NumGPU = 0
+
+		gpus[projectorGPU].FreeMemory -= projectorWeights
 	}
 
-	// On linux and windows, over-allocating CPU memory will almost always result in an error
-	// Darwin has fully dynamic swap so has no direct concept of free swap space
-	if runtime.GOOS != "darwin" {
-		systemMemoryRequired := s.estimate.TotalSize - s.estimate.VRAMSize
-		available := systemInfo.FreeMemory + systemInfo.FreeSwap
-		if systemMemoryRequired > available {
-			slog.Warn("model request too large for system", "requested", format.HumanBytes2(systemMemoryRequired), "available", format.HumanBytes2(available), "total", format.HumanBytes2(systemInfo.TotalMemory), "free", format.HumanBytes2(systemInfo.FreeMemory), "swap", format.HumanBytes2(systemInfo.FreeSwap))
-			return nil, fmt.Errorf("model requires more system memory (%s) than is available (%s)", format.HumanBytes2(systemMemoryRequired), format.HumanBytes2(available))
+	var kvTotal uint64
+	for _, kvLayer := range kv {
+		kvTotal += kvLayer
+	}
+
+	if graphPartialOffload == 0 {
+		headsKV := s.ggml.KV().HeadCountKVMin()
+		if headsKV == 0 {
+			headsKV = 1
+		}
+		gqa := s.ggml.KV().HeadCountMax() / headsKV
+		graphPartialOffload = gqa * kvTotal / 6
+	}
+	if graphFullOffload == 0 {
+		graphFullOffload = graphPartialOffload
+	}
+
+	// On Metal there's no partial offload overhead
+	if len(gpus) > 0 && gpus[0].Library == "Metal" {
+		graphPartialOffload = graphFullOffload
+	}
+
+	// Create a layout based on the memory data that we've built. The compute graph
+	// for GPUs is iteratively assigned based on the number of GPUs that are required.
+	var gpuLayers ml.GPULayersList
+	for {
+		prevGPULayers := gpuLayers
+
+		var err error
+		gpuLayers, err = s.createLayout(systemInfo, gpus, s.mem, requireFull, 0)
+		if err != nil {
+			return nil, err
+		}
+
+		if len(gpuLayers) > len(prevGPULayers) {
+			for _, gl := range gpuLayers {
+				for i := range s.mem.GPUs {
+					if gl.DeviceID == s.mem.GPUs[i].DeviceID {
+						s.mem.GPUs[i].Graph = max(graphPartialOffload, graphFullOffload)
+						break
+					}
+				}
+			}
+		} else {
+			break
 		}
 	}
 
-	slog.Info("offload", "", s.estimate)
+	// This maintains the historical assignment of graph sizes, though it isn't fully accurate
+	graphSize := graphFullOffload
+	if gpuLayers.Sum() < int(s.totalLayers) {
+		graphSize = graphPartialOffload
+	}
 
-	s.gpus = gpus
-	s.loadRequest.GPULayers = createGPULayers(s.estimate, s.ggml, gpus, s.options.NumGPU)
+	// For all layers that we have assigned to GPUs, move them in the memory data so
+	// that it is reported accurately
+	for _, gl := range gpuLayers {
+		for i := range s.mem.GPUs {
+			if gl.DeviceID == s.mem.GPUs[i].DeviceID {
+				for _, l := range gl.Layers {
+					s.mem.GPUs[i].Weights[l] = s.mem.CPU.Weights[l]
+					s.mem.GPUs[i].Cache[l] = s.mem.CPU.Cache[l]
 
-	// Mmap is only supported on the llama engine
-	if s.textProcessor == nil {
-		s.loadRequest.UseMmap = true
+					s.mem.CPU.Weights[l] = 0
+					s.mem.CPU.Cache[l] = 0
+				}
 
-		// mmap has issues with partial offloading on metal
-		for _, g := range gpus {
-			if g.Library == "Metal" &&
-				uint64(s.options.NumGPU) > 0 &&
-				uint64(s.options.NumGPU) < s.ggml.KV().BlockCount()+1 {
-				s.options.UseMMap = new(bool)
-				*s.options.UseMMap = false
+				s.mem.GPUs[i].Graph = graphSize
+				break
 			}
 		}
+	}
 
-		// Windows CUDA should not use mmap for best performance
-		// Linux  with a model larger than free space, mmap leads to thrashing
-		// For CPU loads we want the memory to be allocated, not FS cache
-		if (runtime.GOOS == "windows" && len(gpus) > 0 && gpus[0].Library == "CUDA" && s.options.UseMMap == nil) ||
-			(runtime.GOOS == "linux" && systemInfo.FreeMemory < s.estimate.TotalSize && s.options.UseMMap == nil) ||
-			(len(gpus) == 0 && s.options.UseMMap == nil) ||
-			(len(gpus) > 0 && gpus[0].Library == "Vulkan" && s.options.UseMMap == nil) ||
-			(s.options.UseMMap != nil && !*s.options.UseMMap) {
-			s.loadRequest.UseMmap = false
+	if projectorGPU > 0 && len(s.mem.GPUs[projectorGPU].Weights) > 0 {
+		s.mem.GPUs[projectorGPU].Weights[s.totalLayers-1] += projectorWeights
+	}
+
+	slog.Debug("memory", "estimate", s.mem)
+	s.mem.Log(slog.LevelInfo)
+
+	// The llama engine uses mmap by default
+	s.loadRequest.UseMmap = true
+
+	// mmap has issues with partial offloading on metal
+	for _, g := range gpus {
+		if g.Library == "Metal" &&
+			uint64(s.options.NumGPU) > 0 &&
+			uint64(s.options.NumGPU) < s.totalLayers {
+			s.options.UseMMap = new(bool)
+			*s.options.UseMMap = false
 		}
 	}
 
+	// Windows CUDA should not use mmap for best performance
+	// Linux  with a model larger than free space, mmap leads to thrashing
+	// For CPU loads we want the memory to be allocated, not FS cache
+	if (runtime.GOOS == "windows" && len(gpus) > 0 && gpus[0].Library == "CUDA" && s.options.UseMMap == nil) ||
+		(runtime.GOOS == "linux" && systemInfo.FreeMemory < s.TotalSize() && s.options.UseMMap == nil) ||
+		(len(gpus) == 0 && s.options.UseMMap == nil) ||
+		(len(gpus) > 0 && gpus[0].Library == "Vulkan" && s.options.UseMMap == nil) ||
+		(s.options.UseMMap != nil && !*s.options.UseMMap) {
+		s.loadRequest.UseMmap = false
+	}
+
 	if err := s.waitUntilRunnerLaunched(ctx); err != nil {
 		return nil, err
 	}
 
+	s.loadRequest.GPULayers = gpuLayers
 	resp, err := s.initModel(ctx, s.loadRequest, LoadOperationCommit)
 	if err != nil {
 		return nil, err
 	}
 
-	// On the Ollama engine, we can print out a summary of the memory allocations.
-	// We don't have this for the llama engine but it does something similar itself.
-	if s.textProcessor != nil {
-		resp.Memory.Log(slog.LevelInfo)
-	}
-
 	if !resp.Success {
-		slog.Warn("failed to allocate memory for model", "memory", resp.Memory)
 		return nil, errors.New("failed to allocate memory for model")
 	}
 
 	// The llama engine does its memory allocations together with model loading, so we
 	// need to wait until it is done to ensure that we have accurate memory data before
 	// loading the next model
-	if s.textProcessor == nil {
-		return uniqueDeviceIDs(s.loadRequest.GPULayers), s.WaitUntilRunning(ctx)
-	} else {
-		return uniqueDeviceIDs(s.loadRequest.GPULayers), nil
-	}
+	return uniqueDeviceIDs(s.loadRequest.GPULayers), s.WaitUntilRunning(ctx)
 }
 
-// createGPULayers maps from the tensor splits assigned by the memory estimates to explicit assignment
-// of particular layers onto GPUs
-func createGPULayers(estimate MemoryEstimate, ggml *ggml.GGML, gpus []ml.DeviceInfo, numGPU int) ml.GPULayersList {
-	if numGPU <= 0 || len(gpus) == 0 {
-		return nil
+func projectorMemoryRequirements(filename string) (weights uint64) {
+	file, err := os.Open(filename)
+	if err != nil {
+		return 0
+	}
+	defer file.Close()
+
+	ggml, err := ggml.Decode(file, 1024)
+	if err != nil {
+		return 0
 	}
 
-	gpuLayers := make(ml.GPULayersList, len(gpus))
-	for i := range gpuLayers {
-		gpuLayers[i].DeviceID = gpus[i].DeviceID
+	for _, layer := range ggml.Tensors().GroupLayers() {
+		weights += layer.Size()
 	}
 
-	var sum float32
-	splits := make([]float32, len(estimate.TensorSplit))
-	// cumulative sum of all splits
-	for i := range splits {
-		sum += float32(estimate.TensorSplit[i])
-		splits[i] = sum
-	}
-
-	if sum <= 0 {
-		return nil
-	}
-
-	// normalize splits
-	for i := range splits {
-		splits[i] /= sum
-	}
-
-	blocks := int(ggml.KV().BlockCount())
-	gpuRangeStart := max(0, blocks-numGPU)
-	gpuRangeStop := min(gpuRangeStart+numGPU, blocks+1)
-	for i := range blocks + 1 {
-		if i < gpuRangeStart || i >= gpuRangeStop {
-			continue
-		}
-
-		index := slices.IndexFunc(splits, func(f float32) bool { return float32(i-gpuRangeStart)/float32(gpuRangeStop-gpuRangeStart) < f })
-		if index < 0 || index >= len(gpus) {
-			continue
-		}
-
-		gpuLayers[index].Layers = append(gpuLayers[index].Layers, i)
-	}
-
-	return gpuLayers
+	return weights
 }
 
 // Load finds the optimal layout of layers to offload on GPUs based on no initial information about the size of the model
@@ -652,23 +701,6 @@ func (s *ollamaServer) Load(ctx context.Context, systemInfo ml.SystemInfo, gpus
 
 	slog.Info("loading model", "model layers", s.totalLayers, "requested", s.options.NumGPU)
 
-	systemTotalMemory := systemInfo.TotalMemory
-	systemFreeMemory := systemInfo.FreeMemory
-	systemSwapFreeMemory := systemInfo.FreeSwap
-	slog.Info("system memory", "total", format.HumanBytes2(systemTotalMemory), "free", format.HumanBytes2(systemFreeMemory), "free_swap", format.HumanBytes2(systemSwapFreeMemory))
-
-	for _, gpu := range gpus {
-		available := gpu.FreeMemory - envconfig.GpuOverhead() - gpu.MinimumMemory()
-		if gpu.FreeMemory < envconfig.GpuOverhead()+gpu.MinimumMemory() {
-			available = 0
-		}
-		slog.Info("gpu memory", "id", gpu.ID, "library", gpu.Library,
-			"available", format.HumanBytes2(available),
-			"free", format.HumanBytes2(gpu.FreeMemory),
-			"minimum", format.HumanBytes2(gpu.MinimumMemory()),
-			"overhead", format.HumanBytes2(envconfig.GpuOverhead()))
-	}
-
 	pastAllocations := make(map[uint64]struct{})
 	var backoff float32
 
@@ -834,25 +866,22 @@ func uniqueDeviceIDs(gpuLayers ml.GPULayersList) []ml.DeviceID {
 // - Calculating how much space each GPU has available for layers, based on free memory and space occupied by the graph
 // - Assigning layers
 // - Ensuring that we don't exceed limits, such as requirements about partial offloading or system memory
-func (s *ollamaServer) createLayout(systemInfo ml.SystemInfo, systemGPUs []ml.DeviceInfo, memory *ml.BackendMemory, requireFull bool, backoff float32) (ml.GPULayersList, error) {
+func (s *llmServer) createLayout(systemInfo ml.SystemInfo, systemGPUs []ml.DeviceInfo, memory *ml.BackendMemory, requireFull bool, backoff float32) (ml.GPULayersList, error) {
 	if memory == nil {
 		memory = &ml.BackendMemory{CPU: ml.DeviceMemory{
 			Weights: make([]uint64, s.totalLayers),
 			Cache:   make([]uint64, s.totalLayers),
 		}}
 	}
-	gpuLayers, layers, err := s.buildLayout(systemGPUs, memory, requireFull, backoff)
-	if err != nil {
-		return nil, err
-	}
-	err = s.verifyLayout(systemInfo, memory, requireFull, gpuLayers, layers)
+	gpuLayers, layers := s.buildLayout(systemGPUs, memory, requireFull, backoff)
+	err := s.verifyLayout(systemInfo, memory, requireFull, gpuLayers, layers)
 	if err != nil {
 		return nil, err
 	}
 	return gpuLayers, nil
 }
 
-func (s *ollamaServer) buildLayout(systemGPUs []ml.DeviceInfo, memory *ml.BackendMemory, requireFull bool, backoff float32) (ml.GPULayersList, []uint64, error) {
+func (s *llmServer) buildLayout(systemGPUs []ml.DeviceInfo, memory *ml.BackendMemory, requireFull bool, backoff float32) (ml.GPULayersList, []uint64) {
 	gpus := append(make([]ml.DeviceInfo, 0, len(systemGPUs)), systemGPUs...)
 	sort.Sort(sort.Reverse(ml.ByFreeMemory(gpus)))
 
@@ -910,11 +939,11 @@ func (s *ollamaServer) buildLayout(systemGPUs []ml.DeviceInfo, memory *ml.Backen
 			gpuLayers = libraryGpuLayers
 		}
 	}
-	return gpuLayers, layers, nil
+	return gpuLayers, layers
 }
 
 // verifyLayout ensures that we don't exceed limits, such as requirements about partial offloading or system memory
-func (s *ollamaServer) verifyLayout(systemInfo ml.SystemInfo, memory *ml.BackendMemory, requireFull bool, gpuLayers ml.GPULayersList, layers []uint64) error {
+func (s *llmServer) verifyLayout(systemInfo ml.SystemInfo, memory *ml.BackendMemory, requireFull bool, gpuLayers ml.GPULayersList, layers []uint64) error {
 	// These sizes will only increase as we go through additional iterations and get additional information.
 	cpuSize := memory.InputWeights + memory.CPU.Graph
 	var vramSize uint64
@@ -942,11 +971,13 @@ nextLayer:
 
 	if requireFull {
 		if gpuLayers.Sum() < len(layers) && (s.options.NumGPU < 0 || gpuLayers.Sum() < s.options.NumGPU) {
+			slog.Info("model requires more memory than is currently available, evicting a model to make space", "loaded layers", gpuLayers.Sum())
 			return ErrLoadRequiredFull
 		}
 
 		if cpuSize > systemInfo.FreeMemory {
-			return ErrLoadRequiredFull
+			slog.Info("model requires more system memory than is currently available, evicting a model to make space", "required", cpuSize, "free", systemInfo.FreeMemory)
+			return fmt.Errorf("model requires more system memory than is currently available %w", ErrLoadRequiredFull)
 		}
 	}
 
@@ -976,6 +1007,13 @@ nextLayer:
 
 // assignLayers packs the maximum number of layers onto the smallest set of GPUs and comes up with a layer assignment
 func assignLayers(layers []uint64, gpus []ml.DeviceInfo, requireFull bool, requestedLayers int, lastUsedGPU int) (gpuLayers ml.GPULayersList) {
+	// If the user is manually overriding parameters, treat all GPUs equally so they split according to VRAM
+	if requestedLayers >= 0 || envconfig.SchedSpread() {
+		for i := range gpus {
+			gpus[i].Integrated = false
+		}
+	}
+
 	// If we can't fit everything then prefer offloading layers other than the output layer
 	for range 2 {
 		// requestedLayers may be -1 if nothing was requested
@@ -1008,33 +1046,38 @@ func assignLayers(layers []uint64, gpus []ml.DeviceInfo, requireFull bool, reque
 
 // findBestFit binary searches to find the smallest capacity factor that can fit
 // the max number of layers. The capacity factor is multiplied by the free space on
-// each GPU and a small one will force even balancing.
+// each GPU and a small one will force even balancing. Higher performance GPUs are
+// used first.
 func findBestFit(layers []uint64, gpus []ml.DeviceInfo, requestedLayers int, forceRequest bool) (gpuLayers ml.GPULayersList) {
-	var high float32 = 1
-	var low float32 = 0
+	for _, gl := range ml.ByPerformance(gpus) {
+		var high float32 = 1
+		var low float32 = 0
 
-	// If we need to fulfill the requested number of layers, pretend we have almost infinite VRAM
-	if requestedLayers >= 0 && forceRequest {
-		high = 1000
-	}
-
-	bestAssignments := greedyFit(layers, gpus, high, requestedLayers)
-	maxNumGPU := bestAssignments.Sum()
-	if maxNumGPU == 0 {
-		return bestAssignments
-	}
-
-	for high-low > 1e-6 {
-		mid := (low + high) / 2
-		assignments := greedyFit(layers, gpus, mid, requestedLayers)
-		if assignments.Sum() == maxNumGPU {
-			high = mid
-			bestAssignments = assignments
-		} else {
-			low = mid
+		// If we need to fulfill the requested number of layers, pretend we have almost infinite VRAM
+		if requestedLayers >= 0 && forceRequest {
+			high = 1000
 		}
+
+		bestAssignments := greedyFit(layers, gl, high, requestedLayers)
+		maxNumGPU := bestAssignments.Sum()
+
+		for high-low > 1e-6 {
+			mid := (low + high) / 2
+			assignments := greedyFit(layers, gl, mid, requestedLayers)
+			if assignments.Sum() == maxNumGPU {
+				high = mid
+				bestAssignments = assignments
+			} else {
+				low = mid
+			}
+		}
+
+		layers = layers[:len(layers)-bestAssignments.Sum()]
+		requestedLayers -= bestAssignments.Sum()
+		gpuLayers = append(bestAssignments, gpuLayers...)
 	}
-	return bestAssignments
+
+	return gpuLayers
 }
 
 // greedyFit assigns layers incrementally to GPUs, spilling over as each runs out of free space
@@ -1362,6 +1405,12 @@ type CompletionRequest struct {
 	Grammar  string // set before sending the request to the subprocess
 	Shift    bool
 	Truncate bool
+
+	// Logprobs specifies whether to include log probabilities in the response
+	Logprobs bool
+
+	// TopLogprobs specifies the number of most likely alternative tokens to return (0-20)
+	TopLogprobs int
 }
 
 // DoneReason represents the reason why a completion response is done
@@ -1387,6 +1436,18 @@ func (d DoneReason) String() string {
 	}
 }
 
+// TokenLogprob represents log probability information for a single token alternative.
+type TokenLogprob struct {
+	Token   string  `json:"token"`
+	Logprob float64 `json:"logprob"`
+}
+
+// Logprob contains log probability information for a generated token.
+type Logprob struct {
+	TokenLogprob
+	TopLogprobs []TokenLogprob `json:"top_logprobs,omitempty"`
+}
+
 type CompletionResponse struct {
 	Content            string        `json:"content"`
 	DoneReason         DoneReason    `json:"done_reason"`
@@ -1395,6 +1456,9 @@ type CompletionResponse struct {
 	PromptEvalDuration time.Duration `json:"prompt_eval_duration"`
 	EvalCount          int           `json:"eval_count"`
 	EvalDuration       time.Duration `json:"eval_duration"`
+
+	// Logprobs contains log probability information if requested
+	Logprobs []Logprob `json:"logprobs,omitempty"`
 }
 
 func (s *llmServer) Completion(ctx context.Context, req CompletionRequest, fn func(CompletionResponse)) error {
@@ -1530,7 +1594,8 @@ func (s *llmServer) Completion(ctx context.Context, req CompletionRequest, fn fu
 
 			if c.Content != "" {
 				fn(CompletionResponse{
-					Content: c.Content,
+					Content:  c.Content,
+					Logprobs: c.Logprobs,
 				})
 			}
 
@@ -1623,68 +1688,59 @@ func (s *llmServer) Embedding(ctx context.Context, input string) ([]float32, err
 	return e.Embedding, nil
 }
 
-type TokenizeRequest struct {
-	Content string `json:"content"`
-}
-
-type TokenizeResponse struct {
-	Tokens []int `json:"tokens"`
-}
-
-func (s *llmServer) Tokenize(ctx context.Context, content string) ([]int, error) {
+func (s *llamaServer) Tokenize(ctx context.Context, content string) ([]int, error) {
 	s.llamaModelLock.Lock()
 	defer s.llamaModelLock.Unlock()
 
-	if s.llamaModel != nil {
-		return s.llamaModel.Tokenize(content, false, true)
+	if s.llamaModel == nil {
+		return nil, fmt.Errorf("no tokenizer configured")
 	}
-	if s.textProcessor != nil {
-		tokens, err := s.textProcessor.Encode(content, false)
-		if err != nil {
-			return nil, err
-		}
-		toks := make([]int, len(tokens))
-		for i, t := range tokens {
-			toks[i] = int(t)
-		}
-		return toks, nil
+
+	return s.llamaModel.Tokenize(content, false, true)
+}
+
+func (s *ollamaServer) Tokenize(ctx context.Context, content string) ([]int, error) {
+	tokens, err := s.textProcessor.Encode(content, false)
+	if err != nil {
+		return nil, err
 	}
-	// not reached
-	return nil, fmt.Errorf("no tokenizer configured")
+
+	toks := make([]int, len(tokens))
+	for i, t := range tokens {
+		toks[i] = int(t)
+	}
+
+	return toks, nil
 }
 
-type DetokenizeRequest struct {
-	Tokens []int `json:"tokens"`
-}
-
-type DetokenizeResponse struct {
-	Content string `json:"content"`
-}
-
-func (s *llmServer) Detokenize(ctx context.Context, tokens []int) (string, error) {
+func (s *llamaServer) Detokenize(ctx context.Context, tokens []int) (string, error) {
 	s.llamaModelLock.Lock()
 	defer s.llamaModelLock.Unlock()
 
-	if s.llamaModel != nil {
-		var resp string
-		for _, token := range tokens {
-			resp += s.llamaModel.TokenToPiece(token)
-		}
-		return resp, nil
+	if s.llamaModel == nil {
+		return "", fmt.Errorf("no tokenizer configured")
 	}
-	if s.textProcessor != nil {
-		toks := make([]int32, len(tokens))
-		for i, t := range tokens {
-			toks[i] = int32(t)
-		}
-		content, err := s.textProcessor.Decode(toks)
-		if err != nil {
-			return "", err
-		}
-		return content, nil
+
+	var resp string
+	for _, token := range tokens {
+		resp += s.llamaModel.TokenToPiece(token)
 	}
-	// not reached
-	return "", fmt.Errorf("no tokenizer configured")
+
+	return resp, nil
+}
+
+func (s *ollamaServer) Detokenize(ctx context.Context, tokens []int) (string, error) {
+	toks := make([]int32, len(tokens))
+	for i, t := range tokens {
+		toks[i] = int32(t)
+	}
+
+	content, err := s.textProcessor.Decode(toks)
+	if err != nil {
+		return "", err
+	}
+
+	return content, nil
 }
 
 func (s *llmServer) Close() error {
@@ -1712,31 +1768,12 @@ func (s *llmServer) Close() error {
 	return nil
 }
 
-func (s *llamaServer) VRAMSize() uint64 {
-	return s.estimate.VRAMSize
-}
-
-func (s *llamaServer) TotalSize() uint64 {
-	return s.estimate.TotalSize
-}
-
-func (s *llamaServer) VRAMByGPU(id ml.DeviceID) uint64 {
-	for i, gpu := range s.gpus {
-		if gpu.DeviceID == id {
-			if i < len(s.estimate.GPUSizes) {
-				return s.estimate.GPUSizes[i]
-			}
-		}
-	}
-	return 0
-}
-
 func (s *llamaServer) GetDeviceInfos(ctx context.Context) []ml.DeviceInfo {
 	slog.Debug("llamarunner free vram reporting not supported")
 	return nil
 }
 
-func (s *ollamaServer) VRAMSize() uint64 {
+func (s *llmServer) VRAMSize() uint64 {
 	if s.mem == nil {
 		return 0
 	}
@@ -1764,7 +1801,7 @@ func (s *ollamaServer) VRAMSize() uint64 {
 	return mem
 }
 
-func (s *ollamaServer) TotalSize() uint64 {
+func (s *llmServer) TotalSize() uint64 {
 	if s.mem == nil {
 		return 0
 	}
@@ -1778,7 +1815,7 @@ func (s *ollamaServer) TotalSize() uint64 {
 	return mem
 }
 
-func (s *ollamaServer) VRAMByGPU(id ml.DeviceID) uint64 {
+func (s *llmServer) VRAMByGPU(id ml.DeviceID) uint64 {
 	if s.mem == nil {
 		return 0
 	}
diff --git a/llm/server_test.go b/llm/server_test.go
index 2d3bf6be..1f5d5cda 100644
--- a/llm/server_test.go
+++ b/llm/server_test.go
@@ -14,16 +14,11 @@ import (
 )
 
 func TestLLMServerFitGPU(t *testing.T) {
-	type gpu struct {
-		id   ml.DeviceID
-		free int
-	}
-
 	minMemory := 457 * format.MebiByte
 
 	tests := []struct {
 		name        string
-		gpus        []gpu
+		gpus        []ml.DeviceInfo
 		layers      []int
 		numGPU      int
 		requireFull bool
@@ -38,91 +33,91 @@ func TestLLMServerFitGPU(t *testing.T) {
 		},
 		{
 			name:     "Full single GPU",
-			gpus:     []gpu{{id: ml.DeviceID{ID: "gpu0"}, free: 256*format.MebiByte + minMemory}},
+			gpus:     []ml.DeviceInfo{{DeviceID: ml.DeviceID{ID: "gpu0"}, FreeMemory: uint64(256*format.MebiByte + minMemory)}},
 			layers:   []int{50 * format.MebiByte, 50 * format.MebiByte, 50 * format.MebiByte},
 			numGPU:   -1,
 			expected: ml.GPULayersList{{DeviceID: ml.DeviceID{ID: "gpu0"}, Layers: []int{0, 1, 2}}},
 		},
 		{
 			name:     "Partial single GPU",
-			gpus:     []gpu{{id: ml.DeviceID{ID: "gpu0"}, free: 256*format.MebiByte + minMemory}},
+			gpus:     []ml.DeviceInfo{{DeviceID: ml.DeviceID{ID: "gpu0"}, FreeMemory: uint64(256*format.MebiByte + minMemory)}},
 			layers:   []int{100 * format.MebiByte, 100 * format.MebiByte, 100 * format.MebiByte, 100 * format.MebiByte},
 			numGPU:   -1,
 			expected: ml.GPULayersList{{DeviceID: ml.DeviceID{ID: "gpu0"}, Layers: []int{1, 2}}},
 		},
 		{
 			name:     "Single GPU with numGPU 1",
-			gpus:     []gpu{{id: ml.DeviceID{ID: "gpu0"}, free: 256*format.MebiByte + minMemory}},
+			gpus:     []ml.DeviceInfo{{DeviceID: ml.DeviceID{ID: "gpu0"}, FreeMemory: uint64(256*format.MebiByte + minMemory)}},
 			layers:   []int{50 * format.MebiByte, 50 * format.MebiByte, 50 * format.MebiByte},
 			numGPU:   1,
 			expected: ml.GPULayersList{{DeviceID: ml.DeviceID{ID: "gpu0"}, Layers: []int{1}}},
 		},
 		{
 			name:     "Single GPU with numGPU 0",
-			gpus:     []gpu{{id: ml.DeviceID{ID: "gpu0"}, free: 256*format.MebiByte + minMemory}},
+			gpus:     []ml.DeviceInfo{{DeviceID: ml.DeviceID{ID: "gpu0"}, FreeMemory: uint64(256*format.MebiByte + minMemory)}},
 			layers:   []int{50 * format.MebiByte, 50 * format.MebiByte, 50 * format.MebiByte},
 			numGPU:   0,
 			expected: ml.GPULayersList{},
 		},
 		{
 			name:     "Single GPU with numGPU 999",
-			gpus:     []gpu{{id: ml.DeviceID{ID: "gpu0"}, free: 256*format.MebiByte + minMemory}},
+			gpus:     []ml.DeviceInfo{{DeviceID: ml.DeviceID{ID: "gpu0"}, FreeMemory: uint64(256*format.MebiByte + minMemory)}},
 			layers:   []int{100 * format.MebiByte, 100 * format.MebiByte, 100 * format.MebiByte, 100 * format.MebiByte},
 			numGPU:   999,
 			expected: ml.GPULayersList{{DeviceID: ml.DeviceID{ID: "gpu0"}, Layers: []int{0, 1, 2, 3}}},
 		},
 		{
 			name:     "Multi GPU fits on one",
-			gpus:     []gpu{{id: ml.DeviceID{ID: "gpu0"}, free: 128*format.MebiByte + minMemory}, {id: ml.DeviceID{ID: "gpu1"}, free: 256*format.MebiByte + minMemory}},
+			gpus:     []ml.DeviceInfo{{DeviceID: ml.DeviceID{ID: "gpu0"}, FreeMemory: uint64(128*format.MebiByte + minMemory)}, {DeviceID: ml.DeviceID{ID: "gpu1"}, FreeMemory: uint64(256*format.MebiByte + minMemory)}},
 			layers:   []int{50 * format.MebiByte, 50 * format.MebiByte, 50 * format.MebiByte},
 			numGPU:   -1,
 			expected: ml.GPULayersList{{DeviceID: ml.DeviceID{ID: "gpu1"}, Layers: []int{0, 1, 2}}},
 		},
 		{
 			name:     "Multi GPU split",
-			gpus:     []gpu{{id: ml.DeviceID{ID: "gpu0"}, free: 128*format.MebiByte + minMemory}, {id: ml.DeviceID{ID: "gpu1"}, free: 256*format.MebiByte + minMemory}},
+			gpus:     []ml.DeviceInfo{{DeviceID: ml.DeviceID{ID: "gpu0"}, FreeMemory: uint64(128*format.MebiByte + minMemory)}, {DeviceID: ml.DeviceID{ID: "gpu1"}, FreeMemory: uint64(256*format.MebiByte + minMemory)}},
 			layers:   []int{256 * format.MebiByte, 50 * format.MebiByte, 50 * format.MebiByte},
 			numGPU:   -1,
 			expected: ml.GPULayersList{{DeviceID: ml.DeviceID{ID: "gpu1"}, Layers: []int{0}}, {DeviceID: ml.DeviceID{ID: "gpu0"}, Layers: []int{1, 2}}},
 		},
 		{
 			name:     "Multi GPU partial",
-			gpus:     []gpu{{id: ml.DeviceID{ID: "gpu0"}, free: 128*format.MebiByte + minMemory}, {id: ml.DeviceID{ID: "gpu1"}, free: 256*format.MebiByte + minMemory}},
+			gpus:     []ml.DeviceInfo{{DeviceID: ml.DeviceID{ID: "gpu0"}, FreeMemory: uint64(128*format.MebiByte + minMemory)}, {DeviceID: ml.DeviceID{ID: "gpu1"}, FreeMemory: uint64(256*format.MebiByte + minMemory)}},
 			layers:   []int{256 * format.MebiByte, 256 * format.MebiByte, 50 * format.MebiByte},
 			numGPU:   -1,
 			expected: ml.GPULayersList{{DeviceID: ml.DeviceID{ID: "gpu1"}, Layers: []int{1}}},
 		},
 		{
 			name:     "Multi GPU numGPU 1",
-			gpus:     []gpu{{id: ml.DeviceID{ID: "gpu0"}, free: 128*format.MebiByte + minMemory}, {id: ml.DeviceID{ID: "gpu1"}, free: 256*format.MebiByte + minMemory}},
+			gpus:     []ml.DeviceInfo{{DeviceID: ml.DeviceID{ID: "gpu0"}, FreeMemory: uint64(128*format.MebiByte + minMemory)}, {DeviceID: ml.DeviceID{ID: "gpu1"}, FreeMemory: uint64(256*format.MebiByte + minMemory)}},
 			layers:   []int{50 * format.MebiByte, 50 * format.MebiByte, 50 * format.MebiByte},
 			numGPU:   1,
 			expected: ml.GPULayersList{{DeviceID: ml.DeviceID{ID: "gpu1"}, Layers: []int{1}}},
 		},
 		{
 			name:     "Multi GPU numGPU 2",
-			gpus:     []gpu{{id: ml.DeviceID{ID: "gpu0"}, free: 128*format.MebiByte + minMemory}, {id: ml.DeviceID{ID: "gpu1"}, free: 256*format.MebiByte + minMemory}},
+			gpus:     []ml.DeviceInfo{{DeviceID: ml.DeviceID{ID: "gpu0"}, FreeMemory: uint64(128*format.MebiByte + minMemory)}, {DeviceID: ml.DeviceID{ID: "gpu1"}, FreeMemory: uint64(256*format.MebiByte + minMemory)}},
 			layers:   []int{256 * format.MebiByte, 50 * format.MebiByte, 50 * format.MebiByte},
 			numGPU:   2,
 			expected: ml.GPULayersList{{DeviceID: ml.DeviceID{ID: "gpu1"}, Layers: []int{0}}, {DeviceID: ml.DeviceID{ID: "gpu0"}, Layers: []int{1}}},
 		},
 		{
 			name:     "Multi GPU numGPU 999",
-			gpus:     []gpu{{id: ml.DeviceID{ID: "gpu0"}, free: 128*format.MebiByte + minMemory}, {id: ml.DeviceID{ID: "gpu1"}, free: 256*format.MebiByte + minMemory}},
+			gpus:     []ml.DeviceInfo{{DeviceID: ml.DeviceID{ID: "gpu0"}, FreeMemory: uint64(128*format.MebiByte + minMemory)}, {DeviceID: ml.DeviceID{ID: "gpu1"}, FreeMemory: uint64(256*format.MebiByte + minMemory)}},
 			layers:   []int{256 * format.MebiByte, 256 * format.MebiByte, 50 * format.MebiByte},
 			numGPU:   999,
 			expected: ml.GPULayersList{{DeviceID: ml.DeviceID{ID: "gpu1"}, Layers: []int{0, 1}}, {DeviceID: ml.DeviceID{ID: "gpu0"}, Layers: []int{2}}},
 		},
 		{
 			name:     "Multi GPU different libraries",
-			gpus:     []gpu{{id: ml.DeviceID{Library: "CUDA", ID: "gpu0"}, free: 128*format.MebiByte + minMemory}, {id: ml.DeviceID{Library: "ROCm", ID: "gpu1"}, free: 256*format.MebiByte + minMemory}},
+			gpus:     []ml.DeviceInfo{{DeviceID: ml.DeviceID{Library: "CUDA", ID: "gpu0"}, FreeMemory: uint64(128*format.MebiByte + minMemory)}, {DeviceID: ml.DeviceID{Library: "ROCm", ID: "gpu1"}, FreeMemory: uint64(256*format.MebiByte + minMemory)}},
 			layers:   []int{128 * format.MebiByte, 128 * format.MebiByte, 50 * format.MebiByte},
 			numGPU:   -1,
 			expected: ml.GPULayersList{{DeviceID: ml.DeviceID{ID: "gpu1", Library: "ROCm"}, Layers: []int{0, 1}}},
 		},
 		{
 			name:        "requireFull",
-			gpus:        []gpu{{id: ml.DeviceID{ID: "gpu0"}, free: 256*format.MebiByte + minMemory}},
+			gpus:        []ml.DeviceInfo{{DeviceID: ml.DeviceID{ID: "gpu0"}, FreeMemory: uint64(256*format.MebiByte + minMemory)}},
 			layers:      []int{100 * format.MebiByte, 100 * format.MebiByte, 100 * format.MebiByte, 100 * format.MebiByte},
 			numGPU:      -1,
 			requireFull: true,
@@ -130,12 +125,54 @@ func TestLLMServerFitGPU(t *testing.T) {
 		},
 		{
 			name:        "requireFull numGPU",
-			gpus:        []gpu{{id: ml.DeviceID{ID: "gpu0"}, free: 256 * format.MebiByte}},
+			gpus:        []ml.DeviceInfo{{DeviceID: ml.DeviceID{ID: "gpu0"}, FreeMemory: uint64(256 * format.MebiByte)}},
 			layers:      []int{100 * format.MebiByte, 100 * format.MebiByte, 100 * format.MebiByte, 100 * format.MebiByte},
 			numGPU:      4,
 			requireFull: true,
 			expectedErr: ErrLoadRequiredFull,
 		},
+		{
+			name:     "iGPU",
+			gpus:     []ml.DeviceInfo{{DeviceID: ml.DeviceID{ID: "gpu0"}, Integrated: true, FreeMemory: uint64(256*format.MebiByte + minMemory)}},
+			layers:   []int{50 * format.MebiByte, 50 * format.MebiByte, 50 * format.MebiByte},
+			numGPU:   -1,
+			expected: ml.GPULayersList{{DeviceID: ml.DeviceID{ID: "gpu0"}, Layers: []int{0, 1, 2}}},
+		},
+		{
+			name:     "iGPU + dGPU",
+			gpus:     []ml.DeviceInfo{{DeviceID: ml.DeviceID{ID: "gpu0"}, FreeMemory: uint64(128*format.MebiByte + minMemory)}, {DeviceID: ml.DeviceID{ID: "gpu1"}, Integrated: true, FreeMemory: uint64(256*format.MebiByte + minMemory)}},
+			layers:   []int{50 * format.MebiByte, 50 * format.MebiByte, 50 * format.MebiByte},
+			numGPU:   -1,
+			expected: ml.GPULayersList{{DeviceID: ml.DeviceID{ID: "gpu1"}, Layers: []int{0}}, {DeviceID: ml.DeviceID{ID: "gpu0"}, Layers: []int{1, 2}}},
+		},
+		{
+			name:     "iGPU + dGPU fits on one",
+			gpus:     []ml.DeviceInfo{{DeviceID: ml.DeviceID{ID: "gpu0"}, FreeMemory: uint64(128*format.MebiByte + minMemory)}, {DeviceID: ml.DeviceID{ID: "gpu1"}, Integrated: true, FreeMemory: uint64(256*format.MebiByte + minMemory)}},
+			layers:   []int{50 * format.MebiByte, 50 * format.MebiByte},
+			numGPU:   -1,
+			expected: ml.GPULayersList{{DeviceID: ml.DeviceID{ID: "gpu0"}, Layers: []int{0, 1}}},
+		},
+		{
+			name:     "iGPU + dGPU partial",
+			gpus:     []ml.DeviceInfo{{DeviceID: ml.DeviceID{ID: "gpu0"}, FreeMemory: uint64(128*format.MebiByte + minMemory)}, {DeviceID: ml.DeviceID{ID: "gpu1"}, Integrated: true, FreeMemory: uint64(256*format.MebiByte + minMemory)}},
+			layers:   []int{100 * format.MebiByte, 100 * format.MebiByte, 100 * format.MebiByte, 100 * format.MebiByte},
+			numGPU:   -1,
+			expected: ml.GPULayersList{{DeviceID: ml.DeviceID{ID: "gpu1"}, Layers: []int{0, 1}}, {DeviceID: ml.DeviceID{ID: "gpu0"}, Layers: []int{2}}},
+		},
+		{
+			name:     "iGPU + dGPU numGPU 1",
+			gpus:     []ml.DeviceInfo{{DeviceID: ml.DeviceID{ID: "gpu0"}, FreeMemory: uint64(128*format.MebiByte + minMemory)}, {DeviceID: ml.DeviceID{ID: "gpu1"}, Integrated: true, FreeMemory: uint64(256*format.MebiByte + minMemory)}},
+			layers:   []int{100 * format.MebiByte, 100 * format.MebiByte, 100 * format.MebiByte, 100 * format.MebiByte},
+			numGPU:   1,
+			expected: ml.GPULayersList{{DeviceID: ml.DeviceID{ID: "gpu0"}, Layers: []int{2}}},
+		},
+		{
+			name:     "iGPU + dGPU numGPU 999",
+			gpus:     []ml.DeviceInfo{{DeviceID: ml.DeviceID{ID: "gpu0"}, FreeMemory: uint64(128*format.MebiByte + minMemory)}, {DeviceID: ml.DeviceID{ID: "gpu1"}, Integrated: true, FreeMemory: uint64(256*format.MebiByte + minMemory)}},
+			layers:   []int{100 * format.MebiByte, 100 * format.MebiByte, 100 * format.MebiByte, 100 * format.MebiByte},
+			numGPU:   999,
+			expected: ml.GPULayersList{{DeviceID: ml.DeviceID{ID: "gpu0"}, Layers: []int{0}}, {DeviceID: ml.DeviceID{ID: "gpu1"}, Layers: []int{1, 2, 3}}},
+		},
 	}
 
 	for _, tt := range tests {
@@ -145,12 +182,6 @@ func TestLLMServerFitGPU(t *testing.T) {
 			systemInfo.FreeMemory = 512 * format.MebiByte
 			systemInfo.FreeSwap = 256 * format.MebiByte
 
-			gpus := make([]ml.DeviceInfo, len(tt.gpus))
-			for i := range tt.gpus {
-				gpus[i].DeviceID = tt.gpus[i].id
-				gpus[i].FreeMemory = uint64(tt.gpus[i].free)
-			}
-
 			s := &ollamaServer{
 				llmServer: llmServer{
 					totalLayers: uint64(len(tt.layers)),
@@ -165,19 +196,19 @@ func TestLLMServerFitGPU(t *testing.T) {
 			s.mem = &ml.BackendMemory{CPU: ml.DeviceMemory{
 				Weights: make([]uint64, s.totalLayers),
 				Cache:   make([]uint64, s.totalLayers),
-			}, GPUs: make([]ml.DeviceMemory, len(gpus))}
+			}, GPUs: make([]ml.DeviceMemory, len(tt.gpus))}
 
 			for i := range tt.layers {
 				s.mem.CPU.Weights[i] = uint64(tt.layers[i])
 			}
 
 			for i := range s.mem.GPUs {
-				s.mem.GPUs[i].DeviceID = gpus[i].DeviceID
+				s.mem.GPUs[i].DeviceID = tt.gpus[i].DeviceID
 				s.mem.GPUs[i].Weights = make([]uint64, s.totalLayers)
 				s.mem.GPUs[i].Cache = make([]uint64, s.totalLayers)
 			}
 
-			gpuLayers, err := s.createLayout(systemInfo, gpus, s.mem, tt.requireFull, 0)
+			gpuLayers, err := s.createLayout(systemInfo, tt.gpus, s.mem, tt.requireFull, 0)
 			if err != tt.expectedErr {
 				t.Fatalf("fitGPU returned error: %v", err)
 			}
diff --git a/macapp/.eslintrc.json b/macapp/.eslintrc.json
deleted file mode 100644
index 2d7aa607..00000000
--- a/macapp/.eslintrc.json
+++ /dev/null
@@ -1,16 +0,0 @@
-{
-  "env": {
-    "browser": true,
-    "es6": true,
-    "node": true
-  },
-  "extends": [
-    "eslint:recommended",
-    "plugin:@typescript-eslint/eslint-recommended",
-    "plugin:@typescript-eslint/recommended",
-    "plugin:import/recommended",
-    "plugin:import/electron",
-    "plugin:import/typescript"
-  ],
-  "parser": "@typescript-eslint/parser"
-}
diff --git a/macapp/.gitignore b/macapp/.gitignore
deleted file mode 100644
index 8296128d..00000000
--- a/macapp/.gitignore
+++ /dev/null
@@ -1,92 +0,0 @@
-# Logs
-logs
-*.log
-npm-debug.log*
-yarn-debug.log*
-yarn-error.log*
-lerna-debug.log*
-
-# Diagnostic reports (https://nodejs.org/api/report.html)
-report.[0-9]*.[0-9]*.[0-9]*.[0-9]*.json
-
-# Runtime data
-pids
-*.pid
-*.seed
-*.pid.lock
-.DS_Store
-
-# Directory for instrumented libs generated by jscoverage/JSCover
-lib-cov
-
-# Coverage directory used by tools like istanbul
-coverage
-*.lcov
-
-# nyc test coverage
-.nyc_output
-
-# node-waf configuration
-.lock-wscript
-
-# Compiled binary addons (https://nodejs.org/api/addons.html)
-build/Release
-
-# Dependency directories
-node_modules/
-jspm_packages/
-
-# TypeScript v1 declaration files
-typings/
-
-# TypeScript cache
-*.tsbuildinfo
-
-# Optional npm cache directory
-.npm
-
-# Optional eslint cache
-.eslintcache
-
-# Optional REPL history
-.node_repl_history
-
-# Output of 'npm pack'
-*.tgz
-
-# Yarn Integrity file
-.yarn-integrity
-
-# dotenv environment variables file
-.env
-.env.test
-
-# parcel-bundler cache (https://parceljs.org/)
-.cache
-
-# next.js build output
-.next
-
-# nuxt.js build output
-.nuxt
-
-# vuepress build output
-.vuepress/dist
-
-# Serverless directories
-.serverless/
-
-# FuseBox cache
-.fusebox/
-
-# DynamoDB Local files
-.dynamodb/
-
-# Webpack
-.webpack/
-
-# Vite
-.vite/
-
-# Electron-Forge
-out/
diff --git a/macapp/README.md b/macapp/README.md
deleted file mode 100644
index bdaf05e7..00000000
--- a/macapp/README.md
+++ /dev/null
@@ -1,21 +0,0 @@
-# Desktop
-
-This app builds upon Ollama to provide a desktop experience for running models.
-
-## Developing
-
-First, build the `ollama` binary:
-
-```shell
-cd ..
-go build .
-```
-
-Then run the desktop app with `npm start`:
-
-```shell
-cd macapp
-npm install
-npm start
-```
-
diff --git a/macapp/assets/icon.icns b/macapp/assets/icon.icns
deleted file mode 100644
index 308592aa..00000000
Binary files a/macapp/assets/icon.icns and /dev/null differ
diff --git a/macapp/assets/iconDarkTemplate.png b/macapp/assets/iconDarkTemplate.png
deleted file mode 100644
index 853d3508..00000000
Binary files a/macapp/assets/iconDarkTemplate.png and /dev/null differ
diff --git a/macapp/assets/iconDarkTemplate@2x.png b/macapp/assets/iconDarkTemplate@2x.png
deleted file mode 100644
index 1a94c9e2..00000000
Binary files a/macapp/assets/iconDarkTemplate@2x.png and /dev/null differ
diff --git a/macapp/assets/iconDarkUpdateTemplate.png b/macapp/assets/iconDarkUpdateTemplate.png
deleted file mode 100644
index 9378ca74..00000000
Binary files a/macapp/assets/iconDarkUpdateTemplate.png and /dev/null differ
diff --git a/macapp/assets/iconDarkUpdateTemplate@2x.png b/macapp/assets/iconDarkUpdateTemplate@2x.png
deleted file mode 100644
index 93ab4e04..00000000
Binary files a/macapp/assets/iconDarkUpdateTemplate@2x.png and /dev/null differ
diff --git a/macapp/assets/iconTemplate.png b/macapp/assets/iconTemplate.png
deleted file mode 100644
index 7b088254..00000000
Binary files a/macapp/assets/iconTemplate.png and /dev/null differ
diff --git a/macapp/assets/iconTemplate@2x.png b/macapp/assets/iconTemplate@2x.png
deleted file mode 100644
index 0be1e88e..00000000
Binary files a/macapp/assets/iconTemplate@2x.png and /dev/null differ
diff --git a/macapp/assets/iconUpdateTemplate.png b/macapp/assets/iconUpdateTemplate.png
deleted file mode 100644
index fa9d7158..00000000
Binary files a/macapp/assets/iconUpdateTemplate.png and /dev/null differ
diff --git a/macapp/assets/iconUpdateTemplate@2x.png b/macapp/assets/iconUpdateTemplate@2x.png
deleted file mode 100644
index ce14192d..00000000
Binary files a/macapp/assets/iconUpdateTemplate@2x.png and /dev/null differ
diff --git a/macapp/forge.config.ts b/macapp/forge.config.ts
deleted file mode 100644
index 540fc0a0..00000000
--- a/macapp/forge.config.ts
+++ /dev/null
@@ -1,79 +0,0 @@
-import type { ForgeConfig } from '@electron-forge/shared-types'
-import { MakerSquirrel } from '@electron-forge/maker-squirrel'
-import { MakerZIP } from '@electron-forge/maker-zip'
-import { PublisherGithub } from '@electron-forge/publisher-github'
-import { AutoUnpackNativesPlugin } from '@electron-forge/plugin-auto-unpack-natives'
-import { WebpackPlugin } from '@electron-forge/plugin-webpack'
-import * as path from 'path'
-import * as fs from 'fs'
-
-import { mainConfig } from './webpack.main.config'
-import { rendererConfig } from './webpack.renderer.config'
-
-const packageJson = JSON.parse(fs.readFileSync(path.resolve(__dirname, './package.json'), 'utf8'))
-
-const config: ForgeConfig = {
-  packagerConfig: {
-    appVersion: process.env.VERSION || packageJson.version,
-    asar: true,
-    icon: './assets/icon.icns',
-    extraResource: [
-      path.join(__dirname, '../dist/darwin/ollama'),
-      ...fs.readdirSync(path.join(__dirname, '../dist/darwin-amd64/lib/ollama')).map(f => path.join(__dirname, '../dist/darwin-amd64/lib/ollama', f)),
-      path.join(__dirname, './assets/iconTemplate.png'),
-      path.join(__dirname, './assets/iconTemplate@2x.png'),
-      path.join(__dirname, './assets/iconUpdateTemplate.png'),
-      path.join(__dirname, './assets/iconUpdateTemplate@2x.png'),
-      path.join(__dirname, './assets/iconDarkTemplate.png'),
-      path.join(__dirname, './assets/iconDarkTemplate@2x.png'),
-      path.join(__dirname, './assets/iconDarkUpdateTemplate.png'),
-      path.join(__dirname, './assets/iconDarkUpdateTemplate@2x.png'),
-    ],
-    ...(process.env.SIGN
-      ? {
-          osxSign: {
-            identity: process.env.APPLE_IDENTITY,
-          },
-          osxNotarize: {
-            tool: 'notarytool',
-            appleId: process.env.APPLE_ID || '',
-            appleIdPassword: process.env.APPLE_PASSWORD || '',
-            teamId: process.env.APPLE_TEAM_ID || '',
-          },
-        }
-      : {}),
-    osxUniversal: {
-      x64ArchFiles: '*',
-    },
-  },
-  rebuildConfig: {},
-  makers: [new MakerSquirrel({}), new MakerZIP({}, ['darwin'])],
-  hooks: {
-    readPackageJson: async (_, packageJson) => {
-      return { ...packageJson, version: process.env.VERSION || packageJson.version }
-    },
-  },
-  plugins: [
-    new AutoUnpackNativesPlugin({}),
-    new WebpackPlugin({
-      mainConfig,
-      devContentSecurityPolicy: `default-src * 'unsafe-eval' 'unsafe-inline'; img-src data: 'self'`,
-      renderer: {
-        config: rendererConfig,
-        nodeIntegration: true,
-        entryPoints: [
-          {
-            html: './src/index.html',
-            js: './src/renderer.tsx',
-            name: 'main_window',
-            preload: {
-              js: './src/preload.ts',
-            },
-          },
-        ],
-      },
-    }),
-  ],
-}
-
-export default config
diff --git a/macapp/package-lock.json b/macapp/package-lock.json
deleted file mode 100644
index bacc2a37..00000000
--- a/macapp/package-lock.json
+++ /dev/null
@@ -1,16604 +0,0 @@
-{
-  "name": "ollama",
-  "version": "0.0.0",
-  "lockfileVersion": 3,
-  "requires": true,
-  "packages": {
-    "": {
-      "name": "ollama",
-      "version": "0.0.0",
-      "license": "MIT",
-      "dependencies": {
-        "@electron/remote": "^2.0.10",
-        "@heroicons/react": "^2.0.18",
-        "@segment/analytics-node": "^1.0.0",
-        "copy-to-clipboard": "^3.3.3",
-        "electron-squirrel-startup": "^1.0.0",
-        "electron-store": "^8.1.0",
-        "react": "^18.2.0",
-        "react-dom": "^18.2.0",
-        "uuid": "^9.0.0",
-        "winston": "^3.10.0",
-        "winston-daily-rotate-file": "^4.7.1"
-      },
-      "devDependencies": {
-        "@babel/core": "^7.22.5",
-        "@babel/preset-react": "^7.22.5",
-        "@electron-forge/cli": "^6.2.1",
-        "@electron-forge/maker-deb": "^6.2.1",
-        "@electron-forge/maker-rpm": "^6.2.1",
-        "@electron-forge/maker-squirrel": "^6.2.1",
-        "@electron-forge/maker-zip": "^6.2.1",
-        "@electron-forge/plugin-auto-unpack-natives": "^6.2.1",
-        "@electron-forge/plugin-webpack": "^6.2.1",
-        "@electron-forge/publisher-github": "^6.2.1",
-        "@electron/universal": "^1.4.1",
-        "@svgr/webpack": "^8.0.1",
-        "@types/chmodr": "^1.0.0",
-        "@types/node": "^20.4.0",
-        "@types/react": "^18.2.14",
-        "@types/react-dom": "^18.2.6",
-        "@types/uuid": "^9.0.2",
-        "@typescript-eslint/eslint-plugin": "^5.60.0",
-        "@typescript-eslint/parser": "^5.60.0",
-        "@vercel/webpack-asset-relocator-loader": "^1.7.3",
-        "babel-loader": "^9.1.2",
-        "chmodr": "^1.2.0",
-        "copy-webpack-plugin": "^11.0.0",
-        "css-loader": "^6.8.1",
-        "electron": "25.9.2",
-        "eslint": "^8.43.0",
-        "eslint-plugin-import": "^2.27.5",
-        "fork-ts-checker-webpack-plugin": "^7.3.0",
-        "node-loader": "^2.0.0",
-        "postcss": "^8.4.24",
-        "postcss-import": "^15.1.0",
-        "postcss-loader": "^7.3.3",
-        "postcss-preset-env": "^8.5.1",
-        "style-loader": "^3.3.3",
-        "svg-inline-loader": "^0.8.2",
-        "tailwindcss": "^3.3.2",
-        "ts-loader": "^9.4.3",
-        "ts-node": "^10.9.1",
-        "typescript": "~4.5.4",
-        "url-loader": "^4.1.1",
-        "webpack": "^5.88.0",
-        "webpack-cli": "^5.1.4",
-        "webpack-dev-server": "^4.15.1"
-      }
-    },
-    "node_modules/@alloc/quick-lru": {
-      "version": "5.2.0",
-      "resolved": "https://registry.npmjs.org/@alloc/quick-lru/-/quick-lru-5.2.0.tgz",
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-      "dev": true,
-      "engines": {
-        "node": ">=10"
-      },
-      "funding": {
-        "url": "https://github.com/sponsors/sindresorhus"
-      }
-    },
-    "node_modules/@ampproject/remapping": {
-      "version": "2.2.1",
-      "resolved": "https://registry.npmjs.org/@ampproject/remapping/-/remapping-2.2.1.tgz",
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-      "dev": true,
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-        "@jridgewell/trace-mapping": "^0.3.9"
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-      "engines": {
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-      },
-      "peerDependencies": {
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-    },
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-        "buffer-crc32": "~0.2.3",
-        "fd-slicer": "~1.1.0"
-      }
-    },
-    "node_modules/yn": {
-      "version": "3.1.1",
-      "resolved": "https://registry.npmjs.org/yn/-/yn-3.1.1.tgz",
-      "integrity": "sha512-Ux4ygGWsu2c7isFWe8Yu1YluJmqVhxqK2cLXNQA5AcC3QfbGNpM7fu0Y8b/z16pXLnFxZYvWhd3fhBY9DLmC6Q==",
-      "dev": true,
-      "engines": {
-        "node": ">=6"
-      }
-    },
-    "node_modules/yocto-queue": {
-      "version": "0.1.0",
-      "resolved": "https://registry.npmjs.org/yocto-queue/-/yocto-queue-0.1.0.tgz",
-      "integrity": "sha512-rVksvsnNCdJ/ohGc6xgPwyN8eheCxsiLM8mxuE/t/mOVqJewPuO1miLpTHQiRgTKCLexL4MeAFVagts7HmNZ2Q==",
-      "dev": true,
-      "engines": {
-        "node": ">=10"
-      },
-      "funding": {
-        "url": "https://github.com/sponsors/sindresorhus"
-      }
-    }
-  }
-}
diff --git a/macapp/package.json b/macapp/package.json
deleted file mode 100644
index 088ec0b1..00000000
--- a/macapp/package.json
+++ /dev/null
@@ -1,80 +0,0 @@
-{
-  "name": "ollama",
-  "productName": "Ollama",
-  "version": "0.0.0",
-  "description": "ollama",
-  "main": ".webpack/main",
-  "scripts": {
-    "start": "electron-forge start",
-    "package": "electron-forge package --arch universal",
-    "package:sign": "SIGN=1 electron-forge package --arch universal",
-    "make": "electron-forge make --arch universal",
-    "make:sign": "SIGN=1 electron-forge make --arch universal",
-    "publish": "SIGN=1 electron-forge publish",
-    "lint": "eslint --ext .ts,.tsx ."
-  },
-  "keywords": [],
-  "author": {
-    "name": "Jeffrey Morgan",
-    "email": "jmorganca@gmail.com"
-  },
-  "license": "MIT",
-  "devDependencies": {
-    "@babel/core": "^7.22.5",
-    "@babel/preset-react": "^7.22.5",
-    "@electron-forge/cli": "^6.2.1",
-    "@electron-forge/maker-deb": "^6.2.1",
-    "@electron-forge/maker-rpm": "^6.2.1",
-    "@electron-forge/maker-squirrel": "^6.2.1",
-    "@electron-forge/maker-zip": "^6.2.1",
-    "@electron-forge/plugin-auto-unpack-natives": "^6.2.1",
-    "@electron-forge/plugin-webpack": "^6.2.1",
-    "@electron-forge/publisher-github": "^6.2.1",
-    "@electron/universal": "^1.4.1",
-    "@svgr/webpack": "^8.0.1",
-    "@types/chmodr": "^1.0.0",
-    "@types/node": "^20.4.0",
-    "@types/react": "^18.2.14",
-    "@types/react-dom": "^18.2.6",
-    "@types/uuid": "^9.0.2",
-    "@typescript-eslint/eslint-plugin": "^5.60.0",
-    "@typescript-eslint/parser": "^5.60.0",
-    "@vercel/webpack-asset-relocator-loader": "^1.7.3",
-    "babel-loader": "^9.1.2",
-    "chmodr": "^1.2.0",
-    "copy-webpack-plugin": "^11.0.0",
-    "css-loader": "^6.8.1",
-    "electron": "25.9.2",
-    "eslint": "^8.43.0",
-    "eslint-plugin-import": "^2.27.5",
-    "fork-ts-checker-webpack-plugin": "^7.3.0",
-    "node-loader": "^2.0.0",
-    "postcss": "^8.4.24",
-    "postcss-import": "^15.1.0",
-    "postcss-loader": "^7.3.3",
-    "postcss-preset-env": "^8.5.1",
-    "style-loader": "^3.3.3",
-    "svg-inline-loader": "^0.8.2",
-    "tailwindcss": "^3.3.2",
-    "ts-loader": "^9.4.3",
-    "ts-node": "^10.9.1",
-    "typescript": "~4.5.4",
-    "url-loader": "^4.1.1",
-    "webpack": "^5.88.0",
-    "webpack-cli": "^5.1.4",
-    "webpack-dev-server": "^4.15.1"
-  },
-  "dependencies": {
-    "@electron/remote": "^2.0.10",
-    "@heroicons/react": "^2.0.18",
-    "@segment/analytics-node": "^1.0.0",
-    "copy-to-clipboard": "^3.3.3",
-    "electron-squirrel-startup": "^1.0.0",
-    "electron-store": "^8.1.0",
-    "react": "^18.2.0",
-    "react-dom": "^18.2.0",
-    "uuid": "^9.0.0",
-    "winston": "^3.10.0",
-    "winston-daily-rotate-file": "^4.7.1"
-  }
-}
diff --git a/macapp/postcss.config.js b/macapp/postcss.config.js
deleted file mode 100644
index d0ffab7e..00000000
--- a/macapp/postcss.config.js
+++ /dev/null
@@ -1,7 +0,0 @@
-module.exports = {
-  plugins: {
-    'postcss-import': {},
-    tailwindcss: {},
-    autoprefixer: {},
-  },
-}
diff --git a/macapp/src/app.css b/macapp/src/app.css
deleted file mode 100644
index c22da2f5..00000000
--- a/macapp/src/app.css
+++ /dev/null
@@ -1,34 +0,0 @@
-@tailwind base;
-@tailwind components;
-@tailwind utilities;
-
-html,
-body {
-  background: transparent;
-}
-
-.drag {
-  -webkit-app-region: drag;
-}
-
-.no-drag {
-  -webkit-app-region: no-drag;
-}
-
-.blink {
-  -webkit-animation: 1s blink step-end infinite;
-  -moz-animation: 1s blink step-end infinite;
-  -ms-animation: 1s blink step-end infinite;
-  -o-animation: 1s blink step-end infinite;
-  animation: 1s blink step-end infinite;
-}
-
-@keyframes blink {
-  from,
-  to {
-    color: transparent;
-  }
-  50% {
-    color: black;
-  }
-}
diff --git a/macapp/src/app.tsx b/macapp/src/app.tsx
deleted file mode 100644
index 449fc851..00000000
--- a/macapp/src/app.tsx
+++ /dev/null
@@ -1,122 +0,0 @@
-import { useState } from 'react'
-import copy from 'copy-to-clipboard'
-import { CheckIcon, DocumentDuplicateIcon } from '@heroicons/react/24/outline'
-import Store from 'electron-store'
-import { getCurrentWindow, app } from '@electron/remote'
-
-import { install } from './install'
-import OllamaIcon from './ollama.svg'
-
-const store = new Store()
-
-enum Step {
-  WELCOME = 0,
-  CLI,
-  FINISH,
-}
-
-export default function () {
-  const [step, setStep] = useState<Step>(Step.WELCOME)
-  const [commandCopied, setCommandCopied] = useState<boolean>(false)
-
-  const command = 'ollama run llama3.2'
-
-  return (
-    <div className='drag'>
-      <div className='mx-auto flex min-h-screen w-full flex-col justify-between bg-white px-4 pt-16'>
-        {step === Step.WELCOME && (
-          <>
-            <div className='mx-auto text-center'>
-              <h1 className='mb-6 mt-4 text-2xl tracking-tight text-gray-900'>Welcome to Ollama</h1>
-              <p className='mx-auto w-[65%] text-sm text-gray-400'>
-                Let's get you up and running with your own large language models.
-              </p>
-              <button
-                onClick={() => setStep(Step.CLI)}
-                className='no-drag rounded-dm mx-auto my-8 w-[40%] rounded-md bg-black px-4 py-2 text-sm text-white hover:brightness-110'
-              >
-                Next
-              </button>
-            </div>
-            <div className='mx-auto'>
-              <OllamaIcon />
-            </div>
-          </>
-        )}
-        {step === Step.CLI && (
-          <>
-            <div className='mx-auto flex flex-col space-y-28 text-center'>
-              <h1 className='mt-4 text-2xl tracking-tight text-gray-900'>Install the command line</h1>
-              <pre className='mx-auto text-4xl text-gray-400'>&gt; ollama</pre>
-              <div className='mx-auto'>
-                <button
-                  onClick={async () => {
-                    try {
-                      await install()
-                      setStep(Step.FINISH)
-                    } catch (e) {
-                      console.error('could not install: ', e)
-                    } finally {
-                      getCurrentWindow().show()
-                      getCurrentWindow().focus()
-                    }
-                  }}
-                  className='no-drag rounded-dm mx-auto w-[60%] rounded-md bg-black px-4 py-2 text-sm text-white hover:brightness-110'
-                >
-                  Install
-                </button>
-                <p className='mx-auto my-4 w-[70%] text-xs text-gray-400'>
-                  You will be prompted for administrator access
-                </p>
-              </div>
-            </div>
-          </>
-        )}
-        {step === Step.FINISH && (
-          <>
-            <div className='mx-auto flex flex-col space-y-20 text-center'>
-              <h1 className='mt-4 text-2xl tracking-tight text-gray-900'>Run your first model</h1>
-              <div className='flex flex-col'>
-                <div className='group relative flex items-center'>
-                  <pre className='language-none text-2xs w-full rounded-md bg-gray-100 px-4 py-3 text-start leading-normal'>
-                    {command}
-                  </pre>
-                  <button
-                    className={`no-drag absolute right-[5px] px-2 py-2 ${
-                      commandCopied
-                        ? 'text-gray-900 opacity-100 hover:cursor-auto'
-                        : 'text-gray-200 opacity-50 hover:cursor-pointer'
-                    } hover:font-bold hover:text-gray-900 group-hover:opacity-100`}
-                    onClick={() => {
-                      copy(command)
-                      setCommandCopied(true)
-                      setTimeout(() => setCommandCopied(false), 3000)
-                    }}
-                  >
-                    {commandCopied ? (
-                      <CheckIcon className='h-4 w-4 font-bold text-gray-500' />
-                    ) : (
-                      <DocumentDuplicateIcon className='h-4 w-4 text-gray-500' />
-                    )}
-                  </button>
-                </div>
-                <p className='mx-auto my-4 w-[70%] text-xs text-gray-400'>
-                  Run this command in your favorite terminal.
-                </p>
-              </div>
-              <button
-                onClick={() => {
-                  store.set('first-time-run', true)
-                  window.close()
-                }}
-                className='no-drag rounded-dm mx-auto w-[60%] rounded-md bg-black px-4 py-2 text-sm text-white hover:brightness-110'
-              >
-                Finish
-              </button>
-            </div>
-          </>
-        )}
-      </div>
-    </div>
-  )
-}
diff --git a/macapp/src/declarations.d.ts b/macapp/src/declarations.d.ts
deleted file mode 100644
index a97fbda7..00000000
--- a/macapp/src/declarations.d.ts
+++ /dev/null
@@ -1,4 +0,0 @@
-declare module '*.svg' {
-  const content: string
-  export default content
-}
diff --git a/macapp/src/index.html b/macapp/src/index.html
deleted file mode 100644
index 9a636cbf..00000000
--- a/macapp/src/index.html
+++ /dev/null
@@ -1,9 +0,0 @@
-<!DOCTYPE html>
-<html>
-  <head>
-    <meta charset="UTF-8" />
-  </head>
-  <body>
-    <div id="app"></div>
-  </body>
-</html>
diff --git a/macapp/src/index.ts b/macapp/src/index.ts
deleted file mode 100644
index a5d04d5f..00000000
--- a/macapp/src/index.ts
+++ /dev/null
@@ -1,302 +0,0 @@
-import { spawn, ChildProcess } from 'child_process'
-import { app, autoUpdater, dialog, Tray, Menu, BrowserWindow, MenuItemConstructorOptions, nativeTheme } from 'electron'
-import Store from 'electron-store'
-import winston from 'winston'
-import 'winston-daily-rotate-file'
-import * as path from 'path'
-
-import { v4 as uuidv4 } from 'uuid'
-import { installed } from './install'
-
-require('@electron/remote/main').initialize()
-
-if (require('electron-squirrel-startup')) {
-  app.quit()
-}
-
-const store = new Store()
-
-let welcomeWindow: BrowserWindow | null = null
-
-declare const MAIN_WINDOW_WEBPACK_ENTRY: string
-
-const logger = winston.createLogger({
-  transports: [
-    new winston.transports.Console(),
-    new winston.transports.File({
-      filename: path.join(app.getPath('home'), '.ollama', 'logs', 'server.log'),
-      maxsize: 1024 * 1024 * 20,
-      maxFiles: 5,
-    }),
-  ],
-  format: winston.format.printf(info => info.message),
-})
-
-app.on('ready', () => {
-  const gotTheLock = app.requestSingleInstanceLock()
-  if (!gotTheLock) {
-    app.exit(0)
-    return
-  }
-
-  app.on('second-instance', () => {
-    if (app.hasSingleInstanceLock()) {
-      app.releaseSingleInstanceLock()
-    }
-
-    if (proc) {
-      proc.off('exit', restart)
-      proc.kill()
-    }
-
-    app.exit(0)
-  })
-
-  app.focus({ steal: true })
-
-  init()
-})
-
-function firstRunWindow() {
-  // Create the browser window.
-  welcomeWindow = new BrowserWindow({
-    width: 400,
-    height: 500,
-    frame: false,
-    fullscreenable: false,
-    resizable: false,
-    movable: true,
-    show: false,
-    webPreferences: {
-      nodeIntegration: true,
-      contextIsolation: false,
-    },
-  })
-
-  require('@electron/remote/main').enable(welcomeWindow.webContents)
-
-  welcomeWindow.loadURL(MAIN_WINDOW_WEBPACK_ENTRY)
-  welcomeWindow.on('ready-to-show', () => welcomeWindow.show())
-  welcomeWindow.on('closed', () => {
-    if (process.platform === 'darwin') {
-      app.dock.hide()
-    }
-  })
-}
-
-let tray: Tray | null = null
-let updateAvailable = false
-const assetPath = app.isPackaged ? process.resourcesPath : path.join(__dirname, '..', '..', 'assets')
-
-function trayIconPath() {
-  return nativeTheme.shouldUseDarkColors
-    ? updateAvailable
-      ? path.join(assetPath, 'iconDarkUpdateTemplate.png')
-      : path.join(assetPath, 'iconDarkTemplate.png')
-    : updateAvailable
-    ? path.join(assetPath, 'iconUpdateTemplate.png')
-    : path.join(assetPath, 'iconTemplate.png')
-}
-
-function updateTrayIcon() {
-  if (tray) {
-    tray.setImage(trayIconPath())
-  }
-}
-
-function updateTray() {
-  const updateItems: MenuItemConstructorOptions[] = [
-    { label: 'An update is available', enabled: false },
-    {
-      label: 'Restart to update',
-      click: () => autoUpdater.quitAndInstall(),
-    },
-    { type: 'separator' },
-  ]
-
-  const menu = Menu.buildFromTemplate([
-    ...(updateAvailable ? updateItems : []),
-    { role: 'quit', label: 'Quit Ollama', accelerator: 'Command+Q' },
-  ])
-
-  if (!tray) {
-    tray = new Tray(trayIconPath())
-  }
-
-  tray.setToolTip(updateAvailable ? 'An update is available' : 'Ollama')
-  tray.setContextMenu(menu)
-  tray.setImage(trayIconPath())
-
-  nativeTheme.off('updated', updateTrayIcon)
-  nativeTheme.on('updated', updateTrayIcon)
-}
-
-let proc: ChildProcess = null
-
-function server() {
-  const binary = app.isPackaged
-    ? path.join(process.resourcesPath, 'ollama')
-    : path.resolve(process.cwd(), '..', 'ollama')
-
-  proc = spawn(binary, ['serve'])
-
-  proc.stdout.on('data', data => {
-    logger.info(data.toString().trim())
-  })
-
-  proc.stderr.on('data', data => {
-    logger.error(data.toString().trim())
-  })
-
-  proc.on('exit', restart)
-}
-
-function restart() {
-  setTimeout(server, 1000)
-}
-
-app.on('before-quit', () => {
-  if (proc) {
-    proc.off('exit', restart)
-    proc.kill('SIGINT') // send SIGINT signal to the server, which also stops any loaded llms
-  }
-})
-
-const updateURL = `https://ollama.com/api/update?os=${process.platform}&arch=${
-  process.arch
-}&version=${app.getVersion()}&id=${id()}`
-
-let latest = ''
-async function isNewReleaseAvailable() {
-  try {
-    const response = await fetch(updateURL)
-
-    if (!response.ok) {
-      return false
-    }
-
-    if (response.status === 204) {
-      return false
-    }
-
-    const data = await response.json()
-
-    const url = data?.url
-    if (!url) {
-      return false
-    }
-
-    if (latest === url) {
-      return false
-    }
-
-    latest = url
-
-    return true
-  } catch (error) {
-    logger.error(`update check failed - ${error}`)
-    return false
-  }
-}
-
-async function checkUpdate() {
-  const available = await isNewReleaseAvailable()
-  if (available) {
-    logger.info('checking for update')
-    autoUpdater.checkForUpdates()
-  }
-}
-
-function init() {
-  if (app.isPackaged) {
-    checkUpdate()
-    setInterval(() => {
-      checkUpdate()
-    }, 60 * 60 * 1000)
-  }
-
-  updateTray()
-
-  if (process.platform === 'darwin') {
-    if (app.isPackaged) {
-      if (!app.isInApplicationsFolder()) {
-        const chosen = dialog.showMessageBoxSync({
-          type: 'question',
-          buttons: ['Move to Applications', 'Do Not Move'],
-          message: 'Ollama works best when run from the Applications directory.',
-          defaultId: 0,
-          cancelId: 1,
-        })
-
-        if (chosen === 0) {
-          try {
-            app.moveToApplicationsFolder({
-              conflictHandler: conflictType => {
-                if (conflictType === 'existsAndRunning') {
-                  dialog.showMessageBoxSync({
-                    type: 'info',
-                    message: 'Cannot move to Applications directory',
-                    detail:
-                      'Another version of Ollama is currently running from your Applications directory. Close it first and try again.',
-                  })
-                }
-                return true
-              },
-            })
-            return
-          } catch (e) {
-            logger.error(`[Move to Applications] Failed to move to applications folder - ${e.message}}`)
-          }
-        }
-      }
-    }
-  }
-
-  server()
-
-  if (store.get('first-time-run') && installed()) {
-    if (process.platform === 'darwin') {
-      app.dock.hide()
-    }
-
-    app.setLoginItemSettings({ openAtLogin: app.getLoginItemSettings().openAtLogin })
-    return
-  }
-
-  // This is the first run or the CLI is no longer installed
-  app.setLoginItemSettings({ openAtLogin: true })
-  firstRunWindow()
-}
-
-// Quit when all windows are closed, except on macOS. There, it's common
-// for applications and their menu bar to stay active until the user quits
-// explicitly with Cmd + Q.
-app.on('window-all-closed', () => {
-  if (process.platform !== 'darwin') {
-    app.quit()
-  }
-})
-
-function id(): string {
-  const id = store.get('id') as string
-
-  if (id) {
-    return id
-  }
-
-  const uuid = uuidv4()
-  store.set('id', uuid)
-  return uuid
-}
-
-autoUpdater.setFeedURL({ url: updateURL })
-
-autoUpdater.on('error', e => {
-  logger.error(`update check failed - ${e.message}`)
-  console.error(`update check failed - ${e.message}`)
-})
-
-autoUpdater.on('update-downloaded', () => {
-  updateAvailable = true
-  updateTray()
-})
diff --git a/macapp/src/install.ts b/macapp/src/install.ts
deleted file mode 100644
index d8036542..00000000
--- a/macapp/src/install.ts
+++ /dev/null
@@ -1,21 +0,0 @@
-import * as fs from 'fs'
-import { exec as cbExec } from 'child_process'
-import * as path from 'path'
-import { promisify } from 'util'
-
-const app = process && process.type === 'renderer' ? require('@electron/remote').app : require('electron').app
-const ollama = app.isPackaged ? path.join(process.resourcesPath, 'ollama') : path.resolve(process.cwd(), '..', 'ollama')
-const exec = promisify(cbExec)
-const symlinkPath = '/usr/local/bin/ollama'
-
-export function installed() {
-  return fs.existsSync(symlinkPath) && fs.readlinkSync(symlinkPath) === ollama
-}
-
-export async function install() {
-  const command = `do shell script "mkdir -p ${path.dirname(
-    symlinkPath
-  )} && ln -F -s \\"${ollama}\\" \\"${symlinkPath}\\"" with administrator privileges`
-
-  await exec(`osascript -e '${command}'`)
-}
diff --git a/macapp/src/ollama.svg b/macapp/src/ollama.svg
deleted file mode 100644
index 6e9fb283..00000000
--- a/macapp/src/ollama.svg
+++ /dev/null
@@ -1,9 +0,0 @@
-<svg width="133" height="185" viewBox="0 0 133 185" fill="none" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink">
-<rect width="133" height="185" fill="url(#pattern0)"/>
-<defs>
-<pattern id="pattern0" patternContentUnits="objectBoundingBox" width="1" height="1">
-<use xlink:href="#image0_406_1657" transform="matrix(0.00552486 0 0 0.00397193 0 -0.00840675)"/>
-</pattern>
-<image id="image0_406_1657" width="181" height="256" 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"/>
-</defs>
-</svg>
diff --git a/macapp/src/preload.ts b/macapp/src/preload.ts
deleted file mode 100644
index e69de29b..00000000
diff --git a/macapp/src/renderer.tsx b/macapp/src/renderer.tsx
deleted file mode 100644
index d4712dd1..00000000
--- a/macapp/src/renderer.tsx
+++ /dev/null
@@ -1,7 +0,0 @@
-import App from './app'
-import './app.css'
-import { createRoot } from 'react-dom/client'
-
-const container = document.getElementById('app')
-const root = createRoot(container)
-root.render(<App />)
diff --git a/macapp/tailwind.config.js b/macapp/tailwind.config.js
deleted file mode 100644
index 12e08fc6..00000000
--- a/macapp/tailwind.config.js
+++ /dev/null
@@ -1,6 +0,0 @@
-/** @type {import('tailwindcss').Config} */
-module.exports = {
-  content: ['./src/**/*.{js,ts,jsx,tsx,mdx}'],
-  theme: {},
-  plugins: [],
-}
diff --git a/macapp/tsconfig.json b/macapp/tsconfig.json
deleted file mode 100644
index 407b5ea3..00000000
--- a/macapp/tsconfig.json
+++ /dev/null
@@ -1,20 +0,0 @@
-{
-  "compilerOptions": {
-    "target": "ES6",
-    "allowJs": true,
-    "module": "commonjs",
-    "skipLibCheck": true,
-    "esModuleInterop": true,
-    "noImplicitAny": true,
-    "sourceMap": true,
-    "baseUrl": ".",
-    "outDir": "dist",
-    "moduleResolution": "node",
-    "resolveJsonModule": true,
-    "paths": {
-      "*": ["node_modules/*"]
-    },
-    "jsx": "react-jsx"
-  },
-  "include": ["src/**/*"]
-}
diff --git a/macapp/webpack.main.config.ts b/macapp/webpack.main.config.ts
deleted file mode 100644
index 51160862..00000000
--- a/macapp/webpack.main.config.ts
+++ /dev/null
@@ -1,20 +0,0 @@
-import type { Configuration } from 'webpack'
-
-import { rules } from './webpack.rules'
-import { plugins } from './webpack.plugins'
-
-export const mainConfig: Configuration = {
-  /**
-   * This is the main entry point for your application, it's the first file
-   * that runs in the main process.
-   */
-  entry: './src/index.ts',
-  // Put your normal webpack config below here
-  module: {
-    rules,
-  },
-  plugins,
-  resolve: {
-    extensions: ['.js', '.ts', '.jsx', '.tsx', '.css', '.json'],
-  },
-}
diff --git a/macapp/webpack.plugins.ts b/macapp/webpack.plugins.ts
deleted file mode 100644
index 3f9ce147..00000000
--- a/macapp/webpack.plugins.ts
+++ /dev/null
@@ -1,14 +0,0 @@
-import type IForkTsCheckerWebpackPlugin from 'fork-ts-checker-webpack-plugin'
-import { DefinePlugin } from 'webpack'
-
-// eslint-disable-next-line @typescript-eslint/no-var-requires
-const ForkTsCheckerWebpackPlugin: typeof IForkTsCheckerWebpackPlugin = require('fork-ts-checker-webpack-plugin')
-
-export const plugins = [
-  new ForkTsCheckerWebpackPlugin({
-    logger: 'webpack-infrastructure',
-  }),
-  new DefinePlugin({
-    'process.env.TELEMETRY_WRITE_KEY': JSON.stringify(process.env.TELEMETRY_WRITE_KEY),
-  }),
-]
diff --git a/macapp/webpack.renderer.config.ts b/macapp/webpack.renderer.config.ts
deleted file mode 100644
index 2ef22b2f..00000000
--- a/macapp/webpack.renderer.config.ts
+++ /dev/null
@@ -1,19 +0,0 @@
-import type { Configuration } from 'webpack'
-
-import { rules } from './webpack.rules'
-import { plugins } from './webpack.plugins'
-
-rules.push({
-  test: /\.css$/,
-  use: [{ loader: 'style-loader' }, { loader: 'css-loader' }, { loader: 'postcss-loader' }],
-})
-
-export const rendererConfig: Configuration = {
-  module: {
-    rules,
-  },
-  plugins,
-  resolve: {
-    extensions: ['.js', '.ts', '.jsx', '.tsx', '.css'],
-  },
-}
diff --git a/macapp/webpack.rules.ts b/macapp/webpack.rules.ts
deleted file mode 100644
index a4b109b9..00000000
--- a/macapp/webpack.rules.ts
+++ /dev/null
@@ -1,35 +0,0 @@
-import type { ModuleOptions } from 'webpack'
-
-export const rules: Required<ModuleOptions>['rules'] = [
-  // Add support for native node modules
-  {
-    // We're specifying native_modules in the test because the asset relocator loader generates a
-    // "fake" .node file which is really a cjs file.
-    test: /native_modules[/\\].+\.node$/,
-    use: 'node-loader',
-  },
-  {
-    test: /[/\\]node_modules[/\\].+\.(m?js|node)$/,
-    parser: { amd: false },
-    use: {
-      loader: '@vercel/webpack-asset-relocator-loader',
-      options: {
-        outputAssetBase: 'native_modules',
-      },
-    },
-  },
-  {
-    test: /\.tsx?$/,
-    exclude: /(node_modules|\.webpack)/,
-    use: {
-      loader: 'ts-loader',
-      options: {
-        transpileOnly: true,
-      },
-    },
-  },
-  {
-    test: /\.svg$/,
-    use: ['@svgr/webpack'],
-  },
-]
diff --git a/ml/backend.go b/ml/backend.go
index b07039e2..36557e62 100644
--- a/ml/backend.go
+++ b/ml/backend.go
@@ -146,7 +146,6 @@ type Tensor interface {
 	FromFloats([]float32)
 	FromInts([]int32)
 
-	Neg(ctx Context) Tensor
 	Add(ctx Context, t2 Tensor) Tensor
 	Sub(ctx Context, t2 Tensor) Tensor
 	Mul(ctx Context, t2 Tensor) Tensor
@@ -185,7 +184,6 @@ type Tensor interface {
 	View(ctx Context, offset int, shape ...int) Tensor
 	Permute(ctx Context, shape ...int) Tensor
 	Contiguous(ctx Context, shape ...int) Tensor
-	Set(ctx Context, t2 Tensor, offset int, strides ...int) Tensor
 
 	Pad(ctx Context, shape ...int) Tensor
 
@@ -198,6 +196,10 @@ type Tensor interface {
 	Copy(ctx Context, t2 Tensor) Tensor
 	Duplicate(ctx Context) Tensor
 
+	Slice(ctx Context, dim, low, high, step int) Tensor
+	Chunk(ctx Context, dim int, size int) []Tensor
+	ChunkSections(ctx Context, dim int, sections ...int) []Tensor
+
 	TopK(ctx Context, k int) Tensor
 	Argsort(ctx Context) Tensor
 	Mean(ctx Context) Tensor
@@ -205,7 +207,6 @@ type Tensor interface {
 	Stddev(ctx Context) Tensor
 	Sqr(ctx Context) Tensor
 	Sqrt(ctx Context) Tensor
-	Clamp(ctx Context, min, max float32) Tensor
 }
 
 // ScaledDotProductAttention implements a fused attention
diff --git a/ml/backend/ggml/ggml.go b/ml/backend/ggml/ggml.go
index 5fa0a9ec..2aa72190 100644
--- a/ml/backend/ggml/ggml.go
+++ b/ml/backend/ggml/ggml.go
@@ -1137,13 +1137,6 @@ func (t *Tensor) Cast(ctx ml.Context, dtype ml.DType) ml.Tensor {
 	}
 }
 
-func (t *Tensor) Neg(ctx ml.Context) ml.Tensor {
-	return &Tensor{
-		b: t.b,
-		t: C.ggml_neg(ctx.(*Context).ctx, t.t),
-	}
-}
-
 func (t *Tensor) Add(ctx ml.Context, t2 ml.Tensor) ml.Tensor {
 	return &Tensor{
 		b: t.b,
@@ -1632,20 +1625,6 @@ func (t *Tensor) AvgPool2D(ctx ml.Context, k, s int, p float32) ml.Tensor {
 	}
 }
 
-func (t *Tensor) Set(ctx ml.Context, t2 ml.Tensor, offset int, strides ...int) ml.Tensor {
-	var tt *C.struct_ggml_tensor
-	switch len(strides) {
-	case 0:
-		tt = C.ggml_set_1d(ctx.(*Context).ctx, t.t, t2.(*Tensor).t, C.size_t(offset))
-	case 1:
-		tt = C.ggml_set_2d(ctx.(*Context).ctx, t.t, t2.(*Tensor).t, C.size_t(offset), C.size_t(strides[0]))
-	default:
-		panic("unsupported number of dimensions")
-	}
-
-	return &Tensor{b: t.b, t: tt}
-}
-
 func (t *Tensor) ScaledDotProductAttention(ctx ml.Context, key, value, mask, sinks ml.Tensor, scale float64) ml.Tensor {
 	var kqMask *C.struct_ggml_tensor
 	if mask != nil {
@@ -1732,9 +1711,65 @@ func (t *Tensor) Sqrt(ctx ml.Context) ml.Tensor {
 	}
 }
 
-func (t *Tensor) Clamp(ctx ml.Context, min, max float32) ml.Tensor {
-	return &Tensor{
-		b: t.b,
-		t: C.ggml_clamp(ctx.(*Context).ctx, t.t, C.float(min), C.float(max)),
+// Slice returns a view of the tensor sliced along dim from low to high in step steps.
+// Slice panics if the dimension is invalid or the slice parameters are out of range.
+// If dim=0 and step>1, the tensor is a copy rather than a view to ensure proper shape.
+func (t *Tensor) Slice(ctx ml.Context, dim int, low, high, step int) ml.Tensor {
+	if dim < 0 || dim >= C.GGML_MAX_DIMS {
+		panic("invalid dimension")
+	} else if low < 0 || high > t.Dim(dim) || low >= high || step < 1 {
+		panic("invalid slice parameters")
+	}
+
+	if dim == 0 && step > 1 {
+		// dim=0,step>1 is a special case so handle it here first
+		return t.View(ctx,
+			low*t.Stride(0), 1,
+			step*t.Stride(0), (high-low+1)/step,
+			t.Stride(1), t.Dim(1),
+			// preserve dim 3 by merging it into dim 2
+			t.Stride(2), t.Dim(2)*t.Dim(3),
+		).Contiguous(ctx, (high-low+1)/step, t.Dim(1), t.Dim(2), t.Dim(3))
+	}
+
+	args := []int{
+		low * t.Stride(dim), t.Dim(0),
+		t.Stride(1), t.Dim(1),
+		t.Stride(2), t.Dim(2),
+		t.Stride(3), t.Dim(3),
+	}
+
+	if step == 1 {
+		args[dim*2+1] = high - low
+		return t.View(ctx, args[0], args[1:]...)
+	} else {
+		args[dim*2] = step * t.Stride(dim)
+		args[dim*2+1] = (high - low + 1) / step
+		return t.View(ctx, args[0], args[1:]...)
 	}
 }
+
+// Chunk the tensor into chunk sized tensors along dim. Each sub-tensor is a view of
+// the original.
+func (t *Tensor) Chunk(ctx ml.Context, dim, chunk int) []ml.Tensor {
+	sections := make([]int, 0, t.Dim(dim)/chunk+1)
+	for rest := t.Dim(dim); rest > 0; rest -= chunk {
+		sections = append(sections, min(chunk, rest))
+	}
+	return t.ChunkSections(ctx, dim, sections...)
+}
+
+// ChunkSections split the tensor into section sized tensors along dim. Each sub-tensor is a
+// view of the original. The size of the dim must equal the sum of sections.
+func (t *Tensor) ChunkSections(ctx ml.Context, dim int, sections ...int) []ml.Tensor {
+	var offset int
+	s := make([]ml.Tensor, len(sections))
+	for i, section := range sections {
+		s[i] = t.Slice(ctx, dim, offset, offset+section, 1)
+		offset += section
+	}
+	if offset != t.Dim(dim) {
+		panic("sections do not sum to tensor dimension")
+	}
+	return s
+}
diff --git a/ml/backend/ggml/ggml/src/ggml-impl.h b/ml/backend/ggml/ggml/src/ggml-impl.h
index 639d551a..e5c446d1 100644
--- a/ml/backend/ggml/ggml/src/ggml-impl.h
+++ b/ml/backend/ggml/ggml/src/ggml-impl.h
@@ -693,6 +693,7 @@ GGML_API void ggml_dxgi_pdh_release();
 #endif
 
 #ifdef __cplusplus
+#include <array>
 #include <initializer_list>
 #include <vector>
 
@@ -708,6 +709,21 @@ inline bool ggml_can_fuse_subgraph(const struct ggml_cgraph *          cgraph,
     return ggml_can_fuse_subgraph(cgraph, start_idx, ops.size(), ops.begin(), outputs.begin(), outputs.size());
 }
 
+// Return true if the edges in the graph match expectations.
+inline bool ggml_check_edges(const struct ggml_cgraph *                cgraph,
+                             int                                       start_idx,
+                             std::initializer_list<std::array<int, 3>> edges) {
+    for (const auto & edge : edges) {
+        int dst_node = edge[0];
+        int src_idx  = edge[1];
+        int src_node = edge[2];
+        if (cgraph->nodes[start_idx + dst_node]->src[src_idx] != cgraph->nodes[start_idx + src_node]) {
+            return false;
+        }
+    }
+    return true;
+}
+
 // expose GGUF internals for test code
 GGML_API size_t gguf_type_size(enum gguf_type type);
 GGML_API struct gguf_context * gguf_init_from_file_impl(FILE * file, struct gguf_init_params params);
diff --git a/ml/backend/ggml/ggml/src/ggml-metal/ggml-metal-device.cpp b/ml/backend/ggml/ggml/src/ggml-metal/ggml-metal-device.cpp
index 75811634..c78082ac 100644
--- a/ml/backend/ggml/ggml/src/ggml-metal/ggml-metal-device.cpp
+++ b/ml/backend/ggml/ggml/src/ggml-metal/ggml-metal-device.cpp
@@ -677,7 +677,7 @@ ggml_metal_pipeline_t ggml_metal_library_get_pipeline_mul_mm_id_map0(ggml_metal_
     char name[256];
 
     snprintf(base, 256, "kernel_mul_mm_id_map0_ne20_%d", ne20);
-    snprintf(name, 256, "%s", base);
+    snprintf(name, 256, "%s_ne02=%d", base, ne02);
 
     ggml_metal_pipeline_t res = ggml_metal_library_get_pipeline(lib, name);
     if (res) {
diff --git a/ml/backend/ggml/ggml/src/ggml-vulkan/ggml-vulkan.cpp b/ml/backend/ggml/ggml/src/ggml-vulkan/ggml-vulkan.cpp
index 221e2950..80185d9f 100644
--- a/ml/backend/ggml/ggml/src/ggml-vulkan/ggml-vulkan.cpp
+++ b/ml/backend/ggml/ggml/src/ggml-vulkan/ggml-vulkan.cpp
@@ -146,8 +146,13 @@ static void ggml_vk_destroy_pipeline(vk::Device& device, vk_pipeline& pipeline);
 struct vk_matmul_pipeline_struct {
     vk_pipeline l, m, s;
     vk_pipeline a_l, a_m, a_s;
+    // Returns true when all unaligned pipelines are null.
+    // We only check for unaligned variants since one of the unaligned pipelines must exist
+    // while aligned pipelines are optional
+    bool is_empty() const {
+        return l == nullptr && m == nullptr && s == nullptr;
+    }
 };
-
 typedef std::shared_ptr<vk_matmul_pipeline_struct> vk_matmul_pipeline;
 
 struct vk_matmul_pipeline2 {
@@ -387,12 +392,81 @@ static constexpr uint32_t num_argsort_pipelines = 11;
 static constexpr uint32_t max_argsort_cols = 1 << (num_argsort_pipelines-1);
 static constexpr uint32_t num_topk_moe_pipelines = 10;
 
-static constexpr std::array topk_moe_norm{ GGML_OP_SOFT_MAX, GGML_OP_RESHAPE,  GGML_OP_ARGSORT,
-                                           GGML_OP_VIEW,     GGML_OP_GET_ROWS, GGML_OP_RESHAPE,
-                                           GGML_OP_SUM_ROWS, GGML_OP_DIV,      GGML_OP_RESHAPE };
-static constexpr std::array topk_moe     { GGML_OP_SOFT_MAX, GGML_OP_RESHAPE,  GGML_OP_ARGSORT,
-                                           GGML_OP_VIEW,     GGML_OP_GET_ROWS };
+static constexpr std::initializer_list<ggml_op> topk_moe_early_softmax_norm{ GGML_OP_SOFT_MAX, GGML_OP_RESHAPE,  GGML_OP_ARGSORT,
+                                                                             GGML_OP_VIEW,     GGML_OP_GET_ROWS, GGML_OP_RESHAPE,
+                                                                             GGML_OP_SUM_ROWS, GGML_OP_CLAMP,    GGML_OP_DIV,
+                                                                             GGML_OP_RESHAPE };
+static constexpr std::initializer_list<ggml_op> topk_moe_early_softmax     { GGML_OP_SOFT_MAX, GGML_OP_RESHAPE,  GGML_OP_ARGSORT,
+                                                                             GGML_OP_VIEW,     GGML_OP_GET_ROWS };
+static constexpr std::initializer_list<ggml_op> topk_moe_late_softmax      { GGML_OP_ARGSORT,  GGML_OP_VIEW,
+                                                                             GGML_OP_GET_ROWS, GGML_OP_RESHAPE,
+                                                                             GGML_OP_SOFT_MAX, GGML_OP_RESHAPE };
 
+//node #978 (  SOFT_MAX):     ffn_moe_probs-15 (   0K) [Vulka         ] use=2:    ffn_moe_logits-15 (   0K) [Vulka         ]
+//node #979 (   RESHAPE): ffn_moe_probs-15 (re (   0K) [Vulka         ] use=1:     ffn_moe_probs-15 (   0K) [Vulka         ]
+//node #980 (   ARGSORT):   ffn_moe_argsort-15 (   0K) [Vulka         ] use=1:     ffn_moe_probs-15 (   0K) [Vulka         ]
+//node #981 (      VIEW):      ffn_moe_topk-15 (   0K) [Vulka         ] use=4:   ffn_moe_argsort-15 (   0K) [Vulka         ]
+//node #982 (  GET_ROWS):   ffn_moe_weights-15 (   0K) [Vulka         ] use=1: ffn_moe_probs-15 (re (   0K) [Vulka         ]      ffn_moe_topk-15 (   0K) [Vulka         ]
+//node #983 (   RESHAPE): ffn_moe_weights-15 ( (   0K) [Vulka         ] use=2:   ffn_moe_weights-15 (   0K) [Vulka         ]
+//node #984 (  SUM_ROWS): ffn_moe_weights_sum- (   0K) [Vulka         ] use=1: ffn_moe_weights-15 ( (   0K) [Vulka         ]
+//node #985 (     CLAMP): ffn_moe_weights_sum_ (   0K) [Vulka         ] use=1: ffn_moe_weights_sum- (   0K) [Vulka         ]
+//node #986 (       DIV): ffn_moe_weights_norm (   0K) [Vulka         ] use=1: ffn_moe_weights-15 ( (   0K) [Vulka         ] ffn_moe_weights_sum_ (   0K) [Vulka         ]
+//node #987 (   RESHAPE): ffn_moe_weights_norm (   0K) [Vulka         ] use=1: ffn_moe_weights_norm (   0K) [Vulka         ]
+static constexpr std::initializer_list<std::array<int, 3>> topk_moe_early_softmax_norm_edges {
+    { 1, 0, 0 }, // reshape->src[0]  == softmax
+    { 2, 0, 0 }, // argsort->src[0]  == softmax
+    { 3, 0, 2 }, // view->src[0]     == argsort
+    { 4, 0, 1 }, // get_rows->src[0] == reshape
+    { 4, 1, 3 }, // get_rows->src[1] == view
+    { 5, 0, 4 }, // reshape->src[0]  == get_rows
+    { 6, 0, 5 }, // sum_rows->src[0] == reshape
+    { 7, 0, 6 }, // clamp->src[0]    == sum_rows
+    { 8, 0, 5 }, // div->src[0]      == reshape
+    { 8, 1, 7 }, // div->src[1]      == clamp
+    { 9, 0, 8 }, // reshape->src[0]  == div
+};
+
+// same as early_softmax_norm but ending after the get_rows
+static constexpr std::initializer_list<std::array<int, 3>> topk_moe_early_softmax_edges {
+    { 1, 0, 0 }, // reshape->src[0]  == softmax
+    { 2, 0, 0 }, // argsort->src[0]  == softmax
+    { 3, 0, 2 }, // view->src[0]     == argsort
+    { 4, 0, 1 }, // get_rows->src[0] == reshape
+    { 4, 1, 3 }, // get_rows->src[1] == view
+};
+
+//node #652 (   ARGSORT):   ffn_moe_argsort-11 (   0K) [Vulka         ] use=1:     ffn_moe_probs-11 (   0K) [Vulka         ]
+//node #653 (      VIEW):      ffn_moe_topk-11 (   0K) [Vulka         ] use=7:   ffn_moe_argsort-11 (   0K) [Vulka         ]
+//node #654 (  GET_ROWS):   ffn_moe_weights-11 (   0K) [Vulka         ] use=1: ffn_moe_probs-11 (re (   0K) [Vulka         ]      ffn_moe_topk-11 (   0K) [Vulka         ]
+//node #655 (   RESHAPE): ffn_moe_weights-11 ( (   0K) [Vulka         ] use=1:   ffn_moe_weights-11 (   0K) [Vulka         ]
+//node #656 (  SOFT_MAX):             node_656 (   0K) [Vulka         ] use=1: ffn_moe_weights-11 ( (   0K) [Vulka         ]
+//node #657 (   RESHAPE): ffn_moe_weights_soft (   0K) [Vulka         ] use=1:             node_656 (   0K) [Vulka         ]
+static constexpr std::initializer_list<std::array<int, 3>> topk_moe_late_softmax_edges {
+    { 1, 0, 0 }, // view->src[0]     == argsort
+    { 2, 1, 1 }, // get_rows->src[1] == view
+    { 3, 0, 2 }, // reshape->src[0]  == get_rows
+    { 4, 0, 3 }, // soft_max->src[0] == reshape
+    { 5, 0, 4 }, // reshape->src[0]  == soft_max
+};
+
+enum topk_moe_mode {
+    TOPK_MOE_EARLY_SOFTMAX,
+    TOPK_MOE_EARLY_SOFTMAX_NORM,
+    TOPK_MOE_LATE_SOFTMAX,
+    TOPK_MOE_COUNT,
+};
+
+static topk_moe_mode ggml_vk_num_additional_ops_to_topk_moe_mode(uint32_t num) {
+    topk_moe_mode mode = num == topk_moe_early_softmax_norm.size() - 1 ? TOPK_MOE_EARLY_SOFTMAX_NORM :
+                         num == topk_moe_early_softmax.size() - 1      ? TOPK_MOE_EARLY_SOFTMAX :
+                                                                         TOPK_MOE_LATE_SOFTMAX;
+    return mode;
+}
+
+static constexpr std::initializer_list<std::array<int, 3>> rope_view_set_rows_edges {
+    { 1, 0, 0 }, // view->src[0]     == rope
+    { 2, 0, 1 }, // set_rows->src[0] == view
+};
 
 struct vk_device_struct {
     std::recursive_mutex mutex;
@@ -488,6 +562,7 @@ struct vk_device_struct {
     vk_matmul_pipeline2 pipeline_matmul_id_f16_f32;
 
     vk_matmul_pipeline2 pipeline_dequant_mul_mat_mat_id[GGML_TYPE_COUNT];
+    vk_matmul_pipeline2 pipeline_dequant_mul_mat_mat_id_q8_1[GGML_TYPE_COUNT];
 
     vk_pipeline pipeline_matmul_split_k_reduce;
     vk_pipeline pipeline_quantize_q8_1;
@@ -575,8 +650,8 @@ struct vk_device_struct {
     vk_pipeline pipeline_soft_max_f32, pipeline_soft_max_f32_f16;
     vk_pipeline pipeline_soft_max_f32_wg512, pipeline_soft_max_f32_f16_wg512;
     vk_pipeline pipeline_soft_max_back_f32;
-    vk_pipeline pipeline_rope_norm_f32, pipeline_rope_norm_f16;
-    vk_pipeline pipeline_rope_neox_f32, pipeline_rope_neox_f16;
+    vk_pipeline pipeline_rope_norm_f32, pipeline_rope_norm_f16, pipeline_rope_norm_f32_f16;
+    vk_pipeline pipeline_rope_neox_f32, pipeline_rope_neox_f16, pipeline_rope_neox_f32_f16;
     vk_pipeline pipeline_rope_multi_f32, pipeline_rope_multi_f16;
     vk_pipeline pipeline_rope_vision_f32, pipeline_rope_vision_f16;
     vk_pipeline pipeline_argsort_f32[num_argsort_pipelines];
@@ -606,8 +681,7 @@ struct vk_device_struct {
 
     vk_pipeline pipeline_flash_attn_split_k_reduce;
 
-    // [2] is {!norm, norm}
-    vk_pipeline pipeline_topk_moe[num_topk_moe_pipelines][2];
+    vk_pipeline pipeline_topk_moe[num_topk_moe_pipelines][TOPK_MOE_COUNT];
 
     std::vector<vk_pipeline_ref> all_pipelines;
 
@@ -955,6 +1029,8 @@ static_assert(sizeof(vk_op_multi_add_push_constants) <= 256);
 struct vk_op_topk_moe_push_constants {
     uint32_t n_rows;
     uint32_t n_expert_used;
+    float clamp_min;
+    float clamp_max;
 };
 
 struct vk_op_add_id_push_constants {
@@ -988,6 +1064,7 @@ struct vk_op_rope_push_constants {
     uint32_t s2;
     int32_t sections[4];
     uint32_t is_back;
+    uint32_t set_rows_stride;
 };
 
 struct vk_op_soft_max_push_constants {
@@ -1012,6 +1089,7 @@ struct vk_op_soft_max_push_constants {
 
 struct vk_op_argsort_push_constants {
     uint32_t ncols;
+    uint32_t nrows;
     int32_t order;
 };
 
@@ -1497,6 +1575,10 @@ struct ggml_backend_vk_context {
     // number of additional consecutive nodes that are being fused with the
     // node currently being processed
     int num_additional_fused_ops {};
+    // Bitmask of which fused ops need to write an intermediate value to memory.
+    // Bit 'i' means nodes[start_of_fusion + i] writes to memory.
+    // If there's no fusion, bit 0 is still set.
+    int fused_ops_write_mask {};
 };
 
 static void * const vk_ptr_base = (void *)(uintptr_t) 0x1000;  // NOLINT
@@ -2449,8 +2531,11 @@ static void ggml_vk_load_shaders(vk_device& device) {
                           l_warptile_id, m_warptile_id, s_warptile_id,
                           l_warptile_mmq, m_warptile_mmq, s_warptile_mmq,
                           l_warptile_mmq_int, m_warptile_mmq_int, s_warptile_mmq_int,
+                          l_warptile_mmq_int_k, m_warptile_mmq_int_k, s_warptile_mmq_int_k,
                           l_warptile_mmq_k, m_warptile_mmq_k, s_warptile_mmq_k,
-                          l_warptile_mmqid, m_warptile_mmqid, s_warptile_mmqid;
+                          l_warptile_mmqid, m_warptile_mmqid, s_warptile_mmqid,
+                          l_warptile_mmqid_int, m_warptile_mmqid_int, s_warptile_mmqid_int,
+                          l_warptile_mmqid_int_k, m_warptile_mmqid_int_k, s_warptile_mmqid_int_k;
     std::array<uint32_t, 3> l_wg_denoms, m_wg_denoms, s_wg_denoms,
                             l_mmq_wg_denoms, m_mmq_wg_denoms, s_mmq_wg_denoms,
                             l_mmq_wg_denoms_k, m_mmq_wg_denoms_k, s_mmq_wg_denoms_k,
@@ -2513,10 +2598,16 @@ static void ggml_vk_load_shaders(vk_device& device) {
         m_warptile_mmq = { 128,  64,  64, 32, subgroup_size_8, 32, 2, tm_m, tn_m, tk_m, subgroup_size_8 };
         s_warptile_mmq = { subgroup_size_32, 32, 32, 32, 32, 32, 2, tm_s, tn_s, tk_s, subgroup_size_8 };
 
+        // Integer MMQ has a smaller shared memory profile, but heavier register use
         l_warptile_mmq_int = { 128, 128, 128, 32, subgroup_size_8 * 2, 64, 2, 4, 4, 1, subgroup_size_8 };
         m_warptile_mmq_int = { 128,  64,  64, 32, subgroup_size_8,     32, 2, 2, 2, 1, subgroup_size_8 };
         s_warptile_mmq_int = { subgroup_size_32, 32, 32, 32, 32,       32, 2, 2, 1, 1, subgroup_size_8 };
 
+        // K-quants use even more registers, mitigate by setting WMITER to 1
+        l_warptile_mmq_int_k = { 128, 128, 128, 32, subgroup_size_8 * 2, 64, 1, 4, 4, 1, subgroup_size_8 };
+        m_warptile_mmq_int_k = { 128,  64,  64, 32, subgroup_size_8,     32, 1, 2, 2, 1, subgroup_size_8 };
+        s_warptile_mmq_int_k = { subgroup_size_32, 32, 32, 32, 32,       32, 1, 2, 1, 1, subgroup_size_8 };
+
         l_warptile_id = { 128, 128, 128, 16, mul_mat_subgroup_size_16 * 2, 64, 2, tm_l, tn_l, tk_l, mul_mat_subgroup_size_16 };
         m_warptile_id = { 128,  64,  64, 16, mul_mat_subgroup_size_16, 32, 2, tm_m, tn_m, tk_m, mul_mat_subgroup_size_16 };
         s_warptile_id = { mul_mat_subgroup_size_16, 32, 32, 16, 32, 32, 2, tm_s, tn_s, tk_s, mul_mat_subgroup_size_16 };
@@ -2525,10 +2616,18 @@ static void ggml_vk_load_shaders(vk_device& device) {
         m_warptile_mmqid = { 128,  64,  64, 32, mul_mat_subgroup_size_8, 32, 2, tm_m, tn_m, tk_m, mul_mat_subgroup_size_8 };
         s_warptile_mmqid = { mul_mat_subgroup_size_32, 32, 32, 32, 32, 32, 2, tm_s, tn_s, tk_s, mul_mat_subgroup_size_8 };
 
+        l_warptile_mmqid_int = { 128, 128, 128, 32, mul_mat_subgroup_size_8 * 2, 64, 2, 4, 4, 1, mul_mat_subgroup_size_8 };
+        m_warptile_mmqid_int = { 128,  64,  64, 32, mul_mat_subgroup_size_8,     32, 2, 2, 2, 1, mul_mat_subgroup_size_8 };
+        s_warptile_mmqid_int = { mul_mat_subgroup_size_32, 32, 32, 32, 32,       32, 2, 2, 1, 1, mul_mat_subgroup_size_8 };
+
+        l_warptile_mmqid_int_k = { 128, 128, 128, 32, mul_mat_subgroup_size_16 * 2, 64, 1, 4, 4, 1, mul_mat_subgroup_size_16 };
+        m_warptile_mmqid_int_k = { 128,  64,  64, 32, mul_mat_subgroup_size_16,     32, 1, 2, 2, 1, mul_mat_subgroup_size_16 };
+        s_warptile_mmqid_int_k = { mul_mat_subgroup_size_32, 32, 32, 32, 32,       32, 1, 2, 1, 1, mul_mat_subgroup_size_16 };
+
         // chip specific tuning
         if ((device->architecture == AMD_GCN) && (device->driver_id != vk::DriverId::eAmdProprietary)) {
             m_warptile_mmq = m_warptile_mmq_int = { 256, 64, 64, 32, 16, 16, 2, 2, 2, 1, 16 };
-            m_warptile_mmqid = { 256, 64, 64, 32, 16, 16, 2, 2, 2, 1, 16 };
+            m_warptile_mmqid = m_warptile_mmqid_int = { 256, 64, 64, 32, 16, 16, 2, 2, 2, 1, 16 };
         }
 
         l_mmq_wg_denoms = l_wg_denoms = {128, 128, 1 };
@@ -2913,18 +3012,15 @@ static void ggml_vk_load_shaders(vk_device& device) {
         if (device->mul_mat ## ID ## _s[TYPE]) \
             ggml_vk_create_pipeline(device, device-> PIPELINE_NAME ->a_s, #NAMELC #F16ACC "_aligned_s", NAMELC ## _aligned ## F16ACC ## _len, NAMELC ## _aligned ## F16ACC ## _data, "main", PARAMCOUNT, sizeof(PUSHCONST), s_ ## WG_DENOMS, s_ ## WARPTILE, s_align, false, REQSUBGROUPSIZE > 0, REQSUBGROUPSIZE);   \
 
-#define CREATE_MMQ(TYPE, PIPELINE_NAME, NAMELC, WG_DENOMS, WARPTILE, PUSHCONST, PARAMCOUNT, ID) \
+#define CREATE_MMQ(TYPE, PIPELINE_NAME, NAMELC, WG_DENOMS, WARPTILE, PUSHCONST, PARAMCOUNT, ID, REQSUBGROUPSIZE) \
         if (device->mul_mat ## ID ## _l[TYPE]) { \
-            ggml_vk_create_pipeline(device, device-> PIPELINE_NAME .f16acc->l, #NAMELC "_f16acc_l", NAMELC ## _f16acc_len, NAMELC ##  _f16acc_data, "main", PARAMCOUNT, sizeof(PUSHCONST), l_ ## WG_DENOMS, l_ ## WARPTILE, 1);   \
-            ggml_vk_create_pipeline(device, device-> PIPELINE_NAME .f32acc->l, #NAMELC        "_l", NAMELC ## _len,        NAMELC ##  _data,        "main", PARAMCOUNT, sizeof(PUSHCONST), l_ ## WG_DENOMS, l_ ## WARPTILE, 1);   \
+            ggml_vk_create_pipeline(device, device-> PIPELINE_NAME .f32acc->l, #NAMELC        "_l", NAMELC ## _len,        NAMELC ##  _data,        "main", PARAMCOUNT, sizeof(PUSHCONST), l_ ## WG_DENOMS, l_ ## WARPTILE, 1, false, REQSUBGROUPSIZE > 0, REQSUBGROUPSIZE);   \
         } \
         if (device->mul_mat ## ID ## _m[TYPE]) { \
-            ggml_vk_create_pipeline(device, device-> PIPELINE_NAME .f16acc->m, #NAMELC "_f16acc_m", NAMELC ## _f16acc_len, NAMELC ##  _f16acc_data, "main", PARAMCOUNT, sizeof(PUSHCONST), m_ ## WG_DENOMS, m_ ## WARPTILE, 1);   \
-            ggml_vk_create_pipeline(device, device-> PIPELINE_NAME .f32acc->m, #NAMELC        "_m", NAMELC ## _len,        NAMELC ##  _data,        "main", PARAMCOUNT, sizeof(PUSHCONST), m_ ## WG_DENOMS, m_ ## WARPTILE, 1);   \
+            ggml_vk_create_pipeline(device, device-> PIPELINE_NAME .f32acc->m, #NAMELC        "_m", NAMELC ## _len,        NAMELC ##  _data,        "main", PARAMCOUNT, sizeof(PUSHCONST), m_ ## WG_DENOMS, m_ ## WARPTILE, 1, false, REQSUBGROUPSIZE > 0, REQSUBGROUPSIZE);   \
         } \
         if (device->mul_mat ## ID ## _s[TYPE]) { \
-            ggml_vk_create_pipeline(device, device-> PIPELINE_NAME .f16acc->s, #NAMELC "_f16acc_s", NAMELC ## _f16acc_len, NAMELC ##  _f16acc_data, "main", PARAMCOUNT, sizeof(PUSHCONST), s_ ## WG_DENOMS, s_ ## WARPTILE, 1);   \
-            ggml_vk_create_pipeline(device, device-> PIPELINE_NAME .f32acc->s, #NAMELC        "_s", NAMELC ## _len,        NAMELC ##  _data,        "main", PARAMCOUNT, sizeof(PUSHCONST), s_ ## WG_DENOMS, s_ ## WARPTILE, 1);   \
+            ggml_vk_create_pipeline(device, device-> PIPELINE_NAME .f32acc->s, #NAMELC        "_s", NAMELC ## _len,        NAMELC ##  _data,        "main", PARAMCOUNT, sizeof(PUSHCONST), s_ ## WG_DENOMS, s_ ## WARPTILE, 1, false, REQSUBGROUPSIZE > 0, REQSUBGROUPSIZE);   \
         } \
 
         // Create 2 variants, {f16,f32} accumulator
@@ -2963,11 +3059,19 @@ static void ggml_vk_load_shaders(vk_device& device) {
 
 #if defined(GGML_VULKAN_INTEGER_DOT_GLSLC_SUPPORT)
         if (device->integer_dot_product) {
-            CREATE_MMQ(GGML_TYPE_Q4_0, pipeline_dequant_mul_mat_mat_q8_1[GGML_TYPE_Q4_0], matmul_q4_0_q8_1, mmq_wg_denoms, warptile_mmq_int, vk_mat_mat_push_constants, 3, );
-            CREATE_MMQ(GGML_TYPE_Q4_1, pipeline_dequant_mul_mat_mat_q8_1[GGML_TYPE_Q4_1], matmul_q4_1_q8_1, mmq_wg_denoms, warptile_mmq_int, vk_mat_mat_push_constants, 3, );
-            CREATE_MMQ(GGML_TYPE_Q5_0, pipeline_dequant_mul_mat_mat_q8_1[GGML_TYPE_Q5_0], matmul_q5_0_q8_1, mmq_wg_denoms, warptile_mmq_int, vk_mat_mat_push_constants, 3, );
-            CREATE_MMQ(GGML_TYPE_Q5_1, pipeline_dequant_mul_mat_mat_q8_1[GGML_TYPE_Q5_1], matmul_q5_1_q8_1, mmq_wg_denoms, warptile_mmq_int, vk_mat_mat_push_constants, 3, );
-            CREATE_MMQ(GGML_TYPE_Q8_0, pipeline_dequant_mul_mat_mat_q8_1[GGML_TYPE_Q8_0], matmul_q8_0_q8_1, mmq_wg_denoms, warptile_mmq_int, vk_mat_mat_push_constants, 3, );
+            CREATE_MMQ(GGML_TYPE_Q4_0, pipeline_dequant_mul_mat_mat_q8_1[GGML_TYPE_Q4_0], matmul_q4_0_q8_1, mmq_wg_denoms, warptile_mmq_int, vk_mat_mat_push_constants, 3, , 0);
+            CREATE_MMQ(GGML_TYPE_Q4_1, pipeline_dequant_mul_mat_mat_q8_1[GGML_TYPE_Q4_1], matmul_q4_1_q8_1, mmq_wg_denoms, warptile_mmq_int, vk_mat_mat_push_constants, 3, , 0);
+            CREATE_MMQ(GGML_TYPE_Q5_0, pipeline_dequant_mul_mat_mat_q8_1[GGML_TYPE_Q5_0], matmul_q5_0_q8_1, mmq_wg_denoms, warptile_mmq_int, vk_mat_mat_push_constants, 3, , 0);
+            CREATE_MMQ(GGML_TYPE_Q5_1, pipeline_dequant_mul_mat_mat_q8_1[GGML_TYPE_Q5_1], matmul_q5_1_q8_1, mmq_wg_denoms, warptile_mmq_int, vk_mat_mat_push_constants, 3, , 0);
+            CREATE_MMQ(GGML_TYPE_Q8_0, pipeline_dequant_mul_mat_mat_q8_1[GGML_TYPE_Q8_0], matmul_q8_0_q8_1, mmq_wg_denoms, warptile_mmq_int, vk_mat_mat_push_constants, 3, , 0);
+
+            CREATE_MMQ(GGML_TYPE_MXFP4, pipeline_dequant_mul_mat_mat_q8_1[GGML_TYPE_MXFP4], matmul_mxfp4_q8_1, mmq_wg_denoms, warptile_mmq_int, vk_mat_mat_push_constants, 3, , 0);
+
+            CREATE_MMQ(GGML_TYPE_Q2_K, pipeline_dequant_mul_mat_mat_q8_1[GGML_TYPE_Q2_K], matmul_q2_k_q8_1, mmq_wg_denoms, warptile_mmq_int_k, vk_mat_mat_push_constants, 3, , 0);
+            CREATE_MMQ(GGML_TYPE_Q3_K, pipeline_dequant_mul_mat_mat_q8_1[GGML_TYPE_Q3_K], matmul_q3_k_q8_1, mmq_wg_denoms, warptile_mmq_int_k, vk_mat_mat_push_constants, 3, , 0);
+            CREATE_MMQ(GGML_TYPE_Q4_K, pipeline_dequant_mul_mat_mat_q8_1[GGML_TYPE_Q4_K], matmul_q4_k_q8_1, mmq_wg_denoms, warptile_mmq_int_k, vk_mat_mat_push_constants, 3, , 0);
+            CREATE_MMQ(GGML_TYPE_Q5_K, pipeline_dequant_mul_mat_mat_q8_1[GGML_TYPE_Q5_K], matmul_q5_k_q8_1, mmq_wg_denoms, warptile_mmq_int_k, vk_mat_mat_push_constants, 3, , 0);
+            CREATE_MMQ(GGML_TYPE_Q6_K, pipeline_dequant_mul_mat_mat_q8_1[GGML_TYPE_Q6_K], matmul_q6_k_q8_1, mmq_wg_denoms, warptile_mmq_int_k, vk_mat_mat_push_constants, 3, , 0);
         }
 #endif
 
@@ -2997,6 +3101,24 @@ static void ggml_vk_load_shaders(vk_device& device) {
             CREATE_MM2(GGML_TYPE_IQ4_XS,  pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ4_XS],  matmul_id_subgroup_iq4_xs_f32,  mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4, _id, mul_mat_subgroup_size);
             CREATE_MM2(GGML_TYPE_IQ4_NL,  pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ4_NL],  matmul_id_subgroup_iq4_nl_f32,  mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4, _id, mul_mat_subgroup_size);
             CREATE_MM2(GGML_TYPE_MXFP4,   pipeline_dequant_mul_mat_mat_id[GGML_TYPE_MXFP4],   matmul_id_subgroup_mxfp4_f32,   mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4, _id, mul_mat_subgroup_size);
+
+#if defined(GGML_VULKAN_INTEGER_DOT_GLSLC_SUPPORT)
+            if (device->integer_dot_product) {
+                CREATE_MMQ(GGML_TYPE_Q4_0, pipeline_dequant_mul_mat_mat_id_q8_1[GGML_TYPE_Q4_0], matmul_id_subgroup_q4_0_q8_1, mmq_wg_denoms, warptile_mmqid_int,   vk_mat_mat_id_push_constants, 4, _id, mul_mat_subgroup_size);
+                CREATE_MMQ(GGML_TYPE_Q4_1, pipeline_dequant_mul_mat_mat_id_q8_1[GGML_TYPE_Q4_1], matmul_id_subgroup_q4_1_q8_1, mmq_wg_denoms, warptile_mmqid_int,   vk_mat_mat_id_push_constants, 4, _id, mul_mat_subgroup_size);
+                CREATE_MMQ(GGML_TYPE_Q5_0, pipeline_dequant_mul_mat_mat_id_q8_1[GGML_TYPE_Q5_0], matmul_id_subgroup_q5_0_q8_1, mmq_wg_denoms, warptile_mmqid_int,   vk_mat_mat_id_push_constants, 4, _id, mul_mat_subgroup_size);
+                CREATE_MMQ(GGML_TYPE_Q5_1, pipeline_dequant_mul_mat_mat_id_q8_1[GGML_TYPE_Q5_1], matmul_id_subgroup_q5_1_q8_1, mmq_wg_denoms, warptile_mmqid_int,   vk_mat_mat_id_push_constants, 4, _id, mul_mat_subgroup_size);
+                CREATE_MMQ(GGML_TYPE_Q8_0, pipeline_dequant_mul_mat_mat_id_q8_1[GGML_TYPE_Q8_0], matmul_id_subgroup_q8_0_q8_1, mmq_wg_denoms, warptile_mmqid_int,   vk_mat_mat_id_push_constants, 4, _id, mul_mat_subgroup_size);
+
+                CREATE_MMQ(GGML_TYPE_MXFP4, pipeline_dequant_mul_mat_mat_id_q8_1[GGML_TYPE_MXFP4], matmul_id_subgroup_mxfp4_q8_1, mmq_wg_denoms, warptile_mmqid_int,   vk_mat_mat_id_push_constants, 4, _id, mul_mat_subgroup_size);
+
+                CREATE_MMQ(GGML_TYPE_Q2_K, pipeline_dequant_mul_mat_mat_id_q8_1[GGML_TYPE_Q2_K], matmul_id_subgroup_q2_k_q8_1, mmq_wg_denoms, warptile_mmqid_int_k, vk_mat_mat_id_push_constants, 4, _id, mul_mat_subgroup_size_16);
+                CREATE_MMQ(GGML_TYPE_Q3_K, pipeline_dequant_mul_mat_mat_id_q8_1[GGML_TYPE_Q3_K], matmul_id_subgroup_q3_k_q8_1, mmq_wg_denoms, warptile_mmqid_int_k, vk_mat_mat_id_push_constants, 4, _id, mul_mat_subgroup_size_16);
+                CREATE_MMQ(GGML_TYPE_Q4_K, pipeline_dequant_mul_mat_mat_id_q8_1[GGML_TYPE_Q4_K], matmul_id_subgroup_q4_k_q8_1, mmq_wg_denoms, warptile_mmqid_int_k, vk_mat_mat_id_push_constants, 4, _id, mul_mat_subgroup_size_16);
+                CREATE_MMQ(GGML_TYPE_Q5_K, pipeline_dequant_mul_mat_mat_id_q8_1[GGML_TYPE_Q5_K], matmul_id_subgroup_q5_k_q8_1, mmq_wg_denoms, warptile_mmqid_int_k, vk_mat_mat_id_push_constants, 4, _id, mul_mat_subgroup_size_16);
+                CREATE_MMQ(GGML_TYPE_Q6_K, pipeline_dequant_mul_mat_mat_id_q8_1[GGML_TYPE_Q6_K], matmul_id_subgroup_q6_k_q8_1, mmq_wg_denoms, warptile_mmqid_int_k, vk_mat_mat_id_push_constants, 4, _id, mul_mat_subgroup_size_16);
+            }
+#endif
         } else {
             CREATE_MM(GGML_TYPE_F32, pipeline_matmul_id_f32, matmul_id_f32_f32, , wg_denoms, warptile, vk_mat_mat_push_constants, 4, _id, 0);
             CREATE_MM2(GGML_TYPE_F16, pipeline_matmul_id_f16, matmul_id_f16, wg_denoms, warptile, vk_mat_mat_push_constants, 4, _id, 0);
@@ -3023,6 +3145,24 @@ static void ggml_vk_load_shaders(vk_device& device) {
             CREATE_MM2(GGML_TYPE_IQ4_XS,  pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ4_XS],  matmul_id_iq4_xs_f32,  mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4, _id, 0);
             CREATE_MM2(GGML_TYPE_IQ4_NL,  pipeline_dequant_mul_mat_mat_id[GGML_TYPE_IQ4_NL],  matmul_id_iq4_nl_f32,  mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4, _id, 0);
             CREATE_MM2(GGML_TYPE_MXFP4,   pipeline_dequant_mul_mat_mat_id[GGML_TYPE_MXFP4],   matmul_id_mxfp4_f32,   mmq_wg_denoms, warptile_mmqid, vk_mat_mat_id_push_constants, 4, _id, 0);
+
+#if defined(GGML_VULKAN_INTEGER_DOT_GLSLC_SUPPORT)
+            if (device->integer_dot_product) {
+                CREATE_MMQ(GGML_TYPE_Q4_0, pipeline_dequant_mul_mat_mat_id_q8_1[GGML_TYPE_Q4_0], matmul_id_q4_0_q8_1, mmq_wg_denoms, warptile_mmqid_int,   vk_mat_mat_id_push_constants, 4, _id, 0);
+                CREATE_MMQ(GGML_TYPE_Q4_1, pipeline_dequant_mul_mat_mat_id_q8_1[GGML_TYPE_Q4_1], matmul_id_q4_1_q8_1, mmq_wg_denoms, warptile_mmqid_int,   vk_mat_mat_id_push_constants, 4, _id, 0);
+                CREATE_MMQ(GGML_TYPE_Q5_0, pipeline_dequant_mul_mat_mat_id_q8_1[GGML_TYPE_Q5_0], matmul_id_q5_0_q8_1, mmq_wg_denoms, warptile_mmqid_int,   vk_mat_mat_id_push_constants, 4, _id, 0);
+                CREATE_MMQ(GGML_TYPE_Q5_1, pipeline_dequant_mul_mat_mat_id_q8_1[GGML_TYPE_Q5_1], matmul_id_q5_1_q8_1, mmq_wg_denoms, warptile_mmqid_int,   vk_mat_mat_id_push_constants, 4, _id, 0);
+                CREATE_MMQ(GGML_TYPE_Q8_0, pipeline_dequant_mul_mat_mat_id_q8_1[GGML_TYPE_Q8_0], matmul_id_q8_0_q8_1, mmq_wg_denoms, warptile_mmqid_int,   vk_mat_mat_id_push_constants, 4, _id, 0);
+
+                CREATE_MMQ(GGML_TYPE_MXFP4, pipeline_dequant_mul_mat_mat_id_q8_1[GGML_TYPE_MXFP4], matmul_id_mxfp4_q8_1, mmq_wg_denoms, warptile_mmqid_int,   vk_mat_mat_id_push_constants, 4, _id, 0);
+
+                CREATE_MMQ(GGML_TYPE_Q2_K, pipeline_dequant_mul_mat_mat_id_q8_1[GGML_TYPE_Q2_K], matmul_id_q2_k_q8_1, mmq_wg_denoms, warptile_mmqid_int_k, vk_mat_mat_id_push_constants, 4, _id, 0);
+                CREATE_MMQ(GGML_TYPE_Q3_K, pipeline_dequant_mul_mat_mat_id_q8_1[GGML_TYPE_Q3_K], matmul_id_q3_k_q8_1, mmq_wg_denoms, warptile_mmqid_int_k, vk_mat_mat_id_push_constants, 4, _id, 0);
+                CREATE_MMQ(GGML_TYPE_Q4_K, pipeline_dequant_mul_mat_mat_id_q8_1[GGML_TYPE_Q4_K], matmul_id_q4_k_q8_1, mmq_wg_denoms, warptile_mmqid_int_k, vk_mat_mat_id_push_constants, 4, _id, 0);
+                CREATE_MMQ(GGML_TYPE_Q5_K, pipeline_dequant_mul_mat_mat_id_q8_1[GGML_TYPE_Q5_K], matmul_id_q5_k_q8_1, mmq_wg_denoms, warptile_mmqid_int_k, vk_mat_mat_id_push_constants, 4, _id, 0);
+                CREATE_MMQ(GGML_TYPE_Q6_K, pipeline_dequant_mul_mat_mat_id_q8_1[GGML_TYPE_Q6_K], matmul_id_q6_k_q8_1, mmq_wg_denoms, warptile_mmqid_int_k, vk_mat_mat_id_push_constants, 4, _id, 0);
+            }
+#endif
         }
 #undef CREATE_MM2
 #undef CREATE_MMQ
@@ -3087,6 +3227,12 @@ static void ggml_vk_load_shaders(vk_device& device) {
             CREATE_MMQ(GGML_TYPE_Q5_0, pipeline_dequant_mul_mat_mat_q8_1[GGML_TYPE_Q5_0].f32acc, matmul_q5_0_q8_1, mmq_wg_denoms, warptile_mmq_int, vk_mat_mat_push_constants, 3, );
             CREATE_MMQ(GGML_TYPE_Q5_1, pipeline_dequant_mul_mat_mat_q8_1[GGML_TYPE_Q5_1].f32acc, matmul_q5_1_q8_1, mmq_wg_denoms, warptile_mmq_int, vk_mat_mat_push_constants, 3, );
             CREATE_MMQ(GGML_TYPE_Q8_0, pipeline_dequant_mul_mat_mat_q8_1[GGML_TYPE_Q8_0].f32acc, matmul_q8_0_q8_1, mmq_wg_denoms, warptile_mmq_int, vk_mat_mat_push_constants, 3, );
+
+            CREATE_MMQ(GGML_TYPE_Q2_K, pipeline_dequant_mul_mat_mat_q8_1[GGML_TYPE_Q2_K].f32acc, matmul_q2_k_q8_1, mmq_wg_denoms, warptile_mmq_int_k, vk_mat_mat_push_constants, 3, );
+            CREATE_MMQ(GGML_TYPE_Q3_K, pipeline_dequant_mul_mat_mat_q8_1[GGML_TYPE_Q3_K].f32acc, matmul_q3_k_q8_1, mmq_wg_denoms, warptile_mmq_int_k, vk_mat_mat_push_constants, 3, );
+            CREATE_MMQ(GGML_TYPE_Q4_K, pipeline_dequant_mul_mat_mat_q8_1[GGML_TYPE_Q4_K].f32acc, matmul_q4_k_q8_1, mmq_wg_denoms, warptile_mmq_int_k, vk_mat_mat_push_constants, 3, );
+            CREATE_MMQ(GGML_TYPE_Q5_K, pipeline_dequant_mul_mat_mat_q8_1[GGML_TYPE_Q5_K].f32acc, matmul_q5_k_q8_1, mmq_wg_denoms, warptile_mmq_int_k, vk_mat_mat_push_constants, 3, );
+            CREATE_MMQ(GGML_TYPE_Q6_K, pipeline_dequant_mul_mat_mat_q8_1[GGML_TYPE_Q6_K].f32acc, matmul_q6_k_q8_1, mmq_wg_denoms, warptile_mmq_int_k, vk_mat_mat_push_constants, 3, );
         }
 #endif
 
@@ -3146,7 +3292,7 @@ static void ggml_vk_load_shaders(vk_device& device) {
     }
     // reusing CREATE_MM from the fp32 path
     if ((device->coopmat2 || device->coopmat_support)
-#if defined(GGML_VULKAN_INTEGER_DOT_GLSLC_SUPPORT)
+#if defined(GGML_VULKAN_BFLOAT16_GLSLC_SUPPORT)
         && !device->coopmat_bf16_support
 #endif
         ) {
@@ -3567,21 +3713,27 @@ static void ggml_vk_load_shaders(vk_device& device) {
     ggml_vk_create_pipeline(device, device->pipeline_soft_max_f32_f16_wg512, "soft_max_f32_f16_wg512", soft_max_f32_f16_len, soft_max_f32_f16_data, "main", 4, sizeof(vk_op_soft_max_push_constants), {1, 1, 1}, { 512 }, 1);
     ggml_vk_create_pipeline(device, device->pipeline_soft_max_back_f32, "soft_max_back_f32", soft_max_back_f32_len, soft_max_back_f32_data, "main", 3, sizeof(vk_op_push_constants), {1, 1, 1}, { device->subgroup_size }, 1, true);
 
-    ggml_vk_create_pipeline(device, device->pipeline_rope_norm_f32, "rope_norm_f32", rope_norm_f32_len, rope_norm_f32_data, "main", 4, sizeof(vk_op_rope_push_constants), {1, 512, 1}, {}, 1);
-    ggml_vk_create_pipeline(device, device->pipeline_rope_neox_f32, "rope_neox_f32", rope_neox_f32_len, rope_neox_f32_data, "main", 4, sizeof(vk_op_rope_push_constants), {1, 512, 1}, {}, 1);
-    ggml_vk_create_pipeline(device, device->pipeline_rope_multi_f32, "rope_multi_f32", rope_multi_f32_len, rope_multi_f32_data, "main", 4, sizeof(vk_op_rope_push_constants), {1, 512, 1}, {}, 1);
-    ggml_vk_create_pipeline(device, device->pipeline_rope_vision_f32, "rope_vision_f32", rope_vision_f32_len, rope_vision_f32_data, "main", 4, sizeof(vk_op_rope_push_constants), {1, 512, 1}, {}, 1);
+    ggml_vk_create_pipeline(device, device->pipeline_rope_norm_f32, "rope_norm_f32", rope_norm_f32_len, rope_norm_f32_data, "main", 5, sizeof(vk_op_rope_push_constants), {1, 512, 1}, {}, 1);
+    ggml_vk_create_pipeline(device, device->pipeline_rope_neox_f32, "rope_neox_f32", rope_neox_f32_len, rope_neox_f32_data, "main", 5, sizeof(vk_op_rope_push_constants), {1, 512, 1}, {}, 1);
+    ggml_vk_create_pipeline(device, device->pipeline_rope_multi_f32, "rope_multi_f32", rope_multi_f32_len, rope_multi_f32_data, "main", 5, sizeof(vk_op_rope_push_constants), {1, 512, 1}, {}, 1);
+    ggml_vk_create_pipeline(device, device->pipeline_rope_vision_f32, "rope_vision_f32", rope_vision_f32_len, rope_vision_f32_data, "main", 5, sizeof(vk_op_rope_push_constants), {1, 512, 1}, {}, 1);
 
     if (device->float_controls_rte_fp16) {
-        ggml_vk_create_pipeline(device, device->pipeline_rope_norm_f16, "rope_norm_f16", rope_norm_f16_rte_len, rope_norm_f16_rte_data, "main", 4, sizeof(vk_op_rope_push_constants), {1, 512, 1}, {}, 1);
-        ggml_vk_create_pipeline(device, device->pipeline_rope_neox_f16, "rope_neox_f16", rope_neox_f16_rte_len, rope_neox_f16_rte_data, "main", 4, sizeof(vk_op_rope_push_constants), {1, 512, 1}, {}, 1);
-        ggml_vk_create_pipeline(device, device->pipeline_rope_multi_f16, "rope_multi_f16", rope_multi_f16_rte_len, rope_multi_f16_rte_data, "main", 4, sizeof(vk_op_rope_push_constants), {1, 512, 1}, {}, 1);
-        ggml_vk_create_pipeline(device, device->pipeline_rope_vision_f16, "rope_vision_f16", rope_vision_f16_rte_len, rope_vision_f16_rte_data, "main", 4, sizeof(vk_op_rope_push_constants), {1, 512, 1}, {}, 1);
+        ggml_vk_create_pipeline(device, device->pipeline_rope_norm_f16, "rope_norm_f16", rope_norm_f16_rte_len, rope_norm_f16_rte_data, "main", 5, sizeof(vk_op_rope_push_constants), {1, 512, 1}, {}, 1);
+        ggml_vk_create_pipeline(device, device->pipeline_rope_neox_f16, "rope_neox_f16", rope_neox_f16_rte_len, rope_neox_f16_rte_data, "main", 5, sizeof(vk_op_rope_push_constants), {1, 512, 1}, {}, 1);
+        ggml_vk_create_pipeline(device, device->pipeline_rope_multi_f16, "rope_multi_f16", rope_multi_f16_rte_len, rope_multi_f16_rte_data, "main", 5, sizeof(vk_op_rope_push_constants), {1, 512, 1}, {}, 1);
+        ggml_vk_create_pipeline(device, device->pipeline_rope_vision_f16, "rope_vision_f16", rope_vision_f16_rte_len, rope_vision_f16_rte_data, "main", 5, sizeof(vk_op_rope_push_constants), {1, 512, 1}, {}, 1);
+
+        ggml_vk_create_pipeline(device, device->pipeline_rope_norm_f32_f16, "rope_norm_f32_f16", rope_norm_f32_f16_rte_len, rope_norm_f32_f16_rte_data, "main", 5, sizeof(vk_op_rope_push_constants), {1, 512, 1}, {}, 1);
+        ggml_vk_create_pipeline(device, device->pipeline_rope_neox_f32_f16, "rope_neox_f32_f16", rope_neox_f32_f16_rte_len, rope_neox_f32_f16_rte_data, "main", 5, sizeof(vk_op_rope_push_constants), {1, 512, 1}, {}, 1);
     } else {
-        ggml_vk_create_pipeline(device, device->pipeline_rope_norm_f16, "rope_norm_f16", rope_norm_f16_len, rope_norm_f16_data, "main", 4, sizeof(vk_op_rope_push_constants), {1, 512, 1}, {}, 1);
-        ggml_vk_create_pipeline(device, device->pipeline_rope_neox_f16, "rope_neox_f16", rope_neox_f16_len, rope_neox_f16_data, "main", 4, sizeof(vk_op_rope_push_constants), {1, 512, 1}, {}, 1);
-        ggml_vk_create_pipeline(device, device->pipeline_rope_multi_f16, "rope_multi_f16", rope_multi_f16_len, rope_multi_f16_data, "main", 4, sizeof(vk_op_rope_push_constants), {1, 512, 1}, {}, 1);
-        ggml_vk_create_pipeline(device, device->pipeline_rope_vision_f16, "rope_vision_f16", rope_vision_f16_len, rope_vision_f16_data, "main", 4, sizeof(vk_op_rope_push_constants), {1, 512, 1}, {}, 1);
+        ggml_vk_create_pipeline(device, device->pipeline_rope_norm_f16, "rope_norm_f16", rope_norm_f16_len, rope_norm_f16_data, "main", 5, sizeof(vk_op_rope_push_constants), {1, 512, 1}, {}, 1);
+        ggml_vk_create_pipeline(device, device->pipeline_rope_neox_f16, "rope_neox_f16", rope_neox_f16_len, rope_neox_f16_data, "main", 5, sizeof(vk_op_rope_push_constants), {1, 512, 1}, {}, 1);
+        ggml_vk_create_pipeline(device, device->pipeline_rope_multi_f16, "rope_multi_f16", rope_multi_f16_len, rope_multi_f16_data, "main", 5, sizeof(vk_op_rope_push_constants), {1, 512, 1}, {}, 1);
+        ggml_vk_create_pipeline(device, device->pipeline_rope_vision_f16, "rope_vision_f16", rope_vision_f16_len, rope_vision_f16_data, "main", 5, sizeof(vk_op_rope_push_constants), {1, 512, 1}, {}, 1);
+
+        ggml_vk_create_pipeline(device, device->pipeline_rope_norm_f32_f16, "rope_norm_f32_f16", rope_norm_f32_f16_len, rope_norm_f32_f16_data, "main", 5, sizeof(vk_op_rope_push_constants), {1, 512, 1}, {}, 1);
+        ggml_vk_create_pipeline(device, device->pipeline_rope_neox_f32_f16, "rope_neox_f32_f16", rope_neox_f32_f16_len, rope_neox_f32_f16_data, "main", 5, sizeof(vk_op_rope_push_constants), {1, 512, 1}, {}, 1);
     }
 
     for (uint32_t i = 0; i < num_argsort_pipelines; ++i) {
@@ -3741,8 +3893,9 @@ static void ggml_vk_load_shaders(vk_device& device) {
     ggml_vk_create_pipeline(device, device->pipeline_conv2d_dw_cwhn_f16_f32, "conv2d_dw_cwhn_f16_f32", conv2d_dw_cwhn_f16_f32_len, conv2d_dw_cwhn_f16_f32_data, "main", 3, sizeof(vk_op_conv2d_dw_push_constants), {512, 1, 1}, {}, 1);
 
     for (uint32_t i = 0; i < num_topk_moe_pipelines; ++i) {
-        ggml_vk_create_pipeline2(device, device->pipeline_topk_moe[i][0], "topk_moe_f32_"+std::to_string(i),   topk_moe_f32_len, topk_moe_f32_data, "main", 3, sizeof(vk_op_topk_moe_push_constants), {1, 1, 1}, {device->subgroup_size, 1u<<i, 0}, 1, true, true);
-        ggml_vk_create_pipeline2(device, device->pipeline_topk_moe[i][1], "topk_moe_f32_"+std::to_string(i),   topk_moe_f32_len, topk_moe_f32_data, "main", 3, sizeof(vk_op_topk_moe_push_constants), {1, 1, 1}, {device->subgroup_size, 1u<<i, 1}, 1, true, true);
+        ggml_vk_create_pipeline2(device, device->pipeline_topk_moe[i][TOPK_MOE_EARLY_SOFTMAX],      "topk_moe_f32_early_softmax_"+std::to_string(i),       topk_moe_f32_len, topk_moe_f32_data, "main", 3, sizeof(vk_op_topk_moe_push_constants), {1, 1, 1}, {device->subgroup_size, 1u<<i, 0, 0}, 1, true, true);
+        ggml_vk_create_pipeline2(device, device->pipeline_topk_moe[i][TOPK_MOE_EARLY_SOFTMAX_NORM], "topk_moe_f32_early_softmax_norm"+std::to_string(i),   topk_moe_f32_len, topk_moe_f32_data, "main", 3, sizeof(vk_op_topk_moe_push_constants), {1, 1, 1}, {device->subgroup_size, 1u<<i, 1, 0}, 1, true, true);
+        ggml_vk_create_pipeline2(device, device->pipeline_topk_moe[i][TOPK_MOE_LATE_SOFTMAX],       "topk_moe_f32_late_softmax"+std::to_string(i),         topk_moe_f32_len, topk_moe_f32_data, "main", 3, sizeof(vk_op_topk_moe_push_constants), {1, 1, 1}, {device->subgroup_size, 1u<<i, 0, 1}, 1, true, true);
     }
 
     for (auto &c : compiles) {
@@ -4930,9 +5083,9 @@ static vk_matmul_pipeline ggml_vk_get_mul_mat_mat_pipeline(ggml_backend_vk_conte
 
     // MMQ
     if (src1_type == GGML_TYPE_Q8_1) {
-        vk_matmul_pipeline pipelines = (ctx->device->fp16 && prec == GGML_PREC_DEFAULT) ? ctx->device->pipeline_dequant_mul_mat_mat_q8_1[src0_type].f16acc : ctx->device->pipeline_dequant_mul_mat_mat_q8_1[src0_type].f32acc;
+        vk_matmul_pipeline pipelines = ctx->device->pipeline_dequant_mul_mat_mat_q8_1[src0_type].f32acc;
 
-        if (pipelines->s == nullptr && pipelines->m == nullptr && pipelines->l == nullptr) {
+        if (pipelines->is_empty()) {
             return nullptr;
         }
 
@@ -5077,6 +5230,17 @@ static vk_matmul_pipeline ggml_vk_get_mul_mat_mat_id_pipeline(ggml_backend_vk_co
         }
     }
 
+    // MMQ
+    if (src1_type == GGML_TYPE_Q8_1) {
+        vk_matmul_pipeline pipelines = ctx->device->pipeline_dequant_mul_mat_mat_id_q8_1[src0_type].f32acc;
+
+        if (pipelines->is_empty()) {
+            return nullptr;
+        }
+
+        return pipelines;
+    }
+
     GGML_ASSERT(src1_type == GGML_TYPE_F32 || (ctx->device->coopmat2 && src1_type == GGML_TYPE_F16));
 
     switch (src0_type) {
@@ -5105,16 +5269,17 @@ static vk_matmul_pipeline ggml_vk_get_mul_mat_mat_id_pipeline(ggml_backend_vk_co
             return nullptr;
     }
 
+    vk_matmul_pipeline2& mmp = ctx->device->pipeline_dequant_mul_mat_mat_id[src0_type];
     // XXX TODO 'prec' is not actually allowed in mul_mat_id.
     bool prefer_fp16acc = ctx->device->fp16 /*&& prec == GGML_PREC_DEFAULT*/;
-    bool support_fp16acc = ctx->device->pipeline_dequant_mul_mat_mat_id[src0_type].f16acc != nullptr;
-    bool support_fp32acc = ctx->device->pipeline_dequant_mul_mat_mat_id[src0_type].f32acc != nullptr;
+    bool support_fp16acc = !mmp.f16acc->is_empty();
+    bool support_fp32acc = !mmp.f32acc->is_empty();
 
     if (support_fp16acc && (prefer_fp16acc || !support_fp32acc)) {
-        return ctx->device->pipeline_dequant_mul_mat_mat_id[src0_type].f16acc;
+        return mmp.f16acc;
     } else {
         GGML_ASSERT(support_fp32acc);
-        return ctx->device->pipeline_dequant_mul_mat_mat_id[src0_type].f32acc;
+        return mmp.f32acc;
     }
 }
 
@@ -5654,14 +5819,11 @@ static void ggml_vk_buffer_copy(vk_buffer& dst, size_t dst_offset, vk_buffer& sr
         VK_LOG_DEBUG("ggml_vk_buffer_copy(MULTI_DEVICE, " << size << ")");
         // Copy device to device
         ggml_vk_ensure_sync_staging_buffer(src->device, size);
-        ggml_vk_ensure_sync_staging_buffer(dst->device, size);
 
         // Copy to src staging buffer
         ggml_vk_buffer_copy(src->device->sync_staging, 0, src, src_offset, size);
-        // memcpy to dst staging buffer
-        memcpy(dst->device->sync_staging->ptr, src->device->sync_staging->ptr, size);
         // Copy to dst buffer
-        ggml_vk_buffer_copy(dst, dst_offset, dst->device->sync_staging, 0, size);
+        ggml_vk_buffer_write_2d(dst, dst_offset, src->device->sync_staging->ptr, 0, size, 1);
     }
 }
 
@@ -6882,10 +7044,19 @@ static void ggml_vk_mul_mat_id_q_f16(ggml_backend_vk_context * ctx, vk_context&
 
     const bool y_f32_kernel = src1->type == GGML_TYPE_F32 && !y_non_contig;
 
-    vk_matmul_pipeline mmp = ggml_vk_get_mul_mat_mat_id_pipeline(ctx, src0->type, y_non_contig ? f16_type : src1->type, (ggml_prec)dst->op_params[0]);
+    bool quantize_y = ctx->device->integer_dot_product && src1->type == GGML_TYPE_F32 && ggml_is_contiguous(src1) && (ne11 * ne10) % 4 == 0;
+
+    // Check for mmq first
+    vk_matmul_pipeline mmp = quantize_y ? ggml_vk_get_mul_mat_mat_id_pipeline(ctx, src0->type, GGML_TYPE_Q8_1, (ggml_prec)dst->op_params[0]) : nullptr;
+
+    if (mmp == nullptr) {
+        // Fall back to f16 dequant mul mat
+        mmp = ggml_vk_get_mul_mat_mat_id_pipeline(ctx, src0->type, y_non_contig ? f16_type : src1->type, (ggml_prec)dst->op_params[0]);
+        quantize_y = false;
+    }
 
     const bool qx_needs_dequant = mmp == nullptr || x_non_contig;
-    const bool qy_needs_dequant = (src1->type != f16_type && !y_f32_kernel) || y_non_contig;
+    const bool qy_needs_dequant = !quantize_y && ((src1->type != f16_type && !y_f32_kernel) || y_non_contig);
 
     if (qx_needs_dequant) {
         // Fall back to dequant + f16 mulmat
@@ -6895,8 +7066,8 @@ static void ggml_vk_mul_mat_id_q_f16(ggml_backend_vk_context * ctx, vk_context&
     // Not implemented
     GGML_ASSERT(y_non_contig || !qy_needs_dequant);  // NOLINT
 
-    const uint32_t kpad = ggml_vk_align_size(ne10, ggml_vk_guess_matmul_id_pipeline_align(ctx, mmp, ne01, nei1, qx_needs_dequant ? f16_type : src0->type));
-    const bool aligned = ne10 == kpad && ne01 > 8 && nei1 > 8;
+    const uint32_t kpad = quantize_y ? 0 : ggml_vk_align_size(ne10, ggml_vk_guess_matmul_id_pipeline_align(ctx, mmp, ne01, nei1, qx_needs_dequant ? f16_type : src0->type));
+    const bool aligned = !quantize_y && ne10 == kpad && ne01 > 8 && nei1 > 8;
 
     vk_pipeline pipeline = ggml_vk_guess_matmul_id_pipeline(ctx, mmp, ne01, nei1, aligned, qx_needs_dequant ? f16_type : src0->type);
 
@@ -6909,12 +7080,13 @@ static void ggml_vk_mul_mat_id_q_f16(ggml_backend_vk_context * ctx, vk_context&
     const uint64_t qx_sz = ggml_type_size(src0->type) * x_ne / ggml_blck_size(src0->type);
     const uint64_t qy_sz = ggml_type_size(src1->type) * y_ne / ggml_blck_size(src1->type);
     const uint64_t x_sz = !qx_needs_dequant ? qx_sz : sizeof(ggml_fp16_t) * x_ne;
-    const uint64_t y_sz = y_f32_kernel ? sizeof(float) * y_ne : sizeof(ggml_fp16_t) * y_ne;
+    const uint64_t y_sz = quantize_y ? (y_ne * ggml_type_size(GGML_TYPE_Q8_1) / ggml_blck_size(GGML_TYPE_Q8_1)) : (y_f32_kernel ? sizeof(float) * y_ne : sizeof(ggml_fp16_t) * y_ne);
     const uint64_t ids_sz = nbi2;
     const uint64_t d_sz = sizeof(float) * d_ne;
 
     vk_pipeline to_fp16_vk_0 = nullptr;
     vk_pipeline to_fp16_vk_1 = nullptr;
+    vk_pipeline to_q8_1 = nullptr;
 
     if (x_non_contig) {
         to_fp16_vk_0 = ggml_vk_get_cpy_pipeline(ctx, src0, nullptr, f16_type);
@@ -6929,9 +7101,16 @@ static void ggml_vk_mul_mat_id_q_f16(ggml_backend_vk_context * ctx, vk_context&
     GGML_ASSERT(!qx_needs_dequant || to_fp16_vk_0 != nullptr);  // NOLINT
     GGML_ASSERT(!qy_needs_dequant || to_fp16_vk_1 != nullptr);  // NOLINT
 
+    if (quantize_y) {
+        to_q8_1 = ggml_vk_get_quantize_pipeline(ctx, GGML_TYPE_Q8_1, true);
+    }
+
     if (dryrun) {
         const uint64_t x_sz_upd = x_sz * ne02 * ne03;
-        const uint64_t y_sz_upd = y_sz * ne12 * ne13;
+        uint64_t y_sz_upd = y_sz * ne12 * ne13;
+        if (quantize_y) {
+            y_sz_upd = CEIL_DIV(y_sz_upd, 144) * 144;
+        }
         if (
                 (qx_needs_dequant && x_sz_upd > ctx->device->properties.limits.maxStorageBufferRange) ||
                 (qy_needs_dequant && y_sz_upd > ctx->device->properties.limits.maxStorageBufferRange)) {
@@ -6940,7 +7119,7 @@ static void ggml_vk_mul_mat_id_q_f16(ggml_backend_vk_context * ctx, vk_context&
         if (qx_needs_dequant && ctx->prealloc_size_x < x_sz_upd) {
             ctx->prealloc_size_x = x_sz_upd;
         }
-        if (qy_needs_dequant && ctx->prealloc_size_y < y_sz_upd) {
+        if ((qy_needs_dequant || quantize_y) && ctx->prealloc_size_y < y_sz_upd) {
             ctx->prealloc_size_y = y_sz_upd;
         }
 
@@ -6952,6 +7131,9 @@ static void ggml_vk_mul_mat_id_q_f16(ggml_backend_vk_context * ctx, vk_context&
         if (qy_needs_dequant) {
             ggml_pipeline_request_descriptor_sets(ctx, to_fp16_vk_1, 1);
         }
+        if (quantize_y) {
+            ggml_pipeline_request_descriptor_sets(ctx, to_q8_1, 1);
+        }
         return;
     }
 
@@ -6988,6 +7170,9 @@ static void ggml_vk_mul_mat_id_q_f16(ggml_backend_vk_context * ctx, vk_context&
     if (qy_needs_dequant) {
         d_Y = ctx->prealloc_y;
         GGML_ASSERT(d_Y->size >= y_sz * ne12 * ne13);
+    } else if (quantize_y) {
+        d_Y = ctx->prealloc_y;
+        GGML_ASSERT(d_Y->size >= CEIL_DIV(y_sz * ne12 * ne13, 144) * 144);
     } else {
         d_Y = d_Qy;
         y_buf_offset = qy_buf_offset;
@@ -7019,6 +7204,17 @@ static void ggml_vk_mul_mat_id_q_f16(ggml_backend_vk_context * ctx, vk_context&
             ctx->prealloc_y_last_tensor_used = src1;
         }
     }
+    if (quantize_y) {
+        if (ctx->prealloc_y_last_pipeline_used != to_q8_1.get() ||
+            ctx->prealloc_y_last_tensor_used != src1) {
+            if (ctx->prealloc_y_need_sync) {
+                ggml_vk_sync_buffers(ctx, subctx);
+            }
+            ggml_vk_quantize_q8_1(ctx, subctx, ggml_vk_subbuffer(ctx, d_Qy, qy_buf_offset), ggml_vk_subbuffer(ctx, d_Y, 0), y_ne * ne12 * ne13, true);
+            ctx->prealloc_y_last_pipeline_used = to_q8_1.get();
+            ctx->prealloc_y_last_tensor_used = src1;
+        }
+    }
 
     uint32_t stride_batch_x = ne00*ne01;
     uint32_t stride_batch_y = ne10*ne11;
@@ -7027,14 +7223,19 @@ static void ggml_vk_mul_mat_id_q_f16(ggml_backend_vk_context * ctx, vk_context&
         stride_batch_x = src0->nb[0] / ggml_type_size(src0->type);
     }
 
-    if (!ggml_vk_dim01_contiguous(src1) && !qy_needs_dequant) {
+    if (!ggml_vk_dim01_contiguous(src1) && !qy_needs_dequant && !quantize_y) {
         stride_batch_y = src1->nb[0] / ggml_type_size(src1->type);
     }
 
+    uint32_t y_sz_total = y_sz * ne12 * ne13;
+    if (quantize_y) {
+        y_sz_total = CEIL_DIV(y_sz_total, 144) * 144;
+    }
+
     // compute
     ggml_vk_matmul_id(
         ctx, subctx, pipeline,
-        { d_X, x_buf_offset, x_sz * ne02 * ne03 }, { d_Y, y_buf_offset, y_sz * ne12 * ne13 },
+        { d_X, x_buf_offset, x_sz * ne02 * ne03 }, { d_Y, y_buf_offset, y_sz_total },
         { d_D, d_buf_offset, d_sz * ne22 * ne23 }, { d_ids, ids_buf_offset, ids_sz },
         ne01, ne21, ne10, ne10, ne10, ne01,
         stride_batch_x, stride_batch_y, ne20*ne21,
@@ -7973,8 +8174,8 @@ static vk_pipeline ggml_vk_op_get_pipeline(ggml_backend_vk_context * ctx, const
         if (ctx->num_additional_fused_ops) {
             uint32_t idx = (uint32_t)ceilf(log2f(float(dst->ne[0])));
             GGML_ASSERT(idx < num_topk_moe_pipelines);
-            bool with_norm = ctx->num_additional_fused_ops == topk_moe_norm.size() - 1;
-            return ctx->device->pipeline_topk_moe[idx][with_norm];
+            topk_moe_mode mode = ggml_vk_num_additional_ops_to_topk_moe_mode(ctx->num_additional_fused_ops);
+            return ctx->device->pipeline_topk_moe[idx][mode];
         }
 
         if (src0->type == GGML_TYPE_F32 && (src1 == nullptr || src1->type == GGML_TYPE_F32) && dst->type == GGML_TYPE_F32) {
@@ -7992,7 +8193,8 @@ static vk_pipeline ggml_vk_op_get_pipeline(ggml_backend_vk_context * ctx, const
     case GGML_OP_ROPE:
     case GGML_OP_ROPE_BACK:
         {
-            const int mode = ((const int32_t *) dst->op_params)[2];
+            const ggml_tensor *rope = ctx->num_additional_fused_ops == 2 ? dst->src[0]->src[0] : dst;
+            const int mode = ((const int32_t *) rope->op_params)[2];
             const bool is_neox = mode & GGML_ROPE_TYPE_NEOX;
             const bool is_mrope = mode & GGML_ROPE_TYPE_MROPE;
             const bool is_vision = mode == GGML_ROPE_TYPE_VISION;
@@ -8001,6 +8203,9 @@ static vk_pipeline ggml_vk_op_get_pipeline(ggml_backend_vk_context * ctx, const
                 if (src0->type == GGML_TYPE_F32 && dst->type == GGML_TYPE_F32) {
                     return ctx->device->pipeline_rope_neox_f32;
                 }
+                if (src0->type == GGML_TYPE_F32 && dst->type == GGML_TYPE_F16) {
+                    return ctx->device->pipeline_rope_neox_f32_f16;
+                }
                 if (src0->type == GGML_TYPE_F16 && dst->type == GGML_TYPE_F16) {
                     return ctx->device->pipeline_rope_neox_f16;
                 }
@@ -8022,6 +8227,9 @@ static vk_pipeline ggml_vk_op_get_pipeline(ggml_backend_vk_context * ctx, const
                 if (src0->type == GGML_TYPE_F32 && dst->type == GGML_TYPE_F32) {
                     return ctx->device->pipeline_rope_norm_f32;
                 }
+                if (src0->type == GGML_TYPE_F32 && dst->type == GGML_TYPE_F16) {
+                    return ctx->device->pipeline_rope_norm_f32_f16;
+                }
                 if (src0->type == GGML_TYPE_F16 && dst->type == GGML_TYPE_F16) {
                     return ctx->device->pipeline_rope_norm_f16;
                 }
@@ -8029,6 +8237,13 @@ static vk_pipeline ggml_vk_op_get_pipeline(ggml_backend_vk_context * ctx, const
             return nullptr;
         }
     case GGML_OP_ARGSORT:
+        if (ctx->num_additional_fused_ops) {
+            uint32_t idx = (uint32_t)ceilf(log2f(float(dst->ne[0])));
+            GGML_ASSERT(idx < num_topk_moe_pipelines);
+            topk_moe_mode mode = ggml_vk_num_additional_ops_to_topk_moe_mode(ctx->num_additional_fused_ops);
+            return ctx->device->pipeline_topk_moe[idx][mode];
+        }
+
         if (src0->type == GGML_TYPE_F32 && dst->type == GGML_TYPE_I32) {
             uint32_t idx = (uint32_t)ceilf(log2f(float(dst->ne[0])));
             return ctx->device->pipeline_argsort_f32[idx];
@@ -8224,20 +8439,22 @@ static uint32_t get_misalign_bytes(ggml_backend_vk_context * ctx, const ggml_ten
     return ((vk_tensor_offset(t) + t->view_offs) & (ctx->device->properties.limits.minStorageBufferOffsetAlignment - 1));;
 }
 
-template <typename T> void init_pushconst_tensor_offsets(ggml_backend_vk_context * ctx, T &p, const ggml_tensor * src0, const ggml_tensor * src1, const ggml_tensor * src2, ggml_tensor * dst) {
+template <typename T> void init_pushconst_tensor_offsets(ggml_backend_vk_context * ctx, T &p, const ggml_tensor * src0, const ggml_tensor * src1, const ggml_tensor * src2, const ggml_tensor * src3, ggml_tensor * dst) {
     GGML_UNUSED(p);
     GGML_UNUSED(src0);
     GGML_UNUSED(src1);
     GGML_UNUSED(src2);
+    GGML_UNUSED(src3);
     GGML_UNUSED(dst);
     static_assert(!std::is_const<T>::value, "unexpected type");
     GGML_ASSERT(!src0 || get_misalign_bytes(ctx, src0) == 0);
     GGML_ASSERT(!src1 || get_misalign_bytes(ctx, src1) == 0);
     GGML_ASSERT(!src2 || get_misalign_bytes(ctx, src2) == 0);
+    GGML_ASSERT(!src3 || get_misalign_bytes(ctx, src3) == 0);
     GGML_ASSERT(!dst  || get_misalign_bytes(ctx, dst) == 0);
 }
 
-template <> void init_pushconst_tensor_offsets(ggml_backend_vk_context * ctx, vk_op_unary_push_constants &p, const ggml_tensor * src0, const ggml_tensor * src1, const ggml_tensor * src2, ggml_tensor * dst) {
+template <> void init_pushconst_tensor_offsets(ggml_backend_vk_context * ctx, vk_op_unary_push_constants &p, const ggml_tensor * src0, const ggml_tensor * src1, const ggml_tensor * src2, const ggml_tensor * src3, ggml_tensor * dst) {
     const uint32_t a_offset = get_misalign_bytes(ctx, src0) / ggml_type_size(src0->type);
     const uint32_t d_offset = get_misalign_bytes(ctx, dst) / ggml_type_size(dst->type);
 
@@ -8245,9 +8462,10 @@ template <> void init_pushconst_tensor_offsets(ggml_backend_vk_context * ctx, vk
 
     GGML_UNUSED(src1);
     GGML_UNUSED(src2);
+    GGML_UNUSED(src3);
 }
 
-template <> void init_pushconst_tensor_offsets(ggml_backend_vk_context * ctx, vk_op_sum_rows_push_constants &p, const ggml_tensor * src0, const ggml_tensor * src1, const ggml_tensor * src2, ggml_tensor * dst) {
+template <> void init_pushconst_tensor_offsets(ggml_backend_vk_context * ctx, vk_op_sum_rows_push_constants &p, const ggml_tensor * src0, const ggml_tensor * src1, const ggml_tensor * src2, const ggml_tensor * src3, ggml_tensor * dst) {
     const uint32_t a_offset = get_misalign_bytes(ctx, src0) / ggml_type_size(src0->type);
     const uint32_t d_offset = get_misalign_bytes(ctx, dst) / ggml_type_size(dst->type);
 
@@ -8255,9 +8473,10 @@ template <> void init_pushconst_tensor_offsets(ggml_backend_vk_context * ctx, vk
 
     GGML_UNUSED(src1);
     GGML_UNUSED(src2);
+    GGML_UNUSED(src3);
 }
 
-template <> void init_pushconst_tensor_offsets(ggml_backend_vk_context * ctx, vk_op_pad_push_constants &p, const ggml_tensor * src0, const ggml_tensor * src1, const ggml_tensor * src2, ggml_tensor * dst) {
+template <> void init_pushconst_tensor_offsets(ggml_backend_vk_context * ctx, vk_op_pad_push_constants &p, const ggml_tensor * src0, const ggml_tensor * src1, const ggml_tensor * src2, const ggml_tensor * src3, ggml_tensor * dst) {
     const uint32_t a_offset = get_misalign_bytes(ctx, src0) / ggml_type_size(src0->type);
     const uint32_t d_offset = get_misalign_bytes(ctx, dst) / ggml_type_size(dst->type);
 
@@ -8265,9 +8484,10 @@ template <> void init_pushconst_tensor_offsets(ggml_backend_vk_context * ctx, vk
 
     GGML_UNUSED(src1);
     GGML_UNUSED(src2);
+    GGML_UNUSED(src3);
 }
 
-template <> void init_pushconst_tensor_offsets(ggml_backend_vk_context * ctx, vk_op_im2col_3d_push_constants &p, const ggml_tensor * src0, const ggml_tensor * src1, const ggml_tensor * src2, ggml_tensor * dst) {
+template <> void init_pushconst_tensor_offsets(ggml_backend_vk_context * ctx, vk_op_im2col_3d_push_constants &p, const ggml_tensor * src0, const ggml_tensor * src1, const ggml_tensor * src2, const ggml_tensor * src3, ggml_tensor * dst) {
     const uint32_t a_offset = get_misalign_bytes(ctx, src1) / ggml_type_size(src1->type);
     const uint32_t d_offset = get_misalign_bytes(ctx, dst) / ggml_type_size(dst->type);
 
@@ -8275,9 +8495,10 @@ template <> void init_pushconst_tensor_offsets(ggml_backend_vk_context * ctx, vk
 
     GGML_UNUSED(src0);
     GGML_UNUSED(src2);
+    GGML_UNUSED(src3);
 }
 
-template <> void init_pushconst_tensor_offsets(ggml_backend_vk_context * ctx, vk_op_binary_push_constants &p, const ggml_tensor * src0, const ggml_tensor * src1, const ggml_tensor * src2, ggml_tensor * dst) {
+template <> void init_pushconst_tensor_offsets(ggml_backend_vk_context * ctx, vk_op_binary_push_constants &p, const ggml_tensor * src0, const ggml_tensor * src1, const ggml_tensor * src2, const ggml_tensor * src3, ggml_tensor * dst) {
     const uint32_t a_offset = get_misalign_bytes(ctx, src0) / ggml_type_size(src0->type);
     const uint32_t b_offset = get_misalign_bytes(ctx, src1) / ggml_type_size(src1->type);
     const uint32_t d_offset = get_misalign_bytes(ctx, dst) / ggml_type_size(dst->type);
@@ -8287,9 +8508,10 @@ template <> void init_pushconst_tensor_offsets(ggml_backend_vk_context * ctx, vk
     p.misalign_offsets = (a_offset << 16) | (b_offset << 8) | d_offset;
 
     GGML_UNUSED(src2);
+    GGML_UNUSED(src3);
 }
 
-template <> void init_pushconst_tensor_offsets(ggml_backend_vk_context * ctx, vk_op_upscale_push_constants &p, const ggml_tensor * src0, const ggml_tensor * src1, const ggml_tensor * src2, ggml_tensor * dst) {
+template <> void init_pushconst_tensor_offsets(ggml_backend_vk_context * ctx, vk_op_upscale_push_constants &p, const ggml_tensor * src0, const ggml_tensor * src1, const ggml_tensor * src2, const ggml_tensor * src3, ggml_tensor * dst) {
     const uint32_t a_offset = get_misalign_bytes(ctx, src0) / ggml_type_size(src0->type);
     const uint32_t d_offset = get_misalign_bytes(ctx, dst) / ggml_type_size(dst->type);
 
@@ -8298,10 +8520,11 @@ template <> void init_pushconst_tensor_offsets(ggml_backend_vk_context * ctx, vk
 
     GGML_UNUSED(src1);
     GGML_UNUSED(src2);
+    GGML_UNUSED(src3);
 }
 
 template<typename PC>
-static void ggml_vk_op_f32(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, const ggml_tensor * src1, const ggml_tensor * src2, ggml_tensor * dst, ggml_op op, PC&& pc, bool dryrun = false) {
+static void ggml_vk_op_f32(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, const ggml_tensor * src1, const ggml_tensor * src2, const ggml_tensor * src3, ggml_tensor * dst, ggml_op op, PC&& pc, bool dryrun = false) {
     VK_LOG_DEBUG("ggml_vk_op_f32((" << src0 << ", name=" << src0->name << ", type=" << src0->type << ", ne0=" << src0->ne[0] << ", ne1=" << src0->ne[1] << ", ne2=" << src0->ne[2] << ", ne3=" << src0->ne[3] << ", nb0=" << src0->nb[0] << ", nb1=" << src0->nb[1] << ", nb2=" << src0->nb[2] << ", nb3=" << src0->nb[3];
     if (src1 != nullptr) {
         std::cerr << "), (" << src1 << ", name=" << src1->name << ", type=" << src1->type << ", ne0=" << src1->ne[0] << ", ne1=" << src1->ne[1] << ", ne2=" << src1->ne[2] << ", ne3=" << src1->ne[3] << ", nb0=" << src1->nb[0] << ", nb1=" << src1->nb[1] << ", nb2=" << src1->nb[2] << ", nb3=" << src1->nb[3];
@@ -8309,6 +8532,9 @@ static void ggml_vk_op_f32(ggml_backend_vk_context * ctx, vk_context& subctx, co
     if (src2 != nullptr) {
         std::cerr << "), (" << src2 << ", name=" << src2->name << ", type=" << src2->type << ", ne0=" << src2->ne[0] << ", ne1=" << src2->ne[1] << ", ne2=" << src2->ne[2] << ", ne3=" << src2->ne[3] << ", nb0=" << src2->nb[0] << ", nb1=" << src2->nb[1] << ", nb2=" << src2->nb[2] << ", nb3=" << src2->nb[3];
     }
+    if (src3 != nullptr) {
+        std::cerr << "), (" << src3 << ", name=" << src3->name << ", type=" << src3->type << ", ne0=" << src3->ne[0] << ", ne1=" << src3->ne[1] << ", ne2=" << src3->ne[2] << ", ne3=" << src3->ne[3] << ", nb0=" << src3->nb[0] << ", nb1=" << src3->nb[1] << ", nb2=" << src3->nb[2] << ", nb3=" << src3->nb[3];
+    }
     std::cerr << "), (" << dst << ", name=" << dst->name << ", type=" << dst->type << ", ne0=" << dst->ne[0] << ", ne1=" << dst->ne[1] << ", ne2=" << dst->ne[2] << ", ne3=" << dst->ne[3] << ", nb0=" << dst->nb[0] << ", nb1=" << dst->nb[1] << ", nb2=" << dst->nb[2] << ", nb3=" << dst->nb[3];
     std::cerr << "), " << ggml_op_name(op) << ", " << (dryrun ? "dryrun" : "") << ")");
     GGML_ASSERT(op == GGML_OP_GET_ROWS || op == GGML_OP_CPY || (!ggml_is_quantized(src0->type) && (src1 == nullptr || !ggml_is_quantized(src1->type))));  // NOLINT
@@ -8335,6 +8561,13 @@ static void ggml_vk_op_f32(ggml_backend_vk_context * ctx, vk_context& subctx, co
     const uint64_t ne23 = use_src2 ? src2->ne[3] : 0;
     const uint64_t ne2 = ne20 * ne21;
 
+    const bool use_src3 = src3 != nullptr;
+    const uint64_t ne30 = use_src3 ? src3->ne[0] : 0;
+    const uint64_t ne31 = use_src3 ? src3->ne[1] : 0;
+    const uint64_t ne32 = use_src3 ? src3->ne[2] : 0;
+    const uint64_t ne33 = use_src3 ? src3->ne[3] : 0;
+    const uint64_t ne3 = ne30 * ne31;
+
     const uint64_t ned0 = dst->ne[0];
     const uint64_t ned1 = dst->ne[1];
     const uint64_t ned2 = dst->ne[2];
@@ -8365,6 +8598,7 @@ static void ggml_vk_op_f32(ggml_backend_vk_context * ctx, vk_context& subctx, co
     ggml_backend_vk_buffer_context * src0_buf_ctx = (ggml_backend_vk_buffer_context *)src0->buffer->context;
     ggml_backend_vk_buffer_context * src1_buf_ctx = use_src1 ? (ggml_backend_vk_buffer_context *)src1->buffer->context : nullptr;
     ggml_backend_vk_buffer_context * src2_buf_ctx = use_src2 ? (ggml_backend_vk_buffer_context *)src2->buffer->context : nullptr;
+    ggml_backend_vk_buffer_context * src3_buf_ctx = use_src3 ? (ggml_backend_vk_buffer_context *)src3->buffer->context : nullptr;
 
     vk_buffer d_X = nullptr;
     size_t x_buf_offset = 0;
@@ -8372,10 +8606,13 @@ static void ggml_vk_op_f32(ggml_backend_vk_context * ctx, vk_context& subctx, co
     size_t y_buf_offset = 0;
     vk_buffer d_Z = nullptr;
     size_t z_buf_offset = 0;
+    vk_buffer d_W = nullptr;
+    size_t w_buf_offset = 0;
 
     bool src0_uma = false;
     bool src1_uma = false;
     bool src2_uma = false;
+    bool src3_uma = false;
 
     if (ctx->device->uma) {
         ggml_vk_host_get(ctx->device, src0->data, d_X, x_buf_offset);
@@ -8388,6 +8625,10 @@ static void ggml_vk_op_f32(ggml_backend_vk_context * ctx, vk_context& subctx, co
             ggml_vk_host_get(ctx->device, src2->data, d_Z, z_buf_offset);
             src2_uma = d_Z != nullptr;
         }
+        if (use_src3) {
+            ggml_vk_host_get(ctx->device, src3->data, d_W, w_buf_offset);
+            src3_uma = d_W != nullptr;
+        }
     }
 
     vk_buffer d_D = dst_buf_ctx->dev_buffer;
@@ -8409,11 +8650,17 @@ static void ggml_vk_op_f32(ggml_backend_vk_context * ctx, vk_context& subctx, co
         z_buf_offset = vk_tensor_offset(src2) + src2->view_offs;
         GGML_ASSERT(d_Z != nullptr);
     }
+    if (use_src3 && !src3_uma) {
+        d_W = src3_buf_ctx->dev_buffer;
+        w_buf_offset = vk_tensor_offset(src3) + src3->view_offs;
+        GGML_ASSERT(d_W != nullptr);
+    }
     // Compute misalignment offset for descriptors and store it in in push constants, then align the descriptor offsets.
-    init_pushconst_tensor_offsets(ctx, pc, src0, src1, src2, dst);
+    init_pushconst_tensor_offsets(ctx, pc, src0, src1, src2, src3, dst);
     x_buf_offset &= ~(ctx->device->properties.limits.minStorageBufferOffsetAlignment - 1);
     y_buf_offset &= ~(ctx->device->properties.limits.minStorageBufferOffsetAlignment - 1);
     z_buf_offset &= ~(ctx->device->properties.limits.minStorageBufferOffsetAlignment - 1);
+    w_buf_offset &= ~(ctx->device->properties.limits.minStorageBufferOffsetAlignment - 1);
     d_buf_offset &= ~(ctx->device->properties.limits.minStorageBufferOffsetAlignment - 1);
 
     std::array<uint32_t, 3> elements;
@@ -8470,6 +8717,7 @@ static void ggml_vk_op_f32(ggml_backend_vk_context * ctx, vk_context& subctx, co
         break;
     case GGML_OP_ARGSORT:
         elements = { (uint32_t)ne00, (uint32_t)ggml_nrows(src0), 1 };
+        elements[1] = std::min(elements[1], ctx->device->properties.limits.maxComputeWorkGroupCount[1]);
         break;
     case GGML_OP_IM2COL:
         {
@@ -8614,12 +8862,13 @@ static void ggml_vk_op_f32(ggml_backend_vk_context * ctx, vk_context& subctx, co
         break;
     }
 
-    uint64_t x_sz, y_sz, z_sz, d_sz;
+    uint64_t x_sz, y_sz, z_sz, w_sz, d_sz;
 
     if (op_supports_incontiguous) {
         x_sz = ggml_nbytes(src0) + get_misalign_bytes(ctx, src0);
         y_sz = use_src1 ? ggml_nbytes(src1) + get_misalign_bytes(ctx, src1) : 0;
         z_sz = use_src2 ? ggml_nbytes(src2) + get_misalign_bytes(ctx, src2) : 0;
+        w_sz = use_src3 ? ggml_nbytes(src3) + get_misalign_bytes(ctx, src3) : 0;
         d_sz = ggml_nbytes(dst) + get_misalign_bytes(ctx, dst);
 
         if (x_buf_offset + x_sz >= d_X->size) {
@@ -8631,6 +8880,9 @@ static void ggml_vk_op_f32(ggml_backend_vk_context * ctx, vk_context& subctx, co
         if (use_src2 && z_buf_offset + z_sz >= d_Z->size) {
             z_sz = ggml_vk_get_max_buffer_range(ctx, d_Z, z_buf_offset);
         }
+        if (use_src3 && w_buf_offset + w_sz >= d_W->size) {
+            w_sz = ggml_vk_get_max_buffer_range(ctx, d_W, w_buf_offset);
+        }
         if (d_buf_offset + d_sz >= d_D->size) {
             d_sz = ggml_vk_get_max_buffer_range(ctx, d_D, d_buf_offset);
         }
@@ -8638,6 +8890,7 @@ static void ggml_vk_op_f32(ggml_backend_vk_context * ctx, vk_context& subctx, co
         x_sz = ggml_type_size(src0->type)/ggml_blck_size(src0->type) * ne0 * ne02 * ne03;
         y_sz = use_src1 ? ggml_type_size(src1->type) * ne1 * ne12 * ne13 : 0;
         z_sz = use_src2 ? ggml_type_size(src2->type) * ne2 * ne22 * ne23 : 0;
+        w_sz = use_src3 ? ggml_type_size(src3->type) * ne3 * ne32 * ne33 : 0;
         d_sz = ggml_type_size(dst->type) * ned * ned2 * ned3;
     }
 
@@ -8679,14 +8932,19 @@ static void ggml_vk_op_f32(ggml_backend_vk_context * ctx, vk_context& subctx, co
         ggml_vk_dispatch_pipeline(ctx, subctx, pipeline, { vk_subbuffer{ d_X, x_buf_offset, x_sz }, subbuf_y, subbuf_z, vk_subbuffer{ d_D, d_buf_offset, d_sz } }, pc, elements);
     } else if (op == GGML_OP_ROPE || op == GGML_OP_ROPE_BACK) {
         // Empty src2 is possible in rope, but the shader needs a buffer
-        vk_subbuffer subbuf_z;
+        vk_subbuffer subbuf_z, subbuf_w;
         if (use_src2) {
             subbuf_z = { d_Z, z_buf_offset, z_sz };
         } else {
             subbuf_z = { d_X, 0, x_sz };
         }
+        if (use_src3) {
+            subbuf_w = { d_W, w_buf_offset, w_sz };
+        } else {
+            subbuf_w = { d_X, 0, x_sz };
+        }
 
-        ggml_vk_dispatch_pipeline(ctx, subctx, pipeline, { vk_subbuffer{ d_X, x_buf_offset, x_sz }, vk_subbuffer{ d_Y, y_buf_offset, y_sz }, subbuf_z, vk_subbuffer{ d_D, d_buf_offset, d_sz } }, pc, elements);
+        ggml_vk_dispatch_pipeline(ctx, subctx, pipeline, { vk_subbuffer{ d_X, x_buf_offset, x_sz }, vk_subbuffer{ d_Y, y_buf_offset, y_sz }, subbuf_z, vk_subbuffer{ d_D, d_buf_offset, d_sz }, subbuf_w }, pc, elements);
     } else if (op == GGML_OP_IM2COL || op == GGML_OP_IM2COL_3D) {
         if (ctx->device->shader_int64 && ctx->device->buffer_device_address) {
             // buffer device address path doesn't use dst buffer
@@ -8702,6 +8960,8 @@ static void ggml_vk_op_f32(ggml_backend_vk_context * ctx, vk_context& subctx, co
     } else if (op == GGML_OP_OPT_STEP_SGD) {
         // OPT_STEP_SGD works on src0, it does not need dst
         ggml_vk_dispatch_pipeline(ctx, subctx, pipeline, { vk_subbuffer{ d_X, x_buf_offset, x_sz }, vk_subbuffer{ d_Y, y_buf_offset, y_sz }, vk_subbuffer{ d_Z, z_buf_offset, z_sz } }, pc, elements);
+    } else if (use_src3) {
+        ggml_vk_dispatch_pipeline(ctx, subctx, pipeline, { vk_subbuffer{ d_X, x_buf_offset, x_sz }, vk_subbuffer{ d_Y, y_buf_offset, y_sz }, vk_subbuffer{ d_Z, z_buf_offset, z_sz }, vk_subbuffer{ d_W, w_buf_offset, w_sz }, vk_subbuffer{ d_D, d_buf_offset, d_sz } }, pc, elements);
     } else if (use_src2) {
         ggml_vk_dispatch_pipeline(ctx, subctx, pipeline, { vk_subbuffer{ d_X, x_buf_offset, x_sz }, vk_subbuffer{ d_Y, y_buf_offset, y_sz }, vk_subbuffer{ d_Z, z_buf_offset, z_sz }, vk_subbuffer{ d_D, d_buf_offset, d_sz } }, pc, elements);
     } else if (use_src1) {
@@ -8716,7 +8976,7 @@ static void ggml_vk_get_rows(ggml_backend_vk_context * ctx, vk_context& subctx,
     const uint32_t src1_type_size = ggml_type_size(src1->type);
     const uint32_t dst_type_size = ggml_type_size(dst->type);
 
-    ggml_vk_op_f32<vk_op_binary_push_constants>(ctx, subctx, src0, src1, nullptr, dst, GGML_OP_GET_ROWS, {
+    ggml_vk_op_f32<vk_op_binary_push_constants>(ctx, subctx, src0, src1, nullptr, nullptr, dst, GGML_OP_GET_ROWS, {
         (uint32_t)ggml_nelements(src0),
         (uint32_t)src0->ne[0], (uint32_t)src0->ne[1], (uint32_t)src0->ne[2],(uint32_t)src0->ne[3], (uint32_t)src0->nb[0] / src0_type_size, (uint32_t)src0->nb[1] / src0_type_size, (uint32_t)src0->nb[2] / src0_type_size, (uint32_t)src0->nb[3] / src0_type_size,
         (uint32_t)src1->ne[0], (uint32_t)src1->ne[1], (uint32_t)src1->ne[2],(uint32_t)src1->ne[3], (uint32_t)src1->nb[0] / src1_type_size, (uint32_t)src1->nb[1] / src1_type_size, (uint32_t)src1->nb[2] / src1_type_size, (uint32_t)src1->nb[3] / src1_type_size,
@@ -8736,7 +8996,7 @@ static void ggml_vk_acc(ggml_backend_vk_context * ctx, vk_context& subctx, const
     // int nb3 = dst->op_params[2] / 4; // 4 bytes of float32 - unused
     int offset = dst->op_params[3] / 4; // offset in bytes
 
-    ggml_vk_op_f32<vk_op_binary_push_constants>(ctx, subctx, src0, src1, nullptr, dst, GGML_OP_ACC, {
+    ggml_vk_op_f32<vk_op_binary_push_constants>(ctx, subctx, src0, src1, nullptr, nullptr, dst, GGML_OP_ACC, {
         (uint32_t)ggml_nelements(src0),
         (uint32_t)src0->ne[0], (uint32_t)src0->ne[1], (uint32_t)src0->ne[2],(uint32_t)src0->ne[3], (uint32_t)src0->nb[0] / src0_type_size, (uint32_t)nb1, (uint32_t)nb2, (uint32_t)src0->nb[3] / src0_type_size,
         (uint32_t)src1->ne[0], (uint32_t)src1->ne[1], (uint32_t)src1->ne[2],(uint32_t)src1->ne[3], (uint32_t)src1->nb[0] / src1_type_size, (uint32_t)src1->nb[1] / src1_type_size, (uint32_t)src1->nb[2] / src1_type_size, (uint32_t)src1->nb[3] / src1_type_size,
@@ -8861,7 +9121,7 @@ static void ggml_vk_add(ggml_backend_vk_context * ctx, vk_context& subctx, const
     const uint32_t src1_type_size = ggml_type_size(src1->type);
     const uint32_t dst_type_size = ggml_type_size(dst->type);
 
-    ggml_vk_op_f32<vk_op_binary_push_constants>(ctx, subctx, src0, src1, nullptr, dst, GGML_OP_ADD, {
+    ggml_vk_op_f32<vk_op_binary_push_constants>(ctx, subctx, src0, src1, nullptr, nullptr, dst, GGML_OP_ADD, {
         (uint32_t)ggml_nelements(src0),
         (uint32_t)src0->ne[0], (uint32_t)src0->ne[1], (uint32_t)src0->ne[2],(uint32_t)src0->ne[3], (uint32_t)src0->nb[0] / src0_type_size, (uint32_t)src0->nb[1] / src0_type_size, (uint32_t)src0->nb[2] / src0_type_size, (uint32_t)src0->nb[3] / src0_type_size,
         (uint32_t)src1->ne[0], (uint32_t)src1->ne[1], (uint32_t)src1->ne[2],(uint32_t)src1->ne[3], (uint32_t)src1->nb[0] / src1_type_size, (uint32_t)src1->nb[1] / src1_type_size, (uint32_t)src1->nb[2] / src1_type_size, (uint32_t)src1->nb[3] / src1_type_size,
@@ -8876,7 +9136,7 @@ static void ggml_vk_sub(ggml_backend_vk_context * ctx, vk_context& subctx, const
     const uint32_t src1_type_size = ggml_type_size(src1->type);
     const uint32_t dst_type_size = ggml_type_size(dst->type);
 
-    ggml_vk_op_f32<vk_op_binary_push_constants>(ctx, subctx, src0, src1, nullptr, dst, GGML_OP_SUB, {
+    ggml_vk_op_f32<vk_op_binary_push_constants>(ctx, subctx, src0, src1, nullptr, nullptr, dst, GGML_OP_SUB, {
         (uint32_t)ggml_nelements(src0),
         (uint32_t)src0->ne[0], (uint32_t)src0->ne[1], (uint32_t)src0->ne[2],(uint32_t)src0->ne[3], (uint32_t)src0->nb[0] / src0_type_size, (uint32_t)src0->nb[1] / src0_type_size, (uint32_t)src0->nb[2] / src0_type_size, (uint32_t)src0->nb[3] / src0_type_size,
         (uint32_t)src1->ne[0], (uint32_t)src1->ne[1], (uint32_t)src1->ne[2],(uint32_t)src1->ne[3], (uint32_t)src1->nb[0] / src1_type_size, (uint32_t)src1->nb[1] / src1_type_size, (uint32_t)src1->nb[2] / src1_type_size, (uint32_t)src1->nb[3] / src1_type_size,
@@ -8891,7 +9151,7 @@ static void ggml_vk_mul(ggml_backend_vk_context * ctx, vk_context& subctx, const
     const uint32_t src1_type_size = ggml_type_size(src1->type);
     const uint32_t dst_type_size = ggml_type_size(dst->type);
 
-    ggml_vk_op_f32<vk_op_binary_push_constants>(ctx, subctx, src0, src1, nullptr, dst, GGML_OP_MUL, {
+    ggml_vk_op_f32<vk_op_binary_push_constants>(ctx, subctx, src0, src1, nullptr, nullptr, dst, GGML_OP_MUL, {
         (uint32_t)ggml_nelements(src0),
         (uint32_t)src0->ne[0], (uint32_t)src0->ne[1], (uint32_t)src0->ne[2],(uint32_t)src0->ne[3], (uint32_t)src0->nb[0] / src0_type_size, (uint32_t)src0->nb[1] / src0_type_size, (uint32_t)src0->nb[2] / src0_type_size, (uint32_t)src0->nb[3] / src0_type_size,
         (uint32_t)src1->ne[0], (uint32_t)src1->ne[1], (uint32_t)src1->ne[2],(uint32_t)src1->ne[3], (uint32_t)src1->nb[0] / src1_type_size, (uint32_t)src1->nb[1] / src1_type_size, (uint32_t)src1->nb[2] / src1_type_size, (uint32_t)src1->nb[3] / src1_type_size,
@@ -8906,7 +9166,7 @@ static void ggml_vk_div(ggml_backend_vk_context * ctx, vk_context& subctx, const
     const uint32_t src1_type_size = ggml_type_size(src1->type);
     const uint32_t dst_type_size = ggml_type_size(dst->type);
 
-    ggml_vk_op_f32<vk_op_binary_push_constants>(ctx, subctx, src0, src1, nullptr, dst, GGML_OP_DIV, {
+    ggml_vk_op_f32<vk_op_binary_push_constants>(ctx, subctx, src0, src1, nullptr, nullptr, dst, GGML_OP_DIV, {
         (uint32_t)ggml_nelements(src0),
         (uint32_t)src0->ne[0], (uint32_t)src0->ne[1], (uint32_t)src0->ne[2],(uint32_t)src0->ne[3], (uint32_t)src0->nb[0] / src0_type_size, (uint32_t)src0->nb[1] / src0_type_size, (uint32_t)src0->nb[2] / src0_type_size, (uint32_t)src0->nb[3] / src0_type_size,
         (uint32_t)src1->ne[0], (uint32_t)src1->ne[1], (uint32_t)src1->ne[2],(uint32_t)src1->ne[3], (uint32_t)src1->nb[0] / src1_type_size, (uint32_t)src1->nb[1] / src1_type_size, (uint32_t)src1->nb[2] / src1_type_size, (uint32_t)src1->nb[3] / src1_type_size,
@@ -8921,7 +9181,7 @@ static void ggml_vk_add_id(ggml_backend_vk_context * ctx, vk_context& subctx, co
     const uint32_t src1_type_size = ggml_type_size(src1->type);
     const uint32_t src2_type_size = ggml_type_size(src2->type);
 
-    ggml_vk_op_f32<vk_op_add_id_push_constants>(ctx, subctx, src0, src1, src2, dst, GGML_OP_ADD_ID, {
+    ggml_vk_op_f32<vk_op_add_id_push_constants>(ctx, subctx, src0, src1, src2, nullptr, dst, GGML_OP_ADD_ID, {
         (uint32_t)dst->ne[0],
         (uint32_t)dst->ne[1],
         (uint32_t)src0->nb[1] / src0_type_size,
@@ -9154,7 +9414,7 @@ static void ggml_vk_ssm_conv(ggml_backend_vk_context * ctx, vk_context& subctx,
     const ggml_tensor * src0 = dst->src[0];
     const ggml_tensor * src1 = dst->src[1];
 
-    ggml_vk_op_f32<vk_op_ssm_conv_push_constants>(ctx, subctx, src0, src1, nullptr, dst, GGML_OP_SSM_CONV, {
+    ggml_vk_op_f32<vk_op_ssm_conv_push_constants>(ctx, subctx, src0, src1, nullptr, nullptr, dst, GGML_OP_SSM_CONV, {
         (uint32_t)src0->nb[1], (uint32_t)src0->nb[2],
         (uint32_t)src1->nb[1],
         (uint32_t)dst->nb[0], (uint32_t)dst->nb[1], (uint32_t)dst->nb[2],
@@ -9272,7 +9532,7 @@ static void ggml_vk_opt_step_adamw(ggml_backend_vk_context * ctx, vk_context& su
 static void ggml_vk_opt_step_sgd(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, const ggml_tensor * src1, const ggml_tensor * src2, ggml_tensor * dst, bool dryrun = false) {
     const size_t n = ggml_nelements(dst->src[0]);
 
-    ggml_vk_op_f32<vk_op_push_constants>(ctx, subctx, src0, src1, src2, dst, GGML_OP_OPT_STEP_SGD, { (uint32_t)n, 0, 0.0f, 0.0f }, dryrun);
+    ggml_vk_op_f32<vk_op_push_constants>(ctx, subctx, src0, src1, src2, nullptr, dst, GGML_OP_OPT_STEP_SGD, { (uint32_t)n, 0, 0.0f, 0.0f }, dryrun);
 }
 
 static void ggml_vk_concat(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst, bool dryrun = false) {
@@ -9282,7 +9542,7 @@ static void ggml_vk_concat(ggml_backend_vk_context * ctx, vk_context& subctx, co
     const uint32_t src1_type_size = ggml_type_size(src1->type);
     const uint32_t dst_type_size = ggml_type_size(dst->type);
 
-    ggml_vk_op_f32<vk_op_binary_push_constants>(ctx, subctx, src0, src1, nullptr, dst, GGML_OP_CONCAT, {
+    ggml_vk_op_f32<vk_op_binary_push_constants>(ctx, subctx, src0, src1, nullptr, nullptr, dst, GGML_OP_CONCAT, {
         (uint32_t)ggml_nelements(dst),
         (uint32_t)src0->ne[0], (uint32_t)src0->ne[1], (uint32_t)src0->ne[2],(uint32_t)src0->ne[3], (uint32_t)src0->nb[0] / src0_type_size, (uint32_t)src0->nb[1] / src0_type_size, (uint32_t)src0->nb[2] / src0_type_size, (uint32_t)src0->nb[3] / src0_type_size,
         (uint32_t)src1->ne[0], (uint32_t)src1->ne[1], (uint32_t)src1->ne[2],(uint32_t)src1->ne[3], (uint32_t)src1->nb[0] / src1_type_size, (uint32_t)src1->nb[1] / src1_type_size, (uint32_t)src1->nb[2] / src1_type_size, (uint32_t)src1->nb[3] / src1_type_size,
@@ -9306,7 +9566,7 @@ static void ggml_vk_upscale(ggml_backend_vk_context * ctx, vk_context& subctx, c
         sf1 = (float)(dst->ne[1] - 1) / (src0->ne[1] - 1);
     }
 
-    ggml_vk_op_f32<vk_op_upscale_push_constants>(ctx, subctx, src0, nullptr, nullptr, dst, GGML_OP_UPSCALE, {
+    ggml_vk_op_f32<vk_op_upscale_push_constants>(ctx, subctx, src0, nullptr, nullptr, nullptr, dst, GGML_OP_UPSCALE, {
         (uint32_t)ggml_nelements(dst), 0, 0,
         (uint32_t)src0->ne[0], (uint32_t)src0->ne[1],
         (uint32_t)src0->nb[0] / src0_type_size, (uint32_t)src0->nb[1] / src0_type_size, (uint32_t)src0->nb[2] / src0_type_size, (uint32_t)src0->nb[3] / src0_type_size,
@@ -9320,23 +9580,23 @@ static void ggml_vk_scale(ggml_backend_vk_context * ctx, vk_context& subctx, con
     p.param1 = ggml_get_op_params_f32(dst, 0);
     p.param2 = ggml_get_op_params_f32(dst, 1);
 
-    ggml_vk_op_f32(ctx, subctx, src0, nullptr, nullptr, dst, GGML_OP_SCALE, std::move(p), dryrun);
+    ggml_vk_op_f32(ctx, subctx, src0, nullptr, nullptr, nullptr, dst, GGML_OP_SCALE, std::move(p), dryrun);
 }
 
 static void ggml_vk_sqr(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, ggml_tensor * dst, bool dryrun = false) {
-    ggml_vk_op_f32(ctx, subctx, src0, nullptr, nullptr, dst, GGML_OP_SQR, vk_op_unary_push_constants_init(src0, dst), dryrun);
+    ggml_vk_op_f32(ctx, subctx, src0, nullptr, nullptr, nullptr, dst, GGML_OP_SQR, vk_op_unary_push_constants_init(src0, dst), dryrun);
 }
 
 static void ggml_vk_sqrt(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, ggml_tensor * dst, bool dryrun = false) {
-    ggml_vk_op_f32(ctx, subctx, src0, nullptr, nullptr, dst, GGML_OP_SQRT, vk_op_unary_push_constants_init(src0, dst), dryrun);
+    ggml_vk_op_f32(ctx, subctx, src0, nullptr, nullptr, nullptr, dst, GGML_OP_SQRT, vk_op_unary_push_constants_init(src0, dst), dryrun);
 }
 
 static void ggml_vk_sin(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, ggml_tensor * dst, bool dryrun = false) {
-    ggml_vk_op_f32(ctx, subctx, src0, nullptr, nullptr, dst, GGML_OP_SIN, vk_op_unary_push_constants_init(src0, dst), dryrun);
+    ggml_vk_op_f32(ctx, subctx, src0, nullptr, nullptr, nullptr, dst, GGML_OP_SIN, vk_op_unary_push_constants_init(src0, dst), dryrun);
 }
 
 static void ggml_vk_cos(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, ggml_tensor * dst, bool dryrun = false) {
-    ggml_vk_op_f32(ctx, subctx, src0, nullptr, nullptr, dst, GGML_OP_COS, vk_op_unary_push_constants_init(src0, dst), dryrun);
+    ggml_vk_op_f32(ctx, subctx, src0, nullptr, nullptr, nullptr, dst, GGML_OP_COS, vk_op_unary_push_constants_init(src0, dst), dryrun);
 }
 
 static void ggml_vk_clamp(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, ggml_tensor * dst, bool dryrun = false) {
@@ -9344,12 +9604,12 @@ static void ggml_vk_clamp(ggml_backend_vk_context * ctx, vk_context& subctx, con
     p.param1 = ggml_get_op_params_f32(dst, 0);
     p.param2 = ggml_get_op_params_f32(dst, 1);
 
-    ggml_vk_op_f32(ctx, subctx, src0, nullptr, nullptr, dst, GGML_OP_CLAMP, std::move(p), dryrun);
+    ggml_vk_op_f32(ctx, subctx, src0, nullptr, nullptr, nullptr, dst, GGML_OP_CLAMP, std::move(p), dryrun);
 }
 
 static void ggml_vk_pad(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, ggml_tensor * dst, bool dryrun = false) {
     vk_op_pad_push_constants p = vk_op_pad_push_constants_init(src0, dst);
-    ggml_vk_op_f32(ctx, subctx, src0, nullptr, nullptr, dst, GGML_OP_PAD, std::move(p), dryrun);
+    ggml_vk_op_f32(ctx, subctx, src0, nullptr, nullptr, nullptr, dst, GGML_OP_PAD, std::move(p), dryrun);
 }
 
 static void ggml_vk_roll(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, ggml_tensor * dst, bool dryrun = false) {
@@ -9364,17 +9624,17 @@ static void ggml_vk_roll(ggml_backend_vk_context * ctx, vk_context& subctx, cons
     memcpy(&p.param1, &s01_packed, sizeof(float));
     memcpy(&p.param2, &s23_packed, sizeof(float));
 
-    ggml_vk_op_f32(ctx, subctx, src0, nullptr, nullptr, dst, GGML_OP_ROLL, std::move(p), dryrun);
+    ggml_vk_op_f32(ctx, subctx, src0, nullptr, nullptr, nullptr, dst, GGML_OP_ROLL, std::move(p), dryrun);
 }
 
 static void ggml_vk_repeat(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, ggml_tensor * dst, bool dryrun = false) {
     vk_op_unary_push_constants p = vk_op_unary_push_constants_init(src0, dst, ggml_nelements(dst));
-    ggml_vk_op_f32(ctx, subctx, src0, nullptr, nullptr, dst, GGML_OP_REPEAT, std::move(p), dryrun);
+    ggml_vk_op_f32(ctx, subctx, src0, nullptr, nullptr, nullptr, dst, GGML_OP_REPEAT, std::move(p), dryrun);
 }
 
 static void ggml_vk_repeat_back(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, ggml_tensor * dst, bool dryrun = false) {
     vk_op_unary_push_constants p = vk_op_unary_push_constants_init(src0, dst, ggml_nelements(dst));
-    ggml_vk_op_f32(ctx, subctx, src0, nullptr, nullptr, dst, GGML_OP_REPEAT_BACK, std::move(p), dryrun);
+    ggml_vk_op_f32(ctx, subctx, src0, nullptr, nullptr, nullptr, dst, GGML_OP_REPEAT_BACK, std::move(p), dryrun);
 }
 
 static void ggml_vk_cpy(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, ggml_tensor * dst, bool dryrun = false) {
@@ -9390,7 +9650,7 @@ static void ggml_vk_cpy(ggml_backend_vk_context * ctx, vk_context& subctx, const
     }
 
     vk_op_unary_push_constants p = vk_op_unary_push_constants_init(src0, dst, ne);
-    ggml_vk_op_f32(ctx, subctx, src0, nullptr, nullptr, dst, GGML_OP_CPY, std::move(p), dryrun);
+    ggml_vk_op_f32(ctx, subctx, src0, nullptr, nullptr, nullptr, dst, GGML_OP_CPY, std::move(p), dryrun);
 }
 
 static void ggml_vk_set_rows(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst, bool dryrun = false) {
@@ -9405,7 +9665,7 @@ static void ggml_vk_set_rows(ggml_backend_vk_context * ctx, vk_context& subctx,
         return;
     }
 
-    ggml_vk_op_f32<vk_op_binary_push_constants>(ctx, subctx, src0, src1, nullptr, dst, GGML_OP_SET_ROWS, {
+    ggml_vk_op_f32<vk_op_binary_push_constants>(ctx, subctx, src0, src1, nullptr, nullptr, dst, GGML_OP_SET_ROWS, {
         (uint32_t)ggml_nelements(src0),
         (uint32_t)src0->ne[0], (uint32_t)src0->ne[1], (uint32_t)src0->ne[2],(uint32_t)src0->ne[3], (uint32_t)src0->nb[0] / src0_type_size, (uint32_t)src0->nb[1] / src0_type_size, (uint32_t)src0->nb[2] / src0_type_size, (uint32_t)src0->nb[3] / src0_type_size,
         (uint32_t)src1->ne[0], (uint32_t)src1->ne[1], (uint32_t)src1->ne[2],(uint32_t)src1->ne[3], (uint32_t)src1->nb[0] / src1_type_size, (uint32_t)src1->nb[1] / src1_type_size, (uint32_t)src1->nb[2] / src1_type_size, (uint32_t)src1->nb[3] / src1_type_size,
@@ -9416,13 +9676,13 @@ static void ggml_vk_set_rows(ggml_backend_vk_context * ctx, vk_context& subctx,
 }
 
 static void ggml_vk_silu_back(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst, bool dryrun = false) {
-    ggml_vk_op_f32<vk_op_push_constants>(ctx, subctx, src0, src1, nullptr, dst, GGML_OP_SILU_BACK, { (uint32_t)ggml_nelements(src0), 0, 0.0f, 0.0f }, dryrun);
+    ggml_vk_op_f32<vk_op_push_constants>(ctx, subctx, src0, src1, nullptr, nullptr, dst, GGML_OP_SILU_BACK, { (uint32_t)ggml_nelements(src0), 0, 0.0f, 0.0f }, dryrun);
 }
 
 static void ggml_vk_norm(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, ggml_tensor * dst, bool dryrun = false) {
     float * op_params = (float *)dst->op_params;
 
-    ggml_vk_op_f32<vk_op_push_constants>(ctx, subctx, src0, nullptr, nullptr, dst, GGML_OP_NORM, { (uint32_t)src0->ne[0], (uint32_t)src0->ne[1], op_params[0], 0.0f }, dryrun);
+    ggml_vk_op_f32<vk_op_push_constants>(ctx, subctx, src0, nullptr, nullptr, nullptr, dst, GGML_OP_NORM, { (uint32_t)src0->ne[0], (uint32_t)src0->ne[1], op_params[0], 0.0f }, dryrun);
 }
 
 static void ggml_vk_group_norm(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, ggml_tensor * dst, bool dryrun = false) {
@@ -9433,7 +9693,7 @@ static void ggml_vk_group_norm(ggml_backend_vk_context * ctx, vk_context& subctx
     const float eps = float_op_params[1];
     const uint32_t group_size = src0->ne[0] * src0->ne[1] * ((src0->ne[2] + num_groups - 1) / num_groups);
 
-    ggml_vk_op_f32<vk_op_push_constants>(ctx, subctx, src0, nullptr, nullptr, dst, GGML_OP_GROUP_NORM, { group_size, 0, eps, 0.0f }, dryrun);
+    ggml_vk_op_f32<vk_op_push_constants>(ctx, subctx, src0, nullptr, nullptr, nullptr, dst, GGML_OP_GROUP_NORM, { group_size, 0, eps, 0.0f }, dryrun);
 }
 
 static uint32_t ggml_vk_rms_num_partials(ggml_backend_vk_context * ctx, const ggml_tensor *node) {
@@ -9456,7 +9716,7 @@ static void ggml_vk_rms_norm(ggml_backend_vk_context * ctx, vk_context& subctx,
 
     uint32_t param3 = ctx->do_add_rms_partials ? ggml_vk_rms_num_partials(ctx, dst) : 0;
 
-    ggml_vk_op_f32<vk_op_binary_push_constants>(ctx, subctx, src0, src1, nullptr, dst, GGML_OP_RMS_NORM, {
+    ggml_vk_op_f32<vk_op_binary_push_constants>(ctx, subctx, src0, src1, nullptr, nullptr, dst, GGML_OP_RMS_NORM, {
         (uint32_t)ggml_nelements(src0),
         (uint32_t)src0->ne[0], (uint32_t)src0->ne[1], (uint32_t)src0->ne[2],(uint32_t)src0->ne[3], (uint32_t)src0->nb[0] / src0_type_size, (uint32_t)src0->nb[1] / src0_type_size, (uint32_t)src0->nb[2] / src0_type_size, (uint32_t)src0->nb[3] / src0_type_size,
         (uint32_t)src1->ne[0], (uint32_t)src1->ne[1], (uint32_t)src1->ne[2],(uint32_t)src1->ne[3], (uint32_t)src1->nb[0] / src1_type_size, (uint32_t)src1->nb[1] / src1_type_size, (uint32_t)src1->nb[2] / src1_type_size, (uint32_t)src1->nb[3] / src1_type_size,
@@ -9473,16 +9733,16 @@ static void ggml_vk_rms_norm(ggml_backend_vk_context * ctx, vk_context& subctx,
 
 static void ggml_vk_rms_norm_back(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst, bool dryrun = false) {
     float * op_params = (float *)dst->op_params;
-    ggml_vk_op_f32<vk_op_push_constants>(ctx, subctx, src0, src1, nullptr, dst, GGML_OP_RMS_NORM_BACK, { (uint32_t)src0->ne[0], (uint32_t)src0->ne[1], op_params[0], 0.0f }, dryrun);
+    ggml_vk_op_f32<vk_op_push_constants>(ctx, subctx, src0, src1, nullptr, nullptr, dst, GGML_OP_RMS_NORM_BACK, { (uint32_t)src0->ne[0], (uint32_t)src0->ne[1], op_params[0], 0.0f }, dryrun);
 }
 
 static void ggml_vk_l2_norm(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, ggml_tensor * dst, bool dryrun = false) {
     float * op_params = (float *)dst->op_params;
-    ggml_vk_op_f32<vk_op_push_constants>(ctx, subctx, src0, nullptr, nullptr, dst, GGML_OP_L2_NORM, { (uint32_t)src0->ne[0], (uint32_t)src0->ne[1], op_params[0], 0.0f }, dryrun);
+    ggml_vk_op_f32<vk_op_push_constants>(ctx, subctx, src0, nullptr, nullptr, nullptr, dst, GGML_OP_L2_NORM, { (uint32_t)src0->ne[0], (uint32_t)src0->ne[1], op_params[0], 0.0f }, dryrun);
 }
 
 static void ggml_vk_unary(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, ggml_tensor * dst, bool dryrun = false) {
-    ggml_vk_op_f32<vk_op_push_constants>(ctx, subctx, src0, nullptr, nullptr, dst, GGML_OP_UNARY, { (uint32_t)ggml_nelements(src0), 0, 0.0f, 0.0f }, dryrun);
+    ggml_vk_op_f32<vk_op_push_constants>(ctx, subctx, src0, nullptr, nullptr, nullptr, dst, GGML_OP_UNARY, { (uint32_t)ggml_nelements(src0), 0, 0.0f, 0.0f }, dryrun);
 }
 
 static void ggml_vk_glu(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst, bool dryrun = false) {
@@ -9505,7 +9765,7 @@ static void ggml_vk_glu(ggml_backend_vk_context * ctx, vk_context& subctx, const
 
     const uint32_t mode = split ? 2 : (swapped ? 1 : 0);
 
-    ggml_vk_op_f32<vk_op_glu_push_constants>(ctx, subctx, src0, src1, nullptr, dst, GGML_OP_GLU,
+    ggml_vk_op_f32<vk_op_glu_push_constants>(ctx, subctx, src0, src1, nullptr, nullptr, dst, GGML_OP_GLU,
         {
             (uint32_t)ggml_nelements(dst),
             (uint32_t)src0->ne[0],
@@ -9518,7 +9778,7 @@ static void ggml_vk_glu(ggml_backend_vk_context * ctx, vk_context& subctx, const
 
 static void ggml_vk_diag_mask_inf(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, ggml_tensor * dst, bool dryrun = false) {
     int32_t * op_params = (int32_t *)dst->op_params;
-    ggml_vk_op_f32<vk_op_diag_mask_push_constants>(ctx, subctx, src0, nullptr, nullptr, dst, GGML_OP_DIAG_MASK_INF, { (uint32_t)src0->ne[0], (uint32_t)src0->ne[1], op_params[0] }, dryrun);
+    ggml_vk_op_f32<vk_op_diag_mask_push_constants>(ctx, subctx, src0, nullptr, nullptr, nullptr, dst, GGML_OP_DIAG_MASK_INF, { (uint32_t)src0->ne[0], (uint32_t)src0->ne[1], op_params[0] }, dryrun);
 }
 
 static void ggml_vk_soft_max(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, const ggml_tensor * src1, const ggml_tensor * src2, ggml_tensor * dst, bool dryrun = false) {
@@ -9543,7 +9803,7 @@ static void ggml_vk_soft_max(ggml_backend_vk_context * ctx, vk_context& subctx,
     const float m0 = powf(2.0f, -(max_bias       ) / n_head_log2);
     const float m1 = powf(2.0f, -(max_bias / 2.0f) / n_head_log2);
 
-    ggml_vk_op_f32<vk_op_soft_max_push_constants>(ctx, subctx, src0, src1, src2, dst, GGML_OP_SOFT_MAX, {
+    ggml_vk_op_f32<vk_op_soft_max_push_constants>(ctx, subctx, src0, src1, src2, nullptr, dst, GGML_OP_SOFT_MAX, {
         ncols,
         src1 != nullptr ? nrows_y : (uint32_t)0,
         (uint32_t)src0->ne[0], (uint32_t)src0->ne[1], (uint32_t)src0->ne[2],
@@ -9559,15 +9819,17 @@ static void ggml_vk_soft_max(ggml_backend_vk_context * ctx, vk_context& subctx,
 
 static void ggml_vk_soft_max_back(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst, bool dryrun = false) {
     float * op_params = (float *)dst->op_params;
-    ggml_vk_op_f32<vk_op_push_constants>(ctx, subctx, src0, src1, nullptr, dst, GGML_OP_SOFT_MAX_BACK, { (uint32_t)src0->ne[0], (uint32_t)ggml_nrows(src0), op_params[0], op_params[1] }, dryrun);
+    ggml_vk_op_f32<vk_op_push_constants>(ctx, subctx, src0, src1, nullptr, nullptr, dst, GGML_OP_SOFT_MAX_BACK, { (uint32_t)src0->ne[0], (uint32_t)ggml_nrows(src0), op_params[0], op_params[1] }, dryrun);
 }
 
 static void ggml_vk_topk_moe(ggml_backend_vk_context * ctx, vk_context& subctx, ggml_cgraph * cgraph, int node_idx, bool dryrun = false) {
 
-    bool with_norm = ctx->num_additional_fused_ops == topk_moe_norm.size() - 1;
+    topk_moe_mode mode = ggml_vk_num_additional_ops_to_topk_moe_mode(ctx->num_additional_fused_ops);
     ggml_tensor * logits = cgraph->nodes[node_idx + 0]->src[0];
-    ggml_tensor * weights = with_norm ? cgraph->nodes[node_idx + 8] : cgraph->nodes[node_idx + 4];
-    ggml_tensor * ids = cgraph->nodes[node_idx + 3];
+    ggml_tensor * weights = (mode == TOPK_MOE_EARLY_SOFTMAX_NORM) ? cgraph->nodes[node_idx + 9] :
+                            (mode == TOPK_MOE_EARLY_SOFTMAX)      ? cgraph->nodes[node_idx + 4] :
+                                                                    cgraph->nodes[node_idx + 5];
+    ggml_tensor * ids = (mode == TOPK_MOE_LATE_SOFTMAX) ? cgraph->nodes[node_idx + 1] : cgraph->nodes[node_idx + 3];
 
     GGML_ASSERT(logits->type == GGML_TYPE_F32);
     GGML_ASSERT(weights->type == GGML_TYPE_F32);
@@ -9626,9 +9888,14 @@ static void ggml_vk_topk_moe(ggml_backend_vk_context * ctx, vk_context& subctx,
         GGML_ASSERT(d_ids != nullptr);
     }
 
-    vk_op_topk_moe_push_constants pc;
+    vk_op_topk_moe_push_constants pc {};
     pc.n_rows = n_rows;
     pc.n_expert_used = n_expert_used;
+    if (mode == TOPK_MOE_EARLY_SOFTMAX_NORM) {
+        ggml_tensor * clamp = cgraph->nodes[node_idx + 7];
+        pc.clamp_min = ggml_get_op_params_f32(clamp, 0);
+        pc.clamp_max = ggml_get_op_params_f32(clamp, 1);
+    }
 
     GGML_ASSERT(n_expert_used <= n_experts);
 
@@ -9643,7 +9910,12 @@ static void ggml_vk_topk_moe(ggml_backend_vk_context * ctx, vk_context& subctx,
         }, pc, elements);
 }
 
-static void ggml_vk_rope(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, const ggml_tensor * src1, const ggml_tensor * src2, ggml_tensor * dst, bool backprop, bool dryrun = false) {
+static void ggml_vk_rope(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_cgraph * cgraph, int node_idx, bool backprop, bool dryrun = false) {
+    ggml_tensor * dst = cgraph->nodes[node_idx];
+    const ggml_tensor * src0 = dst->src[0];
+    const ggml_tensor * src1 = dst->src[1];
+    const ggml_tensor * src2 = dst->src[2];
+    const ggml_tensor * src3 = nullptr;
     const int n_dims        = ((int32_t *) dst->op_params)[1];
     const int mode          = ((int32_t *) dst->op_params)[2];
     // const int n_ctx         = ((int32_t *) dst->op_params)[3];
@@ -9667,11 +9939,20 @@ static void ggml_vk_rope(ggml_backend_vk_context * ctx, vk_context& subctx, cons
     uint32_t s1 = src0->nb[1] / ggml_type_size(src0->type);
     uint32_t s2 = src0->nb[2] / ggml_type_size(src0->type);
 
-    ggml_vk_op_f32<vk_op_rope_push_constants>(ctx, subctx, src0, src1, src2, dst, GGML_OP_ROPE, {
+    uint32_t set_rows_stride = 0;
+    // Fused rope + view + set_rows passes the set_rows destination stride in set_rows_stride
+    // and overrides the dst and sets src3=row_indices
+    if (ctx->num_additional_fused_ops > 0) {
+        set_rows_stride = cgraph->nodes[node_idx + 2]->nb[1] / ggml_type_size(cgraph->nodes[node_idx + 2]->type);
+        src3 = cgraph->nodes[node_idx + 2]->src[1];
+        dst = cgraph->nodes[node_idx + 2];
+    }
+
+    ggml_vk_op_f32<vk_op_rope_push_constants>(ctx, subctx, src0, src1, src2, src3, dst, GGML_OP_ROPE, {
         (uint32_t)src0->ne[0], (uint32_t)n_dims, freq_scale, (uint32_t)src0->ne[1],
         freq_base, ext_factor, attn_factor, {corr_dims[0], corr_dims[1]}, theta_scale,
         src2 != nullptr, (uint32_t)src0->ne[2], s1, s2,
-        { sections[0], sections[1], sections[2], sections[3] }, backprop
+        { sections[0], sections[1], sections[2], sections[3] }, backprop, set_rows_stride,
     }, dryrun);
 }
 
@@ -9679,35 +9960,37 @@ static void ggml_vk_argsort(ggml_backend_vk_context * ctx, vk_context& subctx, c
     int32_t * op_params = (int32_t *)dst->op_params;
 
     uint32_t ncols = src0->ne[0];
+    uint32_t nrows = ggml_nrows(src0);
 
-    ggml_vk_op_f32<vk_op_argsort_push_constants>(ctx, subctx, src0, nullptr, nullptr, dst, GGML_OP_ARGSORT, {
+    ggml_vk_op_f32<vk_op_argsort_push_constants>(ctx, subctx, src0, nullptr, nullptr, nullptr, dst, GGML_OP_ARGSORT, {
         ncols,
+        nrows,
         op_params[0],
     }, dryrun);
 }
 
 static void ggml_vk_sum(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, ggml_tensor * dst, bool dryrun = false) {
     vk_op_sum_rows_push_constants p = vk_op_sum_rows_push_constants_init(src0, dst, ggml_nelements(src0));
-    ggml_vk_op_f32(ctx, subctx, src0, nullptr, nullptr, dst, GGML_OP_SUM, p, dryrun);
+    ggml_vk_op_f32(ctx, subctx, src0, nullptr, nullptr, nullptr, dst, GGML_OP_SUM, p, dryrun);
 }
 
 static void ggml_vk_sum_rows(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, ggml_tensor * dst, bool dryrun = false) {
     vk_op_sum_rows_push_constants p = vk_op_sum_rows_push_constants_init(src0, dst, src0->ne[0]);
-    ggml_vk_op_f32(ctx, subctx, src0, nullptr, nullptr, dst, GGML_OP_SUM_ROWS, p, dryrun);
+    ggml_vk_op_f32(ctx, subctx, src0, nullptr, nullptr, nullptr, dst, GGML_OP_SUM_ROWS, p, dryrun);
 }
 
 static void ggml_vk_mean(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, ggml_tensor * dst, bool dryrun = false) {
     vk_op_sum_rows_push_constants p = vk_op_sum_rows_push_constants_init(src0, dst, src0->ne[0]);
     p.weight = 1.0f / (float)src0->ne[0];
-    ggml_vk_op_f32(ctx, subctx, src0, nullptr, nullptr, dst, GGML_OP_MEAN, p, dryrun);
+    ggml_vk_op_f32(ctx, subctx, src0, nullptr, nullptr, nullptr, dst, GGML_OP_MEAN, p, dryrun);
 }
 
 static void ggml_vk_argmax(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, ggml_tensor * dst, bool dryrun = false) {
-    ggml_vk_op_f32<vk_op_push_constants>(ctx, subctx, src0, nullptr, nullptr, dst, GGML_OP_ARGMAX, { (uint32_t)src0->ne[0], (uint32_t)src0->ne[1], 0.0f, 0.0f }, dryrun);
+    ggml_vk_op_f32<vk_op_push_constants>(ctx, subctx, src0, nullptr, nullptr, nullptr, dst, GGML_OP_ARGMAX, { (uint32_t)src0->ne[0], (uint32_t)src0->ne[1], 0.0f, 0.0f }, dryrun);
 }
 
 static void ggml_vk_count_equal(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst, bool dryrun = false) {
-    ggml_vk_op_f32<vk_op_push_constants>(ctx, subctx, src0, src1, nullptr, dst, GGML_OP_COUNT_EQUAL, { (uint32_t)ggml_nelements(src0), 0, 0.0f, 0.0f }, dryrun);
+    ggml_vk_op_f32<vk_op_push_constants>(ctx, subctx, src0, src1, nullptr, nullptr, dst, GGML_OP_COUNT_EQUAL, { (uint32_t)ggml_nelements(src0), 0, 0.0f, 0.0f }, dryrun);
 }
 
 static void ggml_vk_im2col(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst, bool dryrun = false) {
@@ -9740,7 +10023,7 @@ static void ggml_vk_im2col(ggml_backend_vk_context * ctx, vk_context& subctx, co
 
     const vk::DeviceAddress dst_addr = d_buf->bda_addr + vk_tensor_offset(dst) + dst->view_offs;
 
-    ggml_vk_op_f32<vk_op_im2col_push_constants>(ctx, subctx, src0, src1, nullptr, dst, GGML_OP_IM2COL, {
+    ggml_vk_op_f32<vk_op_im2col_push_constants>(ctx, subctx, src0, src1, nullptr, nullptr, dst, GGML_OP_IM2COL, {
         dst_addr,
         batch_offset, offset_delta,
         IC, IW, IH, OW, OH, KW, KH,
@@ -9813,7 +10096,7 @@ static void ggml_vk_im2col_3d(ggml_backend_vk_context * ctx, vk_context& subctx,
     pc.OH_OW_IC_KD_KH_KW = OH*OW*IC*KD*KH*KW;
     pc.OW_IC_KD_KH_KW = OW*IC*KD*KH*KW;
 
-    ggml_vk_op_f32<vk_op_im2col_3d_push_constants>(ctx, subctx, src0, src1, nullptr, dst, GGML_OP_IM2COL_3D, std::move(pc), dryrun);
+    ggml_vk_op_f32<vk_op_im2col_3d_push_constants>(ctx, subctx, src0, src1, nullptr, nullptr, dst, GGML_OP_IM2COL_3D, std::move(pc), dryrun);
 }
 
 static void ggml_vk_timestep_embedding(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, ggml_tensor * dst, bool dryrun = false) {
@@ -9821,7 +10104,7 @@ static void ggml_vk_timestep_embedding(ggml_backend_vk_context * ctx, vk_context
     const uint32_t max_period = dst->op_params[1];
     const uint32_t nb1 = dst->nb[1] / ggml_type_size(dst->type);
 
-    ggml_vk_op_f32<vk_op_timestep_embedding_push_constants>(ctx, subctx, src0, nullptr, nullptr, dst, GGML_OP_TIMESTEP_EMBEDDING, {
+    ggml_vk_op_f32<vk_op_timestep_embedding_push_constants>(ctx, subctx, src0, nullptr, nullptr, nullptr, dst, GGML_OP_TIMESTEP_EMBEDDING, {
         nb1, dim, max_period,
     }, dryrun);
 }
@@ -9854,7 +10137,7 @@ static void ggml_vk_conv_transpose_1d(ggml_backend_vk_context * ctx, vk_context&
     p.nb1 = static_cast<uint32_t>(nb1 / nb0);
     p.s0 = static_cast<uint32_t>(s0);
 
-    ggml_vk_op_f32(ctx, subctx, src0, src1, nullptr, dst, GGML_OP_CONV_TRANSPOSE_1D, std::move(p), dryrun);
+    ggml_vk_op_f32(ctx, subctx, src0, src1, nullptr, nullptr, dst, GGML_OP_CONV_TRANSPOSE_1D, std::move(p), dryrun);
 }
 
 static void ggml_vk_pool_2d(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, ggml_tensor * dst, bool dryrun = false) {
@@ -9877,7 +10160,7 @@ static void ggml_vk_pool_2d(ggml_backend_vk_context * ctx, vk_context& subctx, c
 
     const uint32_t parallel_elements = N * OC * OH * OW;
 
-    ggml_vk_op_f32<vk_op_pool2d_push_constants>(ctx, subctx, src0, nullptr, nullptr, dst, GGML_OP_POOL_2D, {
+    ggml_vk_op_f32<vk_op_pool2d_push_constants>(ctx, subctx, src0, nullptr, nullptr, nullptr, dst, GGML_OP_POOL_2D, {
         IW, IH, OW, OH, OC,
         parallel_elements,
         op,
@@ -9931,7 +10214,7 @@ static void ggml_vk_conv_2d(ggml_backend_vk_context * ctx, vk_context & subctx,
     GGML_ASSERT(ne03 == ne2);
     GGML_ASSERT(ne02 == ne12);
 
-    ggml_vk_op_f32(ctx, subctx, src0, src1, nullptr, dst, GGML_OP_CONV_2D, std::move(p), dryrun);
+    ggml_vk_op_f32(ctx, subctx, src0, src1, nullptr, nullptr, dst, GGML_OP_CONV_2D, std::move(p), dryrun);
 }
 
 static void ggml_vk_conv_transpose_2d(ggml_backend_vk_context * ctx, vk_context & subctx, const ggml_tensor * src0,
@@ -9980,7 +10263,7 @@ static void ggml_vk_conv_transpose_2d(ggml_backend_vk_context * ctx, vk_context
     GGML_ASSERT(ne02 == ne2);
     GGML_ASSERT(ne03 == ne12);
 
-    ggml_vk_op_f32(ctx, subctx, src0, src1, nullptr, dst, GGML_OP_CONV_TRANSPOSE_2D, std::move(p), dryrun);
+    ggml_vk_op_f32(ctx, subctx, src0, src1, nullptr, nullptr, dst, GGML_OP_CONV_TRANSPOSE_2D, std::move(p), dryrun);
 }
 
 static void ggml_vk_conv_2d_dw(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst, bool dryrun = false) {
@@ -10004,12 +10287,12 @@ static void ggml_vk_conv_2d_dw(ggml_backend_vk_context * ctx, vk_context& subctx
     GGML_ASSERT(src0->ne[3] == p.channels);
     GGML_ASSERT(src1->ne[3] == p.batches);
 
-    ggml_vk_op_f32(ctx, subctx, src0, src1, nullptr, dst, GGML_OP_CONV_2D_DW, std::move(p), dryrun);
+    ggml_vk_op_f32(ctx, subctx, src0, src1, nullptr, nullptr, dst, GGML_OP_CONV_2D_DW, std::move(p), dryrun);
 }
 
 static void ggml_vk_leaky_relu(ggml_backend_vk_context * ctx, vk_context& subctx, const ggml_tensor * src0, ggml_tensor * dst, bool dryrun = false) {
     const float * op_params = (const float *)dst->op_params;
-    ggml_vk_op_f32<vk_op_push_constants>(ctx, subctx, src0, nullptr, nullptr, dst, GGML_OP_LEAKY_RELU, { (uint32_t)ggml_nelements(src0), 0, op_params[0], 0.0f }, dryrun);
+    ggml_vk_op_f32<vk_op_push_constants>(ctx, subctx, src0, nullptr, nullptr, nullptr, dst, GGML_OP_LEAKY_RELU, { (uint32_t)ggml_nelements(src0), 0, op_params[0], 0.0f }, dryrun);
 }
 
 #ifdef GGML_VULKAN_RUN_TESTS
@@ -11135,7 +11418,6 @@ static bool ggml_vk_build_graph(ggml_backend_vk_context * ctx, ggml_cgraph * cgr
         case GGML_OP_DIAG_MASK_INF:
         case GGML_OP_SOFT_MAX:
         case GGML_OP_SOFT_MAX_BACK:
-        case GGML_OP_ROPE:
         case GGML_OP_ROPE_BACK:
         case GGML_OP_ARGSORT:
         case GGML_OP_SUM:
@@ -11209,9 +11491,12 @@ static bool ggml_vk_build_graph(ggml_backend_vk_context * ctx, ggml_cgraph * cgr
         // nodes require synchronization.
         for (int32_t i = 0; i < ctx->num_additional_fused_ops + 1 && !need_sync; ++i) {
             const ggml_tensor *cur_node = cgraph->nodes[node_idx + i];
-            if (overlaps_unsynced(cur_node, ctx->unsynced_nodes_read) || overlaps_unsynced(cur_node, ctx->unsynced_nodes_written)) {
-                need_sync = true;
-                break;
+            // If the node actually writes to memory, then check if it needs to sync
+            if (ctx->fused_ops_write_mask & (1 << i)) {
+                if (overlaps_unsynced(cur_node, ctx->unsynced_nodes_read) || overlaps_unsynced(cur_node, ctx->unsynced_nodes_written)) {
+                    need_sync = true;
+                    break;
+                }
             }
             for (uint32_t j = 0; j < GGML_MAX_SRC; ++j) {
                 if (!cur_node->src[j]) {
@@ -11223,7 +11508,13 @@ static bool ggml_vk_build_graph(ggml_backend_vk_context * ctx, ggml_cgraph * cgr
                 }
             }
         }
+
+#define ENABLE_SYNC_LOGGING 0
+
         if (need_sync) {
+#if ENABLE_SYNC_LOGGING
+            std::cerr <<  "sync" << std::endl;
+#endif
             ctx->unsynced_nodes_written.clear();
             ctx->unsynced_nodes_read.clear();
             ggml_vk_sync_buffers(ctx, compute_ctx);
@@ -11232,7 +11523,9 @@ static bool ggml_vk_build_graph(ggml_backend_vk_context * ctx, ggml_cgraph * cgr
         for (int32_t i = 0; i < ctx->num_additional_fused_ops + 1; ++i) {
             const ggml_tensor *cur_node = cgraph->nodes[node_idx + i];
             // Multiple outputs could be written, e.g. in topk_moe. Add them all to the list.
-            ctx->unsynced_nodes_written.push_back(cur_node);
+            if (ctx->fused_ops_write_mask & (1 << i)) {
+                ctx->unsynced_nodes_written.push_back(cur_node);
+            }
             for (uint32_t j = 0; j < GGML_MAX_SRC; ++j) {
                 if (!cur_node->src[j]) {
                     continue;
@@ -11241,6 +11534,18 @@ static bool ggml_vk_build_graph(ggml_backend_vk_context * ctx, ggml_cgraph * cgr
             }
         }
     }
+#if ENABLE_SYNC_LOGGING
+    if (!dryrun) {
+        for (int i = 0; i < ctx->num_additional_fused_ops + 1; ++i) {
+            auto *n = cgraph->nodes[node_idx + i];
+            std::cerr << node_idx + i << " " << ggml_op_name(n->op) << " " <<  n->name;
+            if (n->op == GGML_OP_GLU) {
+                std::cerr << " " << ggml_glu_op_name(ggml_get_glu_op(n)) << " " << (n->src[1] ? "split" : "single") << " ";
+            }
+            std::cerr << std::endl;
+        }
+    }
+#endif
 
     switch (node->op) {
     case GGML_OP_REPEAT:
@@ -11411,15 +11716,19 @@ static bool ggml_vk_build_graph(ggml_backend_vk_context * ctx, ggml_cgraph * cgr
 
         break;
     case GGML_OP_ROPE:
-        ggml_vk_rope(ctx, compute_ctx, src0, src1, src2, node, false, dryrun);
+        ggml_vk_rope(ctx, compute_ctx, cgraph, node_idx, false, dryrun);
 
         break;
     case GGML_OP_ROPE_BACK:
-        ggml_vk_rope(ctx, compute_ctx, src0, src1, src2, node, true, dryrun);
+        ggml_vk_rope(ctx, compute_ctx, cgraph, node_idx, true, dryrun);
 
         break;
     case GGML_OP_ARGSORT:
-        ggml_vk_argsort(ctx, compute_ctx, src0, node, dryrun);
+        if (ctx->num_additional_fused_ops) {
+            ggml_vk_topk_moe(ctx, compute_ctx, cgraph, node_idx, dryrun);
+        } else {
+            ggml_vk_argsort(ctx, compute_ctx, src0, node, dryrun);
+        }
 
         break;
     case GGML_OP_SUM:
@@ -12217,31 +12526,28 @@ static bool ggml_vk_can_fuse(const struct ggml_cgraph * cgraph, int node_idx, st
 }
 
 static bool ggml_vk_can_fuse_topk_moe(ggml_backend_vk_context * ctx, const struct ggml_cgraph * cgraph,
-                                      int node_idx, bool with_norm) {
+                                      int node_idx, topk_moe_mode mode) {
 
-    if (with_norm) {
-        if (node_idx + (int)topk_moe_norm.size() > cgraph->n_nodes) {
-            return false;
-        }
-        for (size_t i = 0; i < topk_moe_norm.size(); ++i) {
-            if (cgraph->nodes[node_idx + i]->op != topk_moe_norm[i]) {
-                return false;
-            }
-        }
-    } else {
-        if (node_idx + (int)topk_moe.size() > cgraph->n_nodes) {
-            return false;
-        }
-        for (size_t i = 0; i < topk_moe.size(); ++i) {
-            if (cgraph->nodes[node_idx + i]->op != topk_moe[i]) {
-                return false;
-            }
-        }
+    const ggml_tensor * softmax;
+    const ggml_tensor * weights;
+
+    switch (mode) {
+    case TOPK_MOE_EARLY_SOFTMAX_NORM:
+        softmax = cgraph->nodes[node_idx + 0];
+        weights = cgraph->nodes[node_idx + 9];
+        break;
+    case TOPK_MOE_EARLY_SOFTMAX:
+        softmax = cgraph->nodes[node_idx + 0];
+        weights = cgraph->nodes[node_idx + 4];
+        break;
+    case TOPK_MOE_LATE_SOFTMAX:
+        softmax = cgraph->nodes[node_idx + 4];
+        weights = cgraph->nodes[node_idx + 5];
+        break;
+    default:
+        return false;
     }
 
-    const ggml_tensor * softmax =  cgraph->nodes[node_idx + 0];
-    const ggml_tensor * weights = with_norm ? cgraph->nodes[node_idx + 8] : cgraph->nodes[node_idx + 4];
-
     const float * op_params = (const float *)softmax->op_params;
 
     float scale = op_params[0];
@@ -12266,60 +12572,6 @@ static bool ggml_vk_can_fuse_topk_moe(ggml_backend_vk_context * ctx, const struc
         return false;
     }
 
-    // Check that the nodes don't have any unexpected uses
-    const ggml_tensor * reshape1 =  cgraph->nodes[node_idx + 1];
-    const ggml_tensor * argsort =   cgraph->nodes[node_idx + 2];
-    const ggml_tensor * view =      cgraph->nodes[node_idx + 3];
-    const ggml_tensor * get_rows =  cgraph->nodes[node_idx + 4];
-    const ggml_tensor * reshape5 =  with_norm ? cgraph->nodes[node_idx + 5] : nullptr;
-    const ggml_tensor * sum_rows =  with_norm ? cgraph->nodes[node_idx + 6] : nullptr;
-    const ggml_tensor * div =       with_norm ? cgraph->nodes[node_idx + 7] : nullptr;
-    const ggml_tensor * reshape8 =  with_norm ? cgraph->nodes[node_idx + 8] : nullptr;
-
-    // softmax is used by reshape and argsort
-    if (ggml_node_get_use_count(cgraph, node_idx) != 2 ||
-        reshape1->src[0] != softmax ||
-        argsort->src[0] != softmax) {
-        return false;
-    }
-    // reshape is used by get_rows
-    if (ggml_node_get_use_count(cgraph, node_idx + 1) != 1 ||
-        get_rows->src[0] != reshape1) {
-        return false;
-    }
-    // argsort is used by view
-    if (ggml_node_get_use_count(cgraph, node_idx + 2) != 1 ||
-        view->src[0] != argsort) {
-        return false;
-    }
-    // view is written (via argsort), we can skip checking it
-
-    if (with_norm) {
-        // get_rows is used by reshape
-        if (ggml_node_get_use_count(cgraph, node_idx + 4) != 1 ||
-            reshape5->src[0] != get_rows) {
-            return false;
-        }
-
-        // reshape is used by sum_rows and div
-        if (ggml_node_get_use_count(cgraph, node_idx + 5) != 2 ||
-            sum_rows->src[0] != reshape5 ||
-            div->src[0] != reshape5) {
-            return false;
-        }
-
-        // sum_rows is used by div
-        if (ggml_node_get_use_count(cgraph, node_idx + 6) != 1 ||
-            div->src[1] != sum_rows) {
-            return false;
-        }
-
-        // div/reshape are written
-        if (reshape8->src[0] != div) {
-            return false;
-        }
-    }
-
     if (!ctx->device->subgroup_arithmetic ||
         !ctx->device->subgroup_shuffle ||
         !ctx->device->subgroup_require_full_support ||
@@ -12330,6 +12582,41 @@ static bool ggml_vk_can_fuse_topk_moe(ggml_backend_vk_context * ctx, const struc
     return true;
 }
 
+static bool ggml_vk_can_fuse_rope_set_rows(ggml_backend_vk_context * ctx, const struct ggml_cgraph * cgraph,
+                                           int node_idx) {
+    GGML_UNUSED(ctx);
+    const ggml_tensor *rope = cgraph->nodes[node_idx + 0];
+    const ggml_tensor *view = cgraph->nodes[node_idx + 1];
+    const ggml_tensor *set_rows = cgraph->nodes[node_idx + 2];
+
+    // ne3 not tested
+    if (rope->src[0]->ne[3] != 1) {
+        return false;
+    }
+
+    if (set_rows->type != GGML_TYPE_F32 && set_rows->type != GGML_TYPE_F16) {
+        return false;
+    }
+
+    if (set_rows->src[1]->type != GGML_TYPE_I64) {
+        return false;
+    }
+
+    // The view should flatten two dims of rope into one dim
+    if (!ggml_is_contiguous(view) ||
+        view->ne[0] != rope->ne[0] * rope->ne[1]) {
+        return false;
+    }
+
+    // Only norm/neox shaders have the fusion code
+    const int mode = ((const int32_t *) rope->op_params)[2];
+    if (mode != GGML_ROPE_TYPE_NORMAL && mode != GGML_ROPE_TYPE_NEOX) {
+        return false;
+    }
+
+    return true;
+}
+
 static uint32_t ggml_vk_fuse_multi_add(ggml_backend_vk_context * ctx, const struct ggml_cgraph * cgraph, int node_idx) {
 
     const ggml_tensor *first_node = cgraph->nodes[node_idx];
@@ -12405,10 +12692,22 @@ static ggml_status ggml_backend_vk_graph_compute(ggml_backend_t backend, ggml_cg
                 ctx->num_additional_fused_ops = num_adds - 1;
             } else if (ggml_vk_can_fuse(cgraph, i, { GGML_OP_RMS_NORM, GGML_OP_MUL })) {
                 ctx->num_additional_fused_ops = 1;
-            } else if (ggml_vk_can_fuse_topk_moe(ctx, cgraph, i, true)) {
-                ctx->num_additional_fused_ops = topk_moe_norm.size() - 1;
-            } else if (ggml_vk_can_fuse_topk_moe(ctx, cgraph, i, false)) {
-                ctx->num_additional_fused_ops = topk_moe.size() - 1;
+            } else if (ggml_can_fuse_subgraph(cgraph, i, { GGML_OP_ROPE, GGML_OP_VIEW, GGML_OP_SET_ROWS }, { i + 2 }) &&
+                       ggml_check_edges(cgraph, i, rope_view_set_rows_edges) &&
+                       ggml_vk_can_fuse_rope_set_rows(ctx, cgraph, i)) {
+                ctx->num_additional_fused_ops = 2;
+            } else if (ggml_can_fuse_subgraph(cgraph, i, topk_moe_early_softmax_norm, { i + 3, i + 9 }) &&
+                       ggml_check_edges(cgraph, i, topk_moe_early_softmax_norm_edges) &&
+                       ggml_vk_can_fuse_topk_moe(ctx, cgraph, i, TOPK_MOE_EARLY_SOFTMAX_NORM)) {
+                ctx->num_additional_fused_ops = topk_moe_early_softmax_norm.size() - 1;
+            } else if (ggml_can_fuse_subgraph(cgraph, i, topk_moe_early_softmax, { i + 3, i + 4 }) &&
+                       ggml_check_edges(cgraph, i, topk_moe_early_softmax_edges) &&
+                       ggml_vk_can_fuse_topk_moe(ctx, cgraph, i, TOPK_MOE_EARLY_SOFTMAX)) {
+                ctx->num_additional_fused_ops = topk_moe_early_softmax.size() - 1;
+            } else if (ggml_can_fuse_subgraph(cgraph, i, topk_moe_late_softmax, { i + 1, i + 5 }) &&
+                       ggml_check_edges(cgraph, i, topk_moe_late_softmax_edges) &&
+                       ggml_vk_can_fuse_topk_moe(ctx, cgraph, i, TOPK_MOE_LATE_SOFTMAX)) {
+                ctx->num_additional_fused_ops = topk_moe_late_softmax.size() - 1;
             }
         }
         ggml_vk_build_graph(ctx, cgraph, i, nullptr, 0, true, false, false, false);
@@ -12506,12 +12805,31 @@ static ggml_status ggml_backend_vk_graph_compute(ggml_backend_t backend, ggml_cg
                 ctx->num_additional_fused_ops = num_adds - 1;
             } else if (ggml_vk_can_fuse(cgraph, i, { GGML_OP_RMS_NORM, GGML_OP_MUL })) {
                 ctx->num_additional_fused_ops = 1;
-            } else if (ggml_vk_can_fuse_topk_moe(ctx, cgraph, i, true)) {
-                ctx->num_additional_fused_ops = topk_moe_norm.size() - 1;
-            } else if (ggml_vk_can_fuse_topk_moe(ctx, cgraph, i, false)) {
-                ctx->num_additional_fused_ops = topk_moe.size() - 1;
+            } else if (ggml_can_fuse_subgraph(cgraph, i, { GGML_OP_ROPE, GGML_OP_VIEW, GGML_OP_SET_ROWS }, { i + 2 }) &&
+                       ggml_check_edges(cgraph, i, rope_view_set_rows_edges) &&
+                       ggml_vk_can_fuse_rope_set_rows(ctx, cgraph, i)) {
+                ctx->num_additional_fused_ops = 2;
+            } else if (ggml_can_fuse_subgraph(cgraph, i, topk_moe_early_softmax_norm, { i + 3, i + 9 }) &&
+                       ggml_check_edges(cgraph, i, topk_moe_early_softmax_norm_edges) &&
+                       ggml_vk_can_fuse_topk_moe(ctx, cgraph, i, TOPK_MOE_EARLY_SOFTMAX_NORM)) {
+                ctx->num_additional_fused_ops = topk_moe_early_softmax_norm.size() - 1;
+                // view of argsort writes to memory
+                ctx->fused_ops_write_mask |= 1 << 3;
+            } else if (ggml_can_fuse_subgraph(cgraph, i, topk_moe_early_softmax, { i + 3, i + 4 }) &&
+                       ggml_check_edges(cgraph, i, topk_moe_early_softmax_edges) &&
+                       ggml_vk_can_fuse_topk_moe(ctx, cgraph, i, TOPK_MOE_EARLY_SOFTMAX)) {
+                ctx->num_additional_fused_ops = topk_moe_early_softmax.size() - 1;
+                // view of argsort writes to memory
+                ctx->fused_ops_write_mask |= 1 << 3;
+            } else if (ggml_can_fuse_subgraph(cgraph, i, topk_moe_late_softmax, { i + 1, i + 5 }) &&
+                       ggml_check_edges(cgraph, i, topk_moe_late_softmax_edges) &&
+                       ggml_vk_can_fuse_topk_moe(ctx, cgraph, i, TOPK_MOE_LATE_SOFTMAX)) {
+                ctx->num_additional_fused_ops = topk_moe_late_softmax.size() - 1;
+                // view of argsort writes to memory
+                ctx->fused_ops_write_mask |= 1 << 1;
             }
         }
+        ctx->fused_ops_write_mask |= 1 << ctx->num_additional_fused_ops;
 
         // Signal the almost_ready fence when the graph is mostly complete (< 20% remaining)
         bool almost_ready = (cgraph->n_nodes - i) < cgraph->n_nodes / 5;
@@ -12557,6 +12875,7 @@ static ggml_status ggml_backend_vk_graph_compute(ggml_backend_t backend, ggml_cg
         }
         i += ctx->num_additional_fused_ops;
         ctx->num_additional_fused_ops = 0;
+        ctx->fused_ops_write_mask = 0;
     }
 
     if (vk_perf_logger_enabled) {
@@ -12642,25 +12961,44 @@ static void ggml_vk_graph_optimize(ggml_backend_t backend, struct ggml_cgraph *
     while (first_unused < graph->n_nodes) {
         std::vector<int> current_set;
 
-        // Avoid reordering topk_moe_norm
-        if (first_unused + (int)topk_moe_norm.size() <= graph->n_nodes) {
-            bool is_topk_moe_norm = true;
-            for (size_t j = 0; j < topk_moe_norm.size(); ++j) {
-                if (graph->nodes[first_unused + j]->op != topk_moe_norm[j] || used[first_unused + j]) {
-                    is_topk_moe_norm = false;
+        // Check for fusion patterns and avoid reordering them
+        auto const &match_pattern = [&](const std::initializer_list<ggml_op> &pattern, int start) -> bool {
+            if (start + (int)pattern.size() <= graph->n_nodes) {
+                bool is_pattern = true;
+                for (size_t j = 0; j < pattern.size(); ++j) {
+                    if (graph->nodes[start + j]->op != pattern.begin()[j] || used[start + j]) {
+                        is_pattern = false;
+                    }
                 }
+                return is_pattern;
             }
-            if (is_topk_moe_norm) {
-                for (size_t j = 0; j < topk_moe_norm.size(); ++j) {
+            return false;
+        };
+
+        auto const &keep_pattern = [&](const std::initializer_list<ggml_op> &pattern) -> bool {
+            if (match_pattern(pattern, first_unused)) {
+                for (size_t j = 0; j < pattern.size(); ++j) {
                     new_order.push_back(graph->nodes[first_unused + j]);
                     used[first_unused + j] = true;
                 }
                 while (first_unused < graph->n_nodes && used[first_unused]) {
                     first_unused++;
                 }
-                continue;
+                return true;
             }
+            return false;
+        };
+
+        if (keep_pattern(topk_moe_early_softmax_norm)) {
+            continue;
         }
+        if (keep_pattern(topk_moe_early_softmax)) {
+            continue;
+        }
+        if (keep_pattern(topk_moe_late_softmax)) {
+            continue;
+        }
+
         // First, grab the next unused node.
         current_set.push_back(first_unused);
 
@@ -12678,6 +13016,12 @@ static void ggml_vk_graph_optimize(ggml_backend_t backend, struct ggml_cgraph *
             if (is_empty(graph->nodes[j])) {
                 continue;
             }
+            // Don't pull forward nodes from fusion patterns
+            if (match_pattern(topk_moe_early_softmax_norm, j) ||
+                match_pattern(topk_moe_early_softmax, j) ||
+                match_pattern(topk_moe_late_softmax, j)) {
+                continue;
+            }
             bool ok = true;
             for (int c = first_unused; c < j; ++c) {
                 if (!used[c] &&
@@ -12689,6 +13033,32 @@ static void ggml_vk_graph_optimize(ggml_backend_t backend, struct ggml_cgraph *
             }
             if (ok) {
                 current_set.push_back(j);
+                // Look for ROPE + VIEW + SET_ROWS and make them consecutive
+                if (graph->nodes[j]->op == GGML_OP_ROPE) {
+                    int view_idx = -1;
+                    int set_rows_idx = -1;
+                    for (int k = j+1; k < std::min(j + 10, graph->n_nodes); ++k) {
+                        if (view_idx == -1 &&
+                            graph->nodes[k]->op == GGML_OP_VIEW &&
+                            graph->nodes[k]->src[0] == graph->nodes[j]) {
+                            view_idx = k;
+                            continue;
+                        }
+                        if (view_idx != -1 &&
+                            set_rows_idx == -1 &&
+                            graph->nodes[k]->op == GGML_OP_SET_ROWS &&
+                            graph->nodes[k]->src[0] == graph->nodes[view_idx]) {
+                            set_rows_idx = k;
+                            break;
+                        }
+                    }
+                    if (set_rows_idx != -1) {
+                        current_set.push_back(view_idx);
+                        current_set.push_back(set_rows_idx);
+                        used[view_idx] = true;
+                        used[set_rows_idx] = true;
+                    }
+                }
             }
         }
         // Second pass grabs view nodes.
diff --git a/ml/backend/ggml/ggml/src/ggml-vulkan/vulkan-shaders/argsort.comp b/ml/backend/ggml/ggml/src/ggml-vulkan/vulkan-shaders/argsort.comp
index c81b8445..c4e68bc0 100644
--- a/ml/backend/ggml/ggml/src/ggml-vulkan/vulkan-shaders/argsort.comp
+++ b/ml/backend/ggml/ggml/src/ggml-vulkan/vulkan-shaders/argsort.comp
@@ -14,6 +14,7 @@ layout (binding = 1)          buffer D {int data_d[];};
 
 layout (push_constant) uniform parameter {
     uint ncols;
+    uint nrows;
     uint order;
 } p;
 
@@ -26,10 +27,9 @@ void swap(uint idx0, uint idx1) {
     dst_row[idx1] = tmp;
 }
 
-void argsort(bool needs_bounds_check) {
+void argsort(bool needs_bounds_check, const uint row) {
     // bitonic sort
     const int col = int(gl_LocalInvocationID.x);
-    const uint row = gl_WorkGroupID.y;
 
     const uint row_offset = row * p.ncols;
 
@@ -72,8 +72,16 @@ void argsort(bool needs_bounds_check) {
 
 void main() {
     if (p.ncols == BLOCK_SIZE) {
-        argsort(false);
+        uint row = gl_WorkGroupID.y;
+        while (row < p.nrows) {
+            argsort(false, row);
+            row += gl_WorkGroupSize.y * gl_NumWorkGroups.y;
+        }
     } else {
-        argsort(true);
+        uint row = gl_WorkGroupID.y;
+        while (row < p.nrows) {
+            argsort(true, row);
+            row += gl_WorkGroupSize.y * gl_NumWorkGroups.y;
+        }
     }
 }
diff --git a/ml/backend/ggml/ggml/src/ggml-vulkan/vulkan-shaders/dequant_funcs.glsl b/ml/backend/ggml/ggml/src/ggml-vulkan/vulkan-shaders/dequant_funcs.glsl
index 0d98f5a9..09676a62 100644
--- a/ml/backend/ggml/ggml/src/ggml-vulkan/vulkan-shaders/dequant_funcs.glsl
+++ b/ml/backend/ggml/ggml/src/ggml-vulkan/vulkan-shaders/dequant_funcs.glsl
@@ -437,7 +437,7 @@ vec4 dequantize4(uint ib, uint iqs, uint a_offset) {
 #if defined(DATA_A_MXFP4)
 vec2 dequantize(uint ib, uint iqs, uint a_offset) {
     const uint vui = uint(data_a[a_offset + ib].qs[iqs]);
-    return vec2(kvalues_mxfp4[vui & 0xF], kvalues_mxfp4[vui >> 4]);
+    return vec2(kvalues_mxfp4[vui & 0xF], kvalues_mxfp4[vui >> 4]) * 0.5;
 }
 vec4 dequantize4(uint ib, uint iqs, uint a_offset) {
     vec2 v0 = dequantize(ib, iqs, a_offset);
@@ -488,9 +488,9 @@ vec2 dequantize(uint ib, uint iqs, uint a_offset) {
 
     const uvec2 qs = uvec2(data_a[a_offset + ib].qs[qsi], data_a[a_offset + ib].qs[qsi + 1]);
     const uint scales = data_a[a_offset + ib].scales[scalesi];
-    const vec2 d = vec2(data_a[a_offset + ib].d);
+    const vec2 dm = vec2(data_a[a_offset + ib].dm);
 
-    return d.x * float(scales & 0xF) * vec2((qs >> qsshift) & 3) - d.y * float(scales >> 4);
+    return dm.x * float(scales & 0xF) * vec2((qs >> qsshift) & 3) - dm.y * float(scales >> 4);
 }
 vec2 get_dm(uint ib, uint a_offset) {
     return vec2(1, 0);
@@ -529,7 +529,7 @@ vec2 dequantize(uint ib, uint iqs, uint a_offset) {
     const uint is = 2 * n + b;                 // 0..7
     const uint qsi = n * 32 + (iqs % 16) * 2;  // 0,2,4..126
 
-    const vec2 loadd = vec2(data_a[a_offset + ib].d);
+    const vec2 loadd = vec2(data_a[a_offset + ib].dm);
 
     const uint scidx0 = (is < 4) ? is : (is + 4);
     const uint scidx1 = (is < 4) ? is : (is - 4);
@@ -567,7 +567,7 @@ vec2 dequantize(uint ib, uint iqs, uint a_offset) {
 
     const uint8_t hm = uint8_t(1 << (iqs / 16));
 
-    const vec2 loadd = vec2(data_a[a_offset + ib].d);
+    const vec2 loadd = vec2(data_a[a_offset + ib].dm);
 
     const uint scidx0 = (is < 4) ? is : (is + 4);
     const uint scidx1 = (is < 4) ? is : (is - 4);
diff --git a/ml/backend/ggml/ggml/src/ggml-vulkan/vulkan-shaders/dequant_funcs_cm2.glsl b/ml/backend/ggml/ggml/src/ggml-vulkan/vulkan-shaders/dequant_funcs_cm2.glsl
index 67baedf7..8ac6482d 100644
--- a/ml/backend/ggml/ggml/src/ggml-vulkan/vulkan-shaders/dequant_funcs_cm2.glsl
+++ b/ml/backend/ggml/ggml/src/ggml-vulkan/vulkan-shaders/dequant_funcs_cm2.glsl
@@ -120,7 +120,7 @@ layout(buffer_reference, std430, buffer_reference_align = 16) buffer decodeBufQ2
 float16_t dequantFuncQ2_K(const in decodeBufQ2_K bl, const in uint blockCoords[2], const in uint coordInBlock[2])
 {
     decodeBufQ2_K_packed16 bl16 = decodeBufQ2_K_packed16(bl);
-    const f16vec2 d = bl.block.d;
+    const f16vec2 dm = bl.block.dm;
     const uint idx = coordInBlock[1];
 
     const uint scalesi = (idx & 0xF0) >> 4;             // 0..15
@@ -131,7 +131,7 @@ float16_t dequantFuncQ2_K(const in decodeBufQ2_K bl, const in uint blockCoords[2
     qs = unpack8(qs)[idx & 1];
 
     const uint scales = bl.block.scales[scalesi];
-    float16_t ret = d.x * float16_t(scales & 0xF) * float16_t(qs) - d.y * float16_t(scales >> 4);
+    float16_t ret = dm.x * float16_t(scales & 0xF) * float16_t(qs) - dm.y * float16_t(scales >> 4);
     return ret;
 }
 
@@ -680,7 +680,7 @@ float16_t dequantFuncMXFP4(const in decodeBufMXFP4 bl, const in uint blockCoords
     uint32_t qs = bl.block.qs[iqs];
     qs >>= shift;
     qs &= 0xF;
-    float16_t ret = float16_t(kvalues_mxfp4[qs] * d);
+    float16_t ret = float16_t(kvalues_mxfp4[qs] * d * 0.5);
     return ret;
 }
 #endif
diff --git a/ml/backend/ggml/ggml/src/ggml-vulkan/vulkan-shaders/dequant_mxfp4.comp b/ml/backend/ggml/ggml/src/ggml-vulkan/vulkan-shaders/dequant_mxfp4.comp
index ffba5a77..3194ba29 100644
--- a/ml/backend/ggml/ggml/src/ggml-vulkan/vulkan-shaders/dequant_mxfp4.comp
+++ b/ml/backend/ggml/ggml/src/ggml-vulkan/vulkan-shaders/dequant_mxfp4.comp
@@ -26,7 +26,7 @@ void main() {
     const float d = e8m0_to_fp32(data_a[ib].e);
 
     [[unroll]] for (uint l = 0; l < 8; ++l) {
-        data_b[b_idx + l +  0] = D_TYPE(d * kvalues_mxfp4[data_a[ib].qs[q_idx + l] & 0xF]);
-        data_b[b_idx + l + 16] = D_TYPE(d * kvalues_mxfp4[data_a[ib].qs[q_idx + l] >>  4]);
+        data_b[b_idx + l +  0] = D_TYPE(d * 0.5 * float(kvalues_mxfp4[data_a[ib].qs[q_idx + l] & 0xF]));
+        data_b[b_idx + l + 16] = D_TYPE(d * 0.5 * float(kvalues_mxfp4[data_a[ib].qs[q_idx + l] >>  4]));
     }
 }
diff --git a/ml/backend/ggml/ggml/src/ggml-vulkan/vulkan-shaders/dequant_q2_k.comp b/ml/backend/ggml/ggml/src/ggml-vulkan/vulkan-shaders/dequant_q2_k.comp
index 58dc2e5d..dc05a783 100644
--- a/ml/backend/ggml/ggml/src/ggml-vulkan/vulkan-shaders/dequant_q2_k.comp
+++ b/ml/backend/ggml/ggml/src/ggml-vulkan/vulkan-shaders/dequant_q2_k.comp
@@ -24,8 +24,8 @@ void main() {
         const uint ql_idx = 32 * ip + il;
         const uint8_t qs = data_a[i].qs[32 * ip + il];
 
-        FLOAT_TYPE dall = FLOAT_TYPE(data_a[i].d.x);
-        FLOAT_TYPE dmin = FLOAT_TYPE(data_a[i].d.y);
+        FLOAT_TYPE dall = FLOAT_TYPE(data_a[i].dm.x);
+        FLOAT_TYPE dmin = FLOAT_TYPE(data_a[i].dm.y);
         data_b[y_idx +  0] = D_TYPE(dall * FLOAT_TYPE((data_a[i].scales[is+0] & 0xF) * ((qs >> 0) & 3)) - dmin * FLOAT_TYPE(data_a[i].scales[is+0] >> 4));
         data_b[y_idx + 32] = D_TYPE(dall * FLOAT_TYPE((data_a[i].scales[is+2] & 0xF) * ((qs >> 2) & 3)) - dmin * FLOAT_TYPE(data_a[i].scales[is+2] >> 4));
         data_b[y_idx + 64] = D_TYPE(dall * FLOAT_TYPE((data_a[i].scales[is+4] & 0xF) * ((qs >> 4) & 3)) - dmin * FLOAT_TYPE(data_a[i].scales[is+4] >> 4));
diff --git a/ml/backend/ggml/ggml/src/ggml-vulkan/vulkan-shaders/dequant_q4_k.comp b/ml/backend/ggml/ggml/src/ggml-vulkan/vulkan-shaders/dequant_q4_k.comp
index 8b7be557..0f23dc0a 100644
--- a/ml/backend/ggml/ggml/src/ggml-vulkan/vulkan-shaders/dequant_q4_k.comp
+++ b/ml/backend/ggml/ggml/src/ggml-vulkan/vulkan-shaders/dequant_q4_k.comp
@@ -20,8 +20,8 @@ void main() {
         const uint is = 2 * il;
         const uint n = 4;
 
-        const FLOAT_TYPE dall = FLOAT_TYPE(data_a[ib].d.x);
-        const FLOAT_TYPE dmin = FLOAT_TYPE(data_a[ib].d.y);
+        const FLOAT_TYPE dall = FLOAT_TYPE(data_a[ib].dm.x);
+        const FLOAT_TYPE dmin = FLOAT_TYPE(data_a[ib].dm.y);
 
         const uint y_idx = ib * QUANT_K + 64 * il + n * ir;
         const uint qs_idx = 32*il + n * ir;
diff --git a/ml/backend/ggml/ggml/src/ggml-vulkan/vulkan-shaders/dequant_q5_k.comp b/ml/backend/ggml/ggml/src/ggml-vulkan/vulkan-shaders/dequant_q5_k.comp
index 6bc04670..970469a6 100644
--- a/ml/backend/ggml/ggml/src/ggml-vulkan/vulkan-shaders/dequant_q5_k.comp
+++ b/ml/backend/ggml/ggml/src/ggml-vulkan/vulkan-shaders/dequant_q5_k.comp
@@ -19,8 +19,8 @@ void main() {
         const uint ir = tid % 16;
         const uint is = 2 * il;
 
-        const FLOAT_TYPE dall = FLOAT_TYPE(data_a[ib].d.x);
-        const FLOAT_TYPE dmin = FLOAT_TYPE(data_a[ib].d.y);
+        const FLOAT_TYPE dall = FLOAT_TYPE(data_a[ib].dm.x);
+        const FLOAT_TYPE dmin = FLOAT_TYPE(data_a[ib].dm.y);
 
         const uint y_idx = ib * QUANT_K + 64 * il + 2 * ir;
         const uint qs_idx = 32*il + 2 * ir;
diff --git a/ml/backend/ggml/ggml/src/ggml-vulkan/vulkan-shaders/mul_mat_vec_q2_k.comp b/ml/backend/ggml/ggml/src/ggml-vulkan/vulkan-shaders/mul_mat_vec_q2_k.comp
index 03ed25d3..14093c0d 100644
--- a/ml/backend/ggml/ggml/src/ggml-vulkan/vulkan-shaders/mul_mat_vec_q2_k.comp
+++ b/ml/backend/ggml/ggml/src/ggml-vulkan/vulkan-shaders/mul_mat_vec_q2_k.comp
@@ -41,9 +41,7 @@ void calc_superblock(const uint a_offset, const uint b_offset, const uint itid,
         const vec4 qs_u32_4 = vec4(unpack8((qs_u32 >> 4) & 0x03030303));
         const vec4 qs_u32_6 = vec4(unpack8((qs_u32 >> 6) & 0x03030303));
 
-        vec2 d = vec2(data_a[ib0 + i].d);
-        const FLOAT_TYPE dall = FLOAT_TYPE(d.x);
-        const FLOAT_TYPE dmin = FLOAT_TYPE(d.y);
+        const FLOAT_TYPE_VEC2 dm = vec2(data_a[ib0 + i].dm);
 
         [[unroll]] for (uint j = 0; j < NUM_COLS; ++j) {
             vec2 b0 =   vec2(data_b_v2[(j*p.batch_stride_b + b_offset + y_idx) / 2 +  0]);
@@ -75,7 +73,7 @@ void calc_superblock(const uint a_offset, const uint b_offset, const uint itid,
                        fma(FLOAT_TYPE(b96[l]),  sccache2[csel][ix][6 + 8*v_im],
                        fma(FLOAT_TYPE(b112[l]), sccache2[csel][ix][7 + 8*v_im], sum2))))))));
             }
-            temp[j][n] = fma(dall, sum1, fma(-dmin, sum2, temp[j][n]));
+            temp[j][n] = fma(dm.x, sum1, fma(-dm.y, sum2, temp[j][n]));
         }
     }
 }
diff --git a/ml/backend/ggml/ggml/src/ggml-vulkan/vulkan-shaders/mul_mat_vec_q4_k.comp b/ml/backend/ggml/ggml/src/ggml-vulkan/vulkan-shaders/mul_mat_vec_q4_k.comp
index 21d07d2e..49d91ad5 100644
--- a/ml/backend/ggml/ggml/src/ggml-vulkan/vulkan-shaders/mul_mat_vec_q4_k.comp
+++ b/ml/backend/ggml/ggml/src/ggml-vulkan/vulkan-shaders/mul_mat_vec_q4_k.comp
@@ -14,9 +14,7 @@ void calc_superblock(const uint a_offset, const uint b_offset, const uint v_im,
 
     [[unroll]] for (uint n = 0; n < num_rows; ++n) {
         const uint ib0 = a_offset / QUANT_K + (first_row+n)*num_blocks_per_row;
-        vec2 d = vec2(data_a[ib0 + i].d);
-        const FLOAT_TYPE dall = FLOAT_TYPE(d.x);
-        const FLOAT_TYPE dmin = FLOAT_TYPE(d.y);
+        const FLOAT_TYPE_VEC2 dm = FLOAT_TYPE_VEC2(data_a[ib0 + i].dm);
 
         const uint32_t scale0_u32 = data_a_packed16[ib0 + i].scales[v_im    ];
         const uint32_t scale4_u32 = data_a_packed16[ib0 + i].scales[v_im + 2];
@@ -81,7 +79,7 @@ void calc_superblock(const uint a_offset, const uint b_offset, const uint v_im,
                 fma(FLOAT_TYPE(by10.y), sc2, fma(FLOAT_TYPE(by132.y), sc3, fma(FLOAT_TYPE(by20.y), sc6, fma(FLOAT_TYPE(by232.y), sc7,
                 fma(FLOAT_TYPE(by10.z), sc2, fma(FLOAT_TYPE(by132.z), sc3, fma(FLOAT_TYPE(by20.z), sc6, fma(FLOAT_TYPE(by232.z), sc7,
                 fma(FLOAT_TYPE(by10.w), sc2, fma(FLOAT_TYPE(by132.w), sc3, fma(FLOAT_TYPE(by20.w), sc6,     FLOAT_TYPE(by232.w) * sc7)))))))))))))));
-            temp[j][n] = fma(dall, fma(sx, sc0, fma(sy, sc1, fma(sz, sc4, sw * sc5))), fma(-dmin, smin, temp[j][n]));
+            temp[j][n] = fma(dm.x, fma(sx, sc0, fma(sy, sc1, fma(sz, sc4, sw * sc5))), fma(-dm.y, smin, temp[j][n]));
         }
     }
 }
diff --git a/ml/backend/ggml/ggml/src/ggml-vulkan/vulkan-shaders/mul_mat_vec_q5_k.comp b/ml/backend/ggml/ggml/src/ggml-vulkan/vulkan-shaders/mul_mat_vec_q5_k.comp
index 9e46c89a..0d61b496 100644
--- a/ml/backend/ggml/ggml/src/ggml-vulkan/vulkan-shaders/mul_mat_vec_q5_k.comp
+++ b/ml/backend/ggml/ggml/src/ggml-vulkan/vulkan-shaders/mul_mat_vec_q5_k.comp
@@ -14,9 +14,7 @@ void calc_superblock(const uint a_offset, const uint b_offset, const uint v_im,
 
     [[unroll]] for (uint n = 0; n < num_rows; ++n) {
         const uint ib0 = a_offset / QUANT_K + (first_row+n)*num_blocks_per_row;
-        vec2 d = vec2(data_a[ib0 + i].d);
-        const FLOAT_TYPE dall = FLOAT_TYPE(d.x);
-        const FLOAT_TYPE dmin = FLOAT_TYPE(d.y);
+        const FLOAT_TYPE_VEC2 dm = FLOAT_TYPE_VEC2(data_a[ib0 + i].dm);
 
         const uint32_t scale0_u32 = data_a_packed16[ib0 + i].scales[v_im    ];
         const uint32_t scale4_u32 = data_a_packed16[ib0 + i].scales[v_im + 2];
@@ -113,7 +111,7 @@ void calc_superblock(const uint a_offset, const uint b_offset, const uint v_im,
               fma(FLOAT_TYPE(by132.x) + FLOAT_TYPE(by132.y) + FLOAT_TYPE(by148.x) + FLOAT_TYPE(by148.y), sc3,
               fma(FLOAT_TYPE(by20.x) + FLOAT_TYPE(by20.y) + FLOAT_TYPE(by216.x) + FLOAT_TYPE(by216.y), sc6,
                   (FLOAT_TYPE(by232.x) + FLOAT_TYPE(by232.y) + FLOAT_TYPE(by248.x) + FLOAT_TYPE(by248.y)) * sc7)));
-            temp[j][n] = fma(dall, fma(sx, sc0, fma(sy, sc1, fma(sz, sc4, sw * sc5))), fma(-dmin, smin, temp[j][n]));
+            temp[j][n] = fma(dm.x, fma(sx, sc0, fma(sy, sc1, fma(sz, sc4, sw * sc5))), fma(-dm.y, smin, temp[j][n]));
         }
     }
 }
diff --git a/ml/backend/ggml/ggml/src/ggml-vulkan/vulkan-shaders/mul_mm.comp b/ml/backend/ggml/ggml/src/ggml-vulkan/vulkan-shaders/mul_mm.comp
index a20788c4..d260969f 100644
--- a/ml/backend/ggml/ggml/src/ggml-vulkan/vulkan-shaders/mul_mm.comp
+++ b/ml/backend/ggml/ggml/src/ggml-vulkan/vulkan-shaders/mul_mm.comp
@@ -120,81 +120,11 @@ shared FLOAT_TYPE_VEC2 buf_b[BN * SHMEM_STRIDE];
 
 #define NUM_WARPS (BLOCK_SIZE / WARP)
 
-#ifdef MUL_MAT_ID
-shared u16vec2 row_ids[BN];
-uint _ne1;
-
-#ifdef MUL_MAT_ID_USE_SUBGROUPS
-shared uvec4 ballots_sh[NUM_WARPS];
-
-void load_row_ids(uint expert_idx, bool nei0_is_pow2, uint ic) {
-    _ne1 = 0;
-    uint num_elements = p.nei1 * p.nei0;
-    uint nei0shift = findLSB(p.nei0);
-
-    uint ids[16];
-    uint iter = 0;
-
-    for (uint j = 0; j < num_elements; j += BLOCK_SIZE) {
-        // prefetch up to 16 elements
-        if (iter == 0) {
-            [[unroll]] for (uint k = 0; k < 16; ++k) {
-                uint i = j + gl_LocalInvocationIndex + k*BLOCK_SIZE;
-                bool in_range = i < num_elements;
-                uint ii1;
-                if (nei0_is_pow2) {
-                    ii1 = i >> nei0shift;
-                } else {
-                    ii1 = i / p.nei0;
-                }
-                uint ii0 = i - ii1 * p.nei0;
-                ids[k] = in_range ? data_ids[ii1*p.nbi1 + ii0] : 0;
-            }
-        }
-        uint i = j + gl_LocalInvocationIndex;
-        bool in_range = i < num_elements;
-        uint ii1;
-        if (nei0_is_pow2) {
-            ii1 = i >> nei0shift;
-        } else {
-            ii1 = i / p.nei0;
-        }
-        uint ii0 = i - ii1 * p.nei0;
-        uint id = ids[iter++];
-        uvec4 ballot = subgroupBallot(in_range && id == expert_idx);
-
-        ballots_sh[gl_SubgroupID] = ballot;
-        barrier();
-
-        uint subgroup_base = 0;
-        uint total = 0;
-        for (uint k = 0; k < gl_NumSubgroups; ++k) {
-            if (k == gl_SubgroupID) {
-                subgroup_base = total;
-            }
-            total += subgroupBallotBitCount(ballots_sh[k]);
-        }
-        barrier();
-
-        uint idx = subgroup_base + subgroupBallotExclusiveBitCount(ballot);
-        if (in_range && id == expert_idx && _ne1 + idx >= ic * BN && _ne1 + idx < (ic + 1) * BN) {
-            row_ids[_ne1 + idx - ic * BN] = u16vec2(ii0, ii1);
-        }
-        _ne1 += total;
-        iter &= 15;
-        if (_ne1 >= (ic + 1) * BN) {
-            break;
-        }
-    }
-    barrier();
-}
-#endif // MUL_MAT_ID_USE_SUBGROUPS
-#endif // MUL_MAT_ID
-
 #ifdef COOPMAT
 shared ACC_TYPE coopmat_stage[TM * TN * NUM_WARPS];
 #endif
 
+#include "mul_mm_id_funcs.glsl"
 #include "mul_mm_funcs.glsl"
 
 void main() {
diff --git a/ml/backend/ggml/ggml/src/ggml-vulkan/vulkan-shaders/mul_mm_funcs.glsl b/ml/backend/ggml/ggml/src/ggml-vulkan/vulkan-shaders/mul_mm_funcs.glsl
index 0ebfbd64..ee5ded2e 100644
--- a/ml/backend/ggml/ggml/src/ggml-vulkan/vulkan-shaders/mul_mm_funcs.glsl
+++ b/ml/backend/ggml/ggml/src/ggml-vulkan/vulkan-shaders/mul_mm_funcs.glsl
@@ -134,15 +134,15 @@ void load_a_to_shmem(const uint pos_a, const uint row, const uint col, const uin
             const uint ib = idx / 128;                         // 2 values per idx
             const uint iqs = idx % 128;                        // 0..127
 
-            const uint qsi = (iqs / 64) * 32 + (iqs % 16) * 2; // 0,2,4..30
+            const uint qsi = (iqs / 64) * 16 + (iqs % 16);     // 0..15
             const uint scalesi = iqs / 8;                      // 0..15
             const uint qsshift = ((iqs % 64) / 16) * 2;        // 0,2,4,6
 
-            const uvec2 qs = uvec2(data_a[ib].qs[qsi], data_a[ib].qs[qsi + 1]);
+            const uvec2 qs = uvec2(unpack8(data_a_packed16[ib].qs[qsi]));
             const uint scales = data_a[ib].scales[scalesi];
-            const vec2 d = vec2(data_a[ib].d);
+            const vec2 dm = vec2(data_a[ib].dm);
 
-            const vec2 v = d.x * float(scales & 0xF) * vec2((qs >> qsshift) & 3) - d.y * float(scales >> 4);
+            const vec2 v = dm.x * float(scales & 0xF) * vec2((qs >> qsshift) & 3) - dm.y * float(scales >> 4);
 
             buf_a[buf_idx] = FLOAT_TYPE_VEC2(v.xy);
 #elif defined(DATA_A_Q3_K)
@@ -179,7 +179,7 @@ void load_a_to_shmem(const uint pos_a, const uint row, const uint col, const uin
             const uint is = 2 * n + b;                 // 0..7
             const uint qsi = n * 32 + (iqs % 16) * 2;  // 0,2,4..126
 
-            const vec2 loadd = vec2(data_a[ib].d);
+            const vec2 loadd = vec2(data_a[ib].dm);
 
             const uint scidx0 = (is < 4) ? is : (is + 4);
             const uint scidx1 = (is < 4) ? is : (is - 4);
@@ -215,7 +215,7 @@ void load_a_to_shmem(const uint pos_a, const uint row, const uint col, const uin
 
             const uint8_t hm = uint8_t(1 << (iqs / 16));
 
-            const vec2 loadd = vec2(data_a[ib].d);
+            const vec2 loadd = vec2(data_a[ib].dm);
 
             const uint scidx0 = (is < 4) ? is : (is + 4);
             const uint scidx1 = (is < 4) ? is : (is - 4);
@@ -468,7 +468,7 @@ void load_a_to_shmem(const uint pos_a, const uint row, const uint col, const uin
             const uint ib = idx / 8;
             const uint iqs = (idx & 0x07) * 2;
 
-            const float d = e8m0_to_fp32(data_a[ib].e);
+            const float d = e8m0_to_fp32(data_a[ib].e) * 0.5;
             const uint vui = uint(data_a[ib].qs[iqs]);
             const uint vui2 = uint(data_a[ib].qs[iqs+1]);
 
diff --git a/ml/backend/ggml/ggml/src/ggml-vulkan/vulkan-shaders/mul_mm_id_funcs.glsl b/ml/backend/ggml/ggml/src/ggml-vulkan/vulkan-shaders/mul_mm_id_funcs.glsl
new file mode 100644
index 00000000..1d0e84ac
--- /dev/null
+++ b/ml/backend/ggml/ggml/src/ggml-vulkan/vulkan-shaders/mul_mm_id_funcs.glsl
@@ -0,0 +1,70 @@
+#ifdef MUL_MAT_ID
+shared u16vec2 row_ids[BN];
+uint _ne1;
+
+#ifdef MUL_MAT_ID_USE_SUBGROUPS
+shared uvec4 ballots_sh[NUM_WARPS];
+
+void load_row_ids(uint expert_idx, bool nei0_is_pow2, uint ic) {
+    _ne1 = 0;
+    uint num_elements = p.nei1 * p.nei0;
+    uint nei0shift = findLSB(p.nei0);
+
+    uint ids[16];
+    uint iter = 0;
+
+    for (uint j = 0; j < num_elements; j += BLOCK_SIZE) {
+        // prefetch up to 16 elements
+        if (iter == 0) {
+            [[unroll]] for (uint k = 0; k < 16; ++k) {
+                uint i = j + gl_LocalInvocationIndex + k*BLOCK_SIZE;
+                bool in_range = i < num_elements;
+                uint ii1;
+                if (nei0_is_pow2) {
+                    ii1 = i >> nei0shift;
+                } else {
+                    ii1 = i / p.nei0;
+                }
+                uint ii0 = i - ii1 * p.nei0;
+                ids[k] = in_range ? data_ids[ii1*p.nbi1 + ii0] : 0;
+            }
+        }
+        uint i = j + gl_LocalInvocationIndex;
+        bool in_range = i < num_elements;
+        uint ii1;
+        if (nei0_is_pow2) {
+            ii1 = i >> nei0shift;
+        } else {
+            ii1 = i / p.nei0;
+        }
+        uint ii0 = i - ii1 * p.nei0;
+        uint id = ids[iter++];
+        uvec4 ballot = subgroupBallot(in_range && id == expert_idx);
+
+        ballots_sh[gl_SubgroupID] = ballot;
+        barrier();
+
+        uint subgroup_base = 0;
+        uint total = 0;
+        for (uint k = 0; k < gl_NumSubgroups; ++k) {
+            if (k == gl_SubgroupID) {
+                subgroup_base = total;
+            }
+            total += subgroupBallotBitCount(ballots_sh[k]);
+        }
+        barrier();
+
+        uint idx = subgroup_base + subgroupBallotExclusiveBitCount(ballot);
+        if (in_range && id == expert_idx && _ne1 + idx >= ic * BN && _ne1 + idx < (ic + 1) * BN) {
+            row_ids[_ne1 + idx - ic * BN] = u16vec2(ii0, ii1);
+        }
+        _ne1 += total;
+        iter &= 15;
+        if (_ne1 >= (ic + 1) * BN) {
+            break;
+        }
+    }
+    barrier();
+}
+#endif // MUL_MAT_ID_USE_SUBGROUPS
+#endif // MUL_MAT_ID
diff --git a/ml/backend/ggml/ggml/src/ggml-vulkan/vulkan-shaders/mul_mmq.comp b/ml/backend/ggml/ggml/src/ggml-vulkan/vulkan-shaders/mul_mmq.comp
index b5d761c0..d955b4fc 100644
--- a/ml/backend/ggml/ggml/src/ggml-vulkan/vulkan-shaders/mul_mmq.comp
+++ b/ml/backend/ggml/ggml/src/ggml-vulkan/vulkan-shaders/mul_mmq.comp
@@ -10,10 +10,9 @@
 #extension GL_EXT_shader_explicit_arithmetic_types_float16 : require
 #endif
 
-#ifdef COOPMAT
-#extension GL_KHR_cooperative_matrix : enable
-#extension GL_KHR_memory_scope_semantics : enable
+#if defined(MUL_MAT_ID_USE_SUBGROUPS)
 #extension GL_KHR_shader_subgroup_basic : enable
+#extension GL_KHR_shader_subgroup_ballot : enable
 #endif
 
 #ifdef MUL_MAT_ID
@@ -24,7 +23,10 @@
 
 layout(local_size_x_id = 0, local_size_y = 1, local_size_z = 1) in;
 
-layout (binding = 0) readonly buffer A {A_TYPE_PACKED16 data_a[];};
+layout (binding = 0) readonly buffer A {A_TYPE data_a[];};
+#if defined(A_TYPE_PACKED16)
+layout (binding = 0) readonly buffer A_PACKED16 {A_TYPE_PACKED16 data_a_packed16[];};
+#endif
 #if defined(A_TYPE_PACKED32)
 layout (binding = 0) readonly buffer A_PACKED32 {A_TYPE_PACKED32 data_a_packed32[];};
 #endif
@@ -76,40 +78,31 @@ layout (constant_id = 10) const uint WARP = 32;
 
 #define BK 32
 
-#ifdef COOPMAT
-#define SHMEM_STRIDE (BK / 4 + 4)
-#else
-#define SHMEM_STRIDE (BK / 4 + 1)
-#endif
+#define MMQ_SHMEM
 
-shared int32_t buf_a_qs[BM * SHMEM_STRIDE];
-
-#ifndef COOPMAT
-#if QUANT_AUXF == 1
-shared FLOAT_TYPE buf_a_dm[BM];
-#else
-shared FLOAT_TYPE_VEC2 buf_a_dm[BM];
-#endif
-#endif
-
-shared int32_t buf_b_qs[BN * SHMEM_STRIDE];
-#ifndef COOPMAT
-shared FLOAT_TYPE_VEC2 buf_b_ds[BN];
-#endif
-
-#define LOAD_VEC_A (4 * QUANT_R)
-#define LOAD_VEC_B 16
+#include "mul_mmq_shmem_types.glsl"
 
 #ifdef MUL_MAT_ID
-shared u16vec2 row_ids[4096];
-#endif // MUL_MAT_ID
+#define BK_STEP 1
+#else
+#ifndef BK_STEP
+#define BK_STEP 4
+#endif
+#endif
+
+// Shared memory cache
+shared block_a_cache buf_a[BM * BK_STEP];
+shared block_b_cache buf_b[BN * BK_STEP];
+// Register cache
+block_a_cache cache_a[WMITER * TM];
+block_b_cache cache_b;
+
+#define LOAD_VEC_A (4 * QUANT_R_MMQ)
+#define LOAD_VEC_B 16
 
 #define NUM_WARPS (BLOCK_SIZE / WARP)
 
-#ifdef COOPMAT
-shared ACC_TYPE coopmat_stage[TM * TN * NUM_WARPS];
-#endif
-
+#include "mul_mm_id_funcs.glsl"
 #include "mul_mmq_funcs.glsl"
 
 void main() {
@@ -139,26 +132,12 @@ void main() {
     const uint WNITER = (WM * WN) / (WARP * TM * TN * WMITER);
     const uint WSUBM = WM / WMITER;
     const uint WSUBN = WN / WNITER;
-
-#ifdef COOPMAT
-    const uint warp_i = gl_SubgroupID;
-
-    const uint tiw = gl_SubgroupInvocationID;
-
-    const uint cms_per_row = WM / TM;
-    const uint cms_per_col = WN / TN;
-
-    const uint storestride = WARP / TM;
-    const uint store_r = tiw % TM;
-    const uint store_c = tiw / TM;
-#else
     const uint warp_i = gl_LocalInvocationID.x / WARP;
 
     const uint tiw = gl_LocalInvocationID.x % WARP;
 
     const uint tiwr = tiw % (WSUBM / TM);
     const uint tiwc = tiw / (WSUBM / TM);
-#endif
 
     const uint warp_r = warp_i % (BM / WM);
     const uint warp_c = warp_i / (BM / WM);
@@ -172,17 +151,27 @@ void main() {
     const uint loadstride_b = BLOCK_SIZE * LOAD_VEC_B / BK;
 
 #ifdef MUL_MAT_ID
-    uint _ne1 = 0;
-    for (uint ii1 = 0; ii1 < p.nei1; ii1++) {
-        for (uint ii0 = 0; ii0 < p.nei0; ii0++) {
+#ifdef MUL_MAT_ID_USE_SUBGROUPS
+    if (bitCount(p.nei0) == 1) {
+        load_row_ids(expert_idx, true, ic);
+    } else {
+        load_row_ids(expert_idx, false, ic);
+    }
+#else
+    _ne1 = 0;
+    for (uint ii1 = 0; ii1 < p.nei1 && _ne1 < (ic + 1) * BN; ii1++) {
+        for (uint ii0 = 0; ii0 < p.nei0 && _ne1 < (ic + 1) * BN; ii0++) {
             if (data_ids[ii1*p.nbi1 + ii0] == expert_idx) {
-                row_ids[_ne1] = u16vec2(ii0, ii1);
+                if (_ne1 >= ic * BN) {
+                    row_ids[_ne1 - ic * BN] = u16vec2(ii0, ii1);
+                }
                 _ne1++;
             }
         }
     }
 
     barrier();
+#endif
 
     // Workgroup has no work
     if (ic * BN >= _ne1) return;
@@ -209,159 +198,70 @@ void main() {
     uint pos_b_ib = (batch_idx * p.batch_stride_b + ic * BN * p.stride_b + start_k) / BK;
 #endif
 
-#ifdef COOPMAT
-    coopmat<int8_t, gl_ScopeSubgroup, TM, TK, gl_MatrixUseA> cache_a;
-    coopmat<int8_t, gl_ScopeSubgroup, TK, TN, gl_MatrixUseB> cache_b;
-    coopmat<int32_t, gl_ScopeSubgroup, TM, TN, gl_MatrixUseAccumulator> cm_result;
-
-    coopmat<ACC_TYPE, gl_ScopeSubgroup, TM, TN, gl_MatrixUseAccumulator> factors[cms_per_row * cms_per_col];
-
-    coopmat<ACC_TYPE, gl_ScopeSubgroup, TM, TN, gl_MatrixUseAccumulator> sums[cms_per_row * cms_per_col];
-
-    [[unroll]] for (uint i = 0; i < cms_per_row * cms_per_col; i++) {
-        sums[i] = coopmat<ACC_TYPE, gl_ScopeSubgroup, TM, TN, gl_MatrixUseAccumulator>(0.0f);
-    }
-#else
-    int32_t cache_a_qs[WMITER * TM * BK / 4];
-
-    int32_t cache_b_qs[TN * BK / 4];
-
     ACC_TYPE sums[WMITER * TM * WNITER * TN];
 
     [[unroll]] for (uint i = 0; i < WMITER*TM*WNITER*TN; i++) {
         sums[i] = ACC_TYPE(0.0f);
     }
-#endif
 
-#if QUANT_AUXF == 1
-    FLOAT_TYPE cache_a_dm[WMITER * TM];
-#else
-    FLOAT_TYPE_VEC2 cache_a_dm[WMITER * TM];
-#endif
-
-    FLOAT_TYPE_VEC2 cache_b_ds[TN];
-
-    for (uint block = start_k; block < end_k; block += BK) {
+    for (uint block = start_k; block < end_k; block += BK * BK_STEP) {
         [[unroll]] for (uint l = 0; loadc_a + l < BM; l += loadstride_a) {
-            const uint ib = pos_a_ib + (loadc_a + l) * p.stride_a / BK;
-            const uint iqs = loadr_a;
             const uint buf_ib = loadc_a + l;
+            const uint ib = pos_a_ib + buf_ib * p.stride_a / BK;
+            const uint iqs = loadr_a;
 
-            if (iqs == 0) {
-#if QUANT_AUXF == 1
-                buf_a_dm[buf_ib] = get_d(ib);
-#else
-                buf_a_dm[buf_ib] = get_dm(ib);
-#endif
+            [[unroll]] for (uint k_step = 0; k_step < BK_STEP; k_step++) {
+                block_a_to_shmem(k_step * BM + buf_ib, ib + k_step, iqs);
             }
-#if QUANT_R == 1
-            buf_a_qs[buf_ib * SHMEM_STRIDE + iqs] = repack(ib, iqs);
-#else
-            const i32vec2 vals = repack(ib, iqs);
-            buf_a_qs[buf_ib * SHMEM_STRIDE + iqs    ] = vals.x;
-            buf_a_qs[buf_ib * SHMEM_STRIDE + iqs + 4] = vals.y;
-#endif
         }
         [[unroll]] for (uint l = 0; loadc_b + l < BN; l += loadstride_b) {
-#ifdef MUL_MAT_ID
-            const u16vec2 row_idx = row_ids[ic * BN + loadc_b + l];
-            const uint idx = pos_b_ib + row_idx.y * p.batch_stride_b / LOAD_VEC_B + (row_idx.x % p.ne11) * p.stride_b / LOAD_VEC_B + loadr_b;
-            const uint ib = idx / 8;
-            const uint iqs = idx & 0x7;
-#else
-            const uint ib = pos_b_ib + (loadc_b + l) * p.stride_b / BK;
-            const uint ib_outer = ib / 4;
-            const uint ib_inner = ib % 4;
-
-            const uint iqs = loadr_b;
-#endif
-
             const uint buf_ib = loadc_b + l;
 
-            if (iqs == 0) {
-                buf_b_ds[buf_ib] = FLOAT_TYPE_VEC2(data_b[ib_outer].ds[ib_inner]);
+#ifdef MUL_MAT_ID
+            const u16vec2 row_idx = row_ids[buf_ib];
+            const uint ib = pos_b_ib + row_idx.y * p.batch_stride_b / BK + (row_idx.x % p.ne11) * p.stride_b / BK;
+#else
+            const uint ib = pos_b_ib + buf_ib * p.stride_b / BK;
+#endif
+            const uint iqs = loadr_b;
+
+            [[unroll]] for (uint k_step = 0; k_step < BK_STEP; k_step++) {
+                block_b_to_shmem(k_step * BN + buf_ib, ib + k_step, iqs);
             }
-            const ivec4 values = data_b[ib_outer].qs[ib_inner * 2 + iqs];
-            buf_b_qs[buf_ib * SHMEM_STRIDE + iqs * 4    ] = values.x;
-            buf_b_qs[buf_ib * SHMEM_STRIDE + iqs * 4 + 1] = values.y;
-            buf_b_qs[buf_ib * SHMEM_STRIDE + iqs * 4 + 2] = values.z;
-            buf_b_qs[buf_ib * SHMEM_STRIDE + iqs * 4 + 3] = values.w;
         }
 
         barrier();
 
-        pos_a_ib += 1;
-        pos_b_ib += 1;
+        pos_a_ib += BK_STEP;
+        pos_b_ib += BK_STEP;
 
-#ifdef COOPMAT
-        [[unroll]] for (uint cm_row = 0; cm_row < cms_per_row; cm_row++) {
-            const uint ib_a = warp_r * WM + cm_row * TM;
+        for (uint k_step = 0; k_step < BK_STEP; k_step++) {
             // Load from shared into cache
-            coopMatLoad(cache_a, buf_a_qs, ib_a * SHMEM_STRIDE, SHMEM_STRIDE, gl_CooperativeMatrixLayoutRowMajor);
-
-            // TODO: only cache values that are actually needed
-            [[unroll]] for (uint t_idx = 0; t_idx < TM; t_idx++) {
-                cache_a_dm[t_idx] = buf_a_dm[ib_a + t_idx];
-            }
-
-            [[unroll]] for (uint cm_col = 0; cm_col < cms_per_col; cm_col++) {
-                const uint ib_b = warp_c * WN + cm_col * TN;
-                coopMatLoad(cache_b, buf_b_qs, ib_b * SHMEM_STRIDE, SHMEM_STRIDE, gl_CooperativeMatrixLayoutColumnMajor);
-
-                // TODO: only cache values that are actually needed
-                [[unroll]] for (uint t_idx = 0; t_idx < TN; t_idx++) {
-                    cache_b_dm[t_idx] = buf_b_d[ib_b + t_idx];
-                }
-
-                cm_result = coopmat<int32_t, gl_ScopeSubgroup, TM, TN, gl_MatrixUseAccumulator>(0);
-                cm_result = coopMatMulAdd(cache_a, cache_b, cm_result);
-
-                [[unroll]] for (uint col = 0; col < TN; col += storestride) {
-                    coopmat_stage[warp_i * TM * TN + (store_c + col) * TM + store_r] = ACC_TYPE(float(cache_a_d[store_r]) * float(cache_b_d[store_c + col]));
-                }
-
-                coopMatLoad(factors, coopmat_stage, warp_i * TM * TN, TM, gl_CooperativeMatrixLayoutColumnMajor);
-                sums[cm_col * cms_per_row + cm_row] += factors * coopmat<ACC_TYPE, gl_ScopeSubgroup, TM, TN, gl_MatrixUseAccumulator>(cm_result);
-            }
-        }
-#else
-        // Load from shared into cache
-        [[unroll]] for (uint wsir = 0; wsir < WMITER; wsir++) {
-            [[unroll]] for (uint cr = 0; cr < TM; cr++) {
-                const uint ib = warp_r * WM + wsir * WSUBM + tiwr * TM + cr;
-                cache_a_dm[wsir * TM + cr] = buf_a_dm[ib];
-                [[unroll]] for (uint idx_k = 0; idx_k < BK / 4; idx_k++) {
-                    cache_a_qs[(wsir * TM + cr) * (BK / 4) + idx_k] = buf_a_qs[ib * SHMEM_STRIDE + idx_k];
-                }
-            }
-        }
-
-        [[unroll]] for (uint wsic = 0; wsic < WNITER; wsic++) {
-            [[unroll]] for (uint cc = 0; cc < TN; cc++) {
-                const uint ib = warp_c * WN + wsic * WSUBN + tiwc * TN + cc;
-                cache_b_ds[cc] = buf_b_ds[ib];
-                [[unroll]] for (uint idx_k = 0; idx_k < BK / 4; idx_k++) {
-                    cache_b_qs[cc * (BK / 4) + idx_k] = buf_b_qs[ib * SHMEM_STRIDE + idx_k];
-                }
-            }
-
             [[unroll]] for (uint wsir = 0; wsir < WMITER; wsir++) {
-                [[unroll]] for (uint cc = 0; cc < TN; cc++) {
-                    [[unroll]] for (uint cr = 0; cr < TM; cr++) {
-                        const uint cache_a_idx = wsir * TM + cr;
-                        const uint sums_idx = (wsic * TN + cc) * (WMITER * TM) + wsir * TM + cr;
-                        int32_t q_sum = 0;
-                        [[unroll]] for (uint idx_k = 0; idx_k < BK / 4; idx_k++) {
-                            q_sum += dotPacked4x8EXT(cache_a_qs[cache_a_idx * (BK / 4) + idx_k],
-                                                     cache_b_qs[cc * (BK / 4) + idx_k]);
-                        }
+                [[unroll]] for (uint cr = 0; cr < TM; cr++) {
+                    const uint reg_ib = wsir * TM + cr;
+                    const uint buf_ib = warp_r * WM + wsir * WSUBM + tiwr * TM + cr;
 
-                        sums[sums_idx] += mul_q8_1(q_sum, cache_a_dm[cache_a_idx], cache_b_ds[cc], 1);
+                    block_a_to_registers(reg_ib, k_step * BM + buf_ib);
+                }
+            }
+
+            [[unroll]] for (uint wsic = 0; wsic < WNITER; wsic++) {
+                [[unroll]] for (uint cc = 0; cc < TN; cc++) {
+                    const uint ib = k_step * BN + warp_c * WN + wsic * WSUBN + tiwc * TN + cc;
+                    block_b_to_registers(ib);
+
+                    [[unroll]] for (uint wsir = 0; wsir < WMITER; wsir++) {
+                        [[unroll]] for (uint cr = 0; cr < TM; cr++) {
+                            const uint cache_a_idx = wsir * TM + cr;
+                            const uint sums_idx = (wsic * TN + cc) * (WMITER * TM) + wsir * TM + cr;
+
+                            sums[sums_idx] += mmq_dot_product(cache_a_idx);
+                        }
                     }
                 }
             }
         }
-#endif
 
         barrier();
     }
@@ -373,54 +273,6 @@ void main() {
     const uint offsets = batch_idx * p.batch_stride_d + ik * p.batch_stride_d * gl_NumWorkGroups.z;
 #endif
 
-#ifdef COOPMAT
-#ifdef MUL_MAT_ID
-    [[unroll]] for (uint cm_row = 0; cm_row < cms_per_row; cm_row++) {
-        [[unroll]] for (uint cm_col = 0; cm_col < cms_per_col; cm_col++) {
-            coopMatStore(sums[cm_col * cms_per_row + cm_row], coopmat_stage, warp_i * TM * TN, TM, gl_CooperativeMatrixLayoutColumnMajor);
-
-            [[unroll]] for (uint col = 0; col < BN; col += storestride) {
-                const uint row_i = dc + cm_col * TN + col + store_c;
-                if (row_i >= _ne1) break;
-
-                const u16vec2 row_idx = row_ids[row_i];
-
-                data_d[row_idx.y * p.batch_stride_d + row_idx.x * p.stride_d + dr + cm_row * TM + store_r] = D_TYPE(coopmat_stage[warp_i * TM * TN + (col + store_c) * TM + store_r]);
-            }
-        }
-    }
-#else
-    const bool is_aligned = p.stride_d % 4 == 0;  // Assumption: D_TYPE == float
-
-    [[unroll]] for (uint cm_row = 0; cm_row < cms_per_row; cm_row++) {
-        [[unroll]] for (uint cm_col = 0; cm_col < cms_per_col; cm_col++) {
-            const bool is_in_bounds = dr + (cm_row + 1) * TM <= p.M && dc + (cm_col + 1) * TN <= p.N;
-
-            if (is_aligned && is_in_bounds) {
-                // Full coopMat is within bounds and stride_d is aligned with 16B
-                coopmat<D_TYPE, gl_ScopeSubgroup, TM, TN, gl_MatrixUseAccumulator> cm_dtype = coopmat<D_TYPE, gl_ScopeSubgroup, TM, TN, gl_MatrixUseAccumulator>(sums[cm_col * cms_per_row + cm_row]);
-                coopMatStore(cm_dtype, data_d, offsets + (dc + cm_col * TN) * p.stride_d + dr + cm_row * TM, p.stride_d, gl_CooperativeMatrixLayoutColumnMajor);
-            } else if (is_in_bounds) {
-                // Full coopMat is within bounds, but stride_d is not aligned
-                coopMatStore(sums[cm_col * cms_per_row + cm_row], coopmat_stage, warp_i * TM * TN, TM, gl_CooperativeMatrixLayoutColumnMajor);
-
-                [[unroll]] for (uint col = 0; col < TN; col += storestride) {
-                    data_d[offsets + (dc + cm_col * TN + col + store_c) * p.stride_d + dr + cm_row * TM + store_r] = D_TYPE(coopmat_stage[warp_i * TM * TN + (col + store_c) * TM + store_r]);
-                }
-            } else if (dr + cm_row * TM < p.M && dc + cm_col * TN < p.N) {
-                // Partial coopMat is within bounds
-                coopMatStore(sums[cm_col * cms_per_row + cm_row], coopmat_stage, warp_i * TM * TN, TM, gl_CooperativeMatrixLayoutColumnMajor);
-
-                [[unroll]] for (uint col = 0; col < TN; col += storestride) {
-                    if (dr + cm_row * TM + store_r < p.M && dc + cm_col * TN + col + store_c < p.N) {
-                        data_d[offsets + (dc + cm_col * TN + col + store_c) * p.stride_d + dr + cm_row * TM + store_r] = D_TYPE(coopmat_stage[warp_i * TM * TN + (col + store_c) * TM + store_r]);
-                    }
-                }
-            }
-        }
-    }
-#endif // MUL_MAT_ID
-#else
     [[unroll]] for (uint wsic = 0; wsic < WNITER; wsic++) {
         [[unroll]] for (uint wsir = 0; wsir < WMITER; wsir++) {
 
@@ -431,19 +283,21 @@ void main() {
                 const uint row_i = dc_warp + cc;
                 if (row_i >= _ne1) break;
 
-                const u16vec2 row_idx = row_ids[row_i];
+                const u16vec2 row_idx = row_ids[row_i - ic * BN];
 #endif // MUL_MAT_ID
                 [[unroll]] for (uint cr = 0; cr < TM; cr++) {
+                    const uint sums_idx = (wsic * TN + cc) * WMITER * TM + wsir * TM + cr;
 #ifdef MUL_MAT_ID
-                    data_d[row_idx.y * p.batch_stride_d + row_idx.x * p.stride_d + dr_warp + cr] = D_TYPE(sums[(wsic * TN + cc) * (WMITER * TM) + wsir * TM + cr]);
+                    if (dr_warp + cr < p.M) {
+                        data_d[row_idx.y * p.batch_stride_d + row_idx.x * p.stride_d + dr_warp + cr] = D_TYPE(sums[sums_idx].x);
+                    }
 #else
                     if (dr_warp + cr < p.M && dc_warp + cc < p.N) {
-                        data_d[offsets + (dc_warp + cc) * p.stride_d + dr_warp + cr] = D_TYPE(sums[(wsic * TN + cc) * (WMITER * TM) + wsir * TM + cr]);
+                        data_d[offsets + (dc_warp + cc) * p.stride_d + dr_warp + cr] = D_TYPE(sums[sums_idx].x);
                     }
 #endif // MUL_MAT_ID
                 }
             }
         }
     }
-#endif // COOPMAT
 }
diff --git a/ml/backend/ggml/ggml/src/ggml-vulkan/vulkan-shaders/mul_mmq_funcs.glsl b/ml/backend/ggml/ggml/src/ggml-vulkan/vulkan-shaders/mul_mmq_funcs.glsl
index fe71eb13..c0c03fed 100644
--- a/ml/backend/ggml/ggml/src/ggml-vulkan/vulkan-shaders/mul_mmq_funcs.glsl
+++ b/ml/backend/ggml/ggml/src/ggml-vulkan/vulkan-shaders/mul_mmq_funcs.glsl
@@ -6,41 +6,89 @@
 
 // Each iqs value maps to a 32-bit integer
 
-#if defined(DATA_A_Q4_0)
+#if defined(DATA_A_Q4_0) || defined(DATA_A_Q4_1)
+// 2-byte loads for Q4_0 blocks (18 bytes)
+// 4-byte loads for Q4_1 blocks (20 bytes)
 i32vec2 repack(uint ib, uint iqs) {
-    // Use 2-byte loads since a q4_0 block (18 bytes) is not divisible by 4
-    const u16vec2 quants = u16vec2(data_a[ib].qs[iqs * 2    ],
-                                   data_a[ib].qs[iqs * 2 + 1]);
+#ifdef DATA_A_Q4_0
+    const u16vec2 quants = u16vec2(data_a_packed16[ib].qs[iqs * 2    ],
+                                   data_a_packed16[ib].qs[iqs * 2 + 1]);
     const uint32_t vui = pack32(quants);
     return i32vec2( vui       & 0x0F0F0F0F,
                    (vui >> 4) & 0x0F0F0F0F);
+#else // DATA_A_Q4_1
+    const uint32_t vui = data_a_packed32[ib].qs[iqs];
+    return i32vec2( vui       & 0x0F0F0F0F,
+                   (vui >> 4) & 0x0F0F0F0F);
+#endif
 }
 
+#ifdef DATA_A_Q4_0
 ACC_TYPE mul_q8_1(const int32_t q_sum, const float da, const vec2 dsb, const int32_t sum_divisor) {
     return ACC_TYPE(da * (float(q_sum) * dsb.x - (8 / sum_divisor) * dsb.y));
 }
-#endif
-
-#if defined(DATA_A_Q4_1)
-i32vec2 repack(uint ib, uint iqs) {
-    // Use 4-byte loads since a q4_1 block (20 bytes) is divisible by 4
-    const uint32_t vui = data_a_packed32[ib].qs[iqs];
-    return i32vec2( vui       & 0x0F0F0F0F,
-                   (vui >> 4) & 0x0F0F0F0F);
-}
-
+#else // DATA_A_Q4_1
 ACC_TYPE mul_q8_1(const int32_t q_sum, const vec2 dma, const vec2 dsb, const int32_t sum_divisor) {
     return ACC_TYPE(float(q_sum) * dma.x * dsb.x + dma.y * dsb.y / sum_divisor);
 }
 #endif
 
-#if defined(DATA_A_Q5_0)
+#ifdef MMQ_SHMEM
+void block_a_to_shmem(const uint buf_ib, const uint ib, const uint iqs) {
+#ifdef DATA_A_Q4_0
+    buf_a[buf_ib].qs[iqs] = pack32(u16vec2(data_a_packed16[ib].qs[iqs * 2],
+                                           data_a_packed16[ib].qs[iqs * 2 + 1]));
+
+    if (iqs == 0) {
+        buf_a[buf_ib].dm = FLOAT_TYPE(data_a_packed16[ib].d);
+    }
+#else // DATA_A_Q4_1
+    buf_a[buf_ib].qs[iqs] = data_a_packed32[ib].qs[iqs];
+
+    if (iqs == 0) {
+        buf_a[buf_ib].dm = FLOAT_TYPE_VEC2(data_a_packed32[ib].dm);
+    }
+#endif
+}
+
+void block_a_to_registers(const uint reg_ib, const uint buf_ib) {
+    cache_a[reg_ib].dm = buf_a[buf_ib].dm;
+
+    [[unroll]] for (uint iqs = 0; iqs < 4; iqs++) {
+        cache_a[reg_ib].qs[iqs] = buf_a[buf_ib].qs[iqs];
+    }
+}
+
+ACC_TYPE mmq_dot_product(const uint ib_a) {
+    int32_t q_sum = 0;
+    [[unroll]] for (uint iqs = 0; iqs < 4; iqs++) {
+        const uint32_t vui = cache_a[ib_a].qs[iqs];
+        const i32vec2 qs_a = i32vec2( vui       & 0x0F0F0F0F,
+                                     (vui >> 4) & 0x0F0F0F0F);
+
+        const int32_t qs_b0 = cache_b.qs[iqs];
+        const int32_t qs_b1 = cache_b.qs[iqs + 4];
+
+        q_sum += dotPacked4x8EXT(qs_a.x, qs_b0);
+        q_sum += dotPacked4x8EXT(qs_a.y, qs_b1);
+    }
+
+    return mul_q8_1(q_sum, cache_a[ib_a].dm, cache_b.ds, 1);
+}
+#endif // MMQ_SHMEM
+
+#elif defined(DATA_A_Q5_0) || defined(DATA_A_Q5_1)
+// 2-byte loads for Q5_0 blocks (22 bytes)
+// 4-byte loads for Q5_1 blocks (24 bytes)
 i32vec2 repack(uint ib, uint iqs) {
-    // Use 2-byte loads since a q5_0 block (22 bytes) is not divisible by 4
-    const u16vec2 quants = u16vec2(data_a[ib].qs[iqs * 2    ],
-                                   data_a[ib].qs[iqs * 2 + 1]);
+    const u16vec2 quants = u16vec2(data_a_packed16[ib].qs[iqs * 2    ],
+                                   data_a_packed16[ib].qs[iqs * 2 + 1]);
     const uint32_t vui = pack32(quants);
-    const int32_t qh = int32_t((uint32_t(data_a[ib].qh[1]) << 16 | data_a[ib].qh[0]) >> (4 * iqs));
+#ifdef DATA_A_Q5_0
+    const int32_t qh = int32_t((uint32_t(data_a_packed16[ib].qh[1]) << 16 | data_a_packed16[ib].qh[0]) >> (4 * iqs));
+#else // DATA_A_Q5_1
+    const int32_t qh = int32_t(data_a_packed32[ib].qh >> (4 * iqs));
+#endif
     const int32_t v0 = int32_t(vui & 0x0F0F0F0F)
                      | ((qh & 0xF) * 0x02040810) & 0x10101010; // (0,1,2,3) -> (4,12,20,28)
 
@@ -50,40 +98,457 @@ i32vec2 repack(uint ib, uint iqs) {
     return i32vec2(v0, v1);
 }
 
+#ifdef DATA_A_Q5_0
 ACC_TYPE mul_q8_1(const int32_t q_sum, const float da, const vec2 dsb, const int32_t sum_divisor) {
     return ACC_TYPE(da * (float(q_sum) * dsb.x - (16 / sum_divisor) * dsb.y));
 }
-#endif
-
-#if defined(DATA_A_Q5_1)
-i32vec2 repack(uint ib, uint iqs) {
-    // Use 4-byte loads since a q5_1 block (24 bytes) is divisible by 4
-    const uint32_t vui = data_a_packed32[ib].qs[iqs];
-    const int32_t qh = int32_t(data_a_packed32[ib].qh >> (4 * iqs));
-    const int32_t v0 = int32_t(vui & 0x0F0F0F0F)
-                     | ((qh & 0xF) * 0x02040810) & 0x10101010; // (0,1,2,3) -> (4,12,20,28)
-
-    const int32_t v1 = int32_t((vui >> 4) & 0x0F0F0F0F)
-                     | (((qh >> 16) & 0xF) * 0x02040810) & 0x10101010; // (16,17,18,19) -> (4,12,20,28)
-
-    return i32vec2(v0, v1);
-}
-
+#else // DATA_A_Q5_1
 ACC_TYPE mul_q8_1(const int32_t q_sum, const vec2 dma, const vec2 dsb, const int32_t sum_divisor) {
     return ACC_TYPE(float(q_sum) * dma.x * dsb.x + dma.y * dsb.y / sum_divisor);
 }
 #endif
 
+#ifdef MMQ_SHMEM
+void block_a_to_shmem(const uint buf_ib, const uint ib, const uint iqs) {
+#ifdef DATA_A_Q5_0
+    buf_a[buf_ib].qs[iqs] = pack32(u16vec2(data_a_packed16[ib].qs[iqs * 2],
+                                           data_a_packed16[ib].qs[iqs * 2 + 1]));
+
+    if (iqs == 0) {
+        buf_a[buf_ib].dm = FLOAT_TYPE(data_a_packed16[ib].d);
+        buf_a[buf_ib].qh = pack32(u16vec2(data_a_packed16[ib].qh[0], data_a_packed16[ib].qh[1]));
+    }
+#else // DATA_A_Q5_1
+    buf_a[buf_ib].qs[iqs] = data_a_packed32[ib].qs[iqs];
+
+    if (iqs == 0) {
+        buf_a[buf_ib].dm = FLOAT_TYPE_VEC2(data_a_packed32[ib].dm);
+        buf_a[buf_ib].qh = data_a_packed32[ib].qh;
+    }
+#endif
+}
+
+void block_a_to_registers(const uint reg_ib, const uint buf_ib) {
+    cache_a[reg_ib].dm = buf_a[buf_ib].dm;
+    cache_a[reg_ib].qh = buf_a[buf_ib].qh;
+
+    [[unroll]] for (uint iqs = 0; iqs < 4; iqs++) {
+        cache_a[reg_ib].qs[iqs] = buf_a[buf_ib].qs[iqs];
+    }
+}
+
+ACC_TYPE mmq_dot_product(const uint ib_a) {
+    int32_t q_sum = 0;
+    [[unroll]] for (uint iqs = 0; iqs < 4; iqs++) {
+        const uint32_t vui = cache_a[ib_a].qs[iqs];
+        const int32_t qh = int32_t(cache_a[ib_a].qh >> (4 * iqs));
+        const int32_t qs_a0 = int32_t(vui & 0x0F0F0F0F)
+                         | ((qh & 0xF) * 0x02040810) & 0x10101010; // (0,1,2,3) -> (4,12,20,28)
+        const int32_t qs_a1 = int32_t((vui >> 4) & 0x0F0F0F0F)
+                         | (((qh >> 16) & 0xF) * 0x02040810) & 0x10101010; // (16,17,18,19) -> (4,12,20,28)
+
+        const int32_t qs_b0 = cache_b.qs[iqs];
+        const int32_t qs_b1 = cache_b.qs[iqs + 4];
+
+        q_sum += dotPacked4x8EXT(qs_a0, qs_b0);
+        q_sum += dotPacked4x8EXT(qs_a1, qs_b1);
+    }
+
+    return mul_q8_1(q_sum, cache_a[ib_a].dm, cache_b.ds, 1);
+}
+#endif // MMQ_SHMEM
+#endif
+
 #if defined(DATA_A_Q8_0)
+// 2-byte loads for Q8_0 blocks (34 bytes)
 int32_t repack(uint ib, uint iqs) {
-    // Use 2-byte loads since a q8_0 block (34 bytes) is not divisible by 4
-    return pack32(i16vec2(data_a[ib].qs[iqs * 2    ],
-                          data_a[ib].qs[iqs * 2 + 1]));
+    return pack32(i16vec2(data_a_packed16[ib].qs[iqs * 2    ],
+                          data_a_packed16[ib].qs[iqs * 2 + 1]));
 }
 
 ACC_TYPE mul_q8_1(const int32_t q_sum, const float da, const vec2 dsb, const int32_t sum_divisor) {
     return ACC_TYPE(float(q_sum) * da * dsb.x);
 }
+
+#ifdef MMQ_SHMEM
+void block_a_to_shmem(const uint buf_ib, const uint ib, const uint iqs) {
+    buf_a[buf_ib].qs[iqs] = pack32(i16vec2(data_a_packed16[ib].qs[iqs * 2],
+                                           data_a_packed16[ib].qs[iqs * 2 + 1]));
+
+    if (iqs == 0) {
+        buf_a[buf_ib].dm = FLOAT_TYPE(data_a_packed16[ib].d);
+    }
+}
+
+void block_a_to_registers(const uint reg_ib, const uint buf_ib) {
+    cache_a[reg_ib].dm = buf_a[buf_ib].dm;
+
+    [[unroll]] for (uint iqs = 0; iqs < 8; iqs++) {
+        cache_a[reg_ib].qs[iqs] = buf_a[buf_ib].qs[iqs];
+    }
+}
+
+ACC_TYPE mmq_dot_product(const uint ib_a) {
+    int32_t q_sum = 0;
+    [[unroll]] for (uint iqs = 0; iqs < 8; iqs++) {
+        const int32_t qs_a = cache_a[ib_a].qs[iqs];
+        const int32_t qs_b = cache_b.qs[iqs];
+
+        q_sum += dotPacked4x8EXT(qs_a, qs_b);
+    }
+
+    return mul_q8_1(q_sum, cache_a[ib_a].dm, cache_b.ds, 1);
+}
+#endif // MMQ_SHMEM
+#endif
+
+#if defined(DATA_A_MXFP4)
+// 1-byte loads for mxfp4 blocks (17 bytes)
+i32vec2 repack(uint ib, uint iqs) {
+    const uint32_t quants = pack32(u8vec4(data_a[ib].qs[iqs * 4    ],
+                                          data_a[ib].qs[iqs * 4 + 1],
+                                          data_a[ib].qs[iqs * 4 + 2],
+                                          data_a[ib].qs[iqs * 4 + 3]));
+
+    return i32vec2( quants       & 0x0F0F0F0F,
+                   (quants >> 4) & 0x0F0F0F0F);
+}
+
+ACC_TYPE mul_q8_1(const int32_t q_sum, const float da, const vec2 dsb, const int32_t sum_divisor) {
+    return ACC_TYPE(da * dsb.x * float(q_sum));
+}
+
+#ifdef MMQ_SHMEM
+void block_a_to_shmem(const uint buf_ib, const uint ib, const uint iqs) {
+    const uint32_t qs = pack32(u8vec4(data_a[ib].qs[iqs * 4    ],
+                                      data_a[ib].qs[iqs * 4 + 1],
+                                      data_a[ib].qs[iqs * 4 + 2],
+                                      data_a[ib].qs[iqs * 4 + 3]));
+
+    const u8vec4 i_a0 = unpack8( qs       & 0x0F0F0F0F);
+    const u8vec4 i_a1 = unpack8((qs >> 4) & 0x0F0F0F0F);
+
+    buf_a[buf_ib].qs[iqs    ] = pack32(i8vec4(kvalues_mxfp4[i_a0.x], kvalues_mxfp4[i_a0.y], kvalues_mxfp4[i_a0.z], kvalues_mxfp4[i_a0.w]));
+    buf_a[buf_ib].qs[iqs + 4] = pack32(i8vec4(kvalues_mxfp4[i_a1.x], kvalues_mxfp4[i_a1.y], kvalues_mxfp4[i_a1.z], kvalues_mxfp4[i_a1.w]));
+
+    if (iqs == 0) {
+        buf_a[buf_ib].d = FLOAT_TYPE(e8m0_to_fp32(data_a[ib].e) * 0.5);
+    }
+}
+
+void block_a_to_registers(const uint reg_ib, const uint buf_ib) {
+    cache_a[reg_ib].d = buf_a[buf_ib].d;
+
+    [[unroll]] for (uint iqs = 0; iqs < 8; iqs++) {
+        cache_a[reg_ib].qs[iqs] = buf_a[buf_ib].qs[iqs];
+    }
+}
+
+ACC_TYPE mmq_dot_product(const uint ib_a) {
+    int32_t q_sum = 0;
+    [[unroll]] for (uint iqs = 0; iqs < 8; iqs++) {
+        const int32_t qs_a = cache_a[ib_a].qs[iqs];
+
+        q_sum += dotPacked4x8EXT(qs_a, cache_b.qs[iqs]);
+    }
+
+    return mul_q8_1(q_sum, cache_a[ib_a].d, cache_b.ds, 1);
+}
+#endif // MMQ_SHMEM
+#endif
+
+// For k-quants, ib and iqs still assume 32-wide blocks, but k-quants are 256-wide
+// iqs still refers to a 32-bit integer, meaning 0..7 for 32-wide quants
+#if defined(DATA_A_Q2_K)
+// 4-byte loads for Q2_K blocks (84 bytes)
+int32_t repack(uint ib, uint iqs) {
+    const uint ib_k = ib / 8;
+    const uint iqs_k = (ib % 8) * 8 + iqs;
+
+    const uint qs_idx = (iqs_k / 32) * 8 + (iqs_k % 8);
+    const uint qs_shift = ((iqs_k % 32) / 8) * 2;
+
+    return int32_t((data_a_packed32[ib_k].qs[qs_idx] >> qs_shift) & 0x03030303);
+}
+
+uint8_t get_scale(uint ib, uint iqs) {
+    const uint ib_k = ib / 8;
+    const uint iqs_k = (ib % 8) * 8 + iqs;
+
+    return data_a[ib_k].scales[iqs_k / 4];
+}
+
+ACC_TYPE mul_q8_1(const int32_t sum_d, const int32_t sum_m, const vec2 dma, const vec2 dsb, const int32_t sum_divisor) {
+    return ACC_TYPE(dsb.x * (dma.x * float(sum_d) - dma.y * float(sum_m)));
+}
+
+#ifdef MMQ_SHMEM
+void block_a_to_shmem(const uint buf_ib, const uint ib, const uint iqs) {
+    const uint ib_k = ib / 8;
+    const uint iqs_k = (ib % 8) * 8 + iqs * QUANT_R_MMQ;
+
+    const uint qs_idx = (iqs_k / 32) * 8 + (iqs_k % 8);
+    const uint qs_shift = ((iqs_k % 32) / 8) * 2;
+
+    // Repack 4x4 quants into one int
+    const uint32_t vals0 = (data_a_packed32[ib_k].qs[qs_idx    ] >> qs_shift) & 0x03030303;
+    const uint32_t vals1 = (data_a_packed32[ib_k].qs[qs_idx + 1] >> qs_shift) & 0x03030303;
+    const uint32_t vals2 = (data_a_packed32[ib_k].qs[qs_idx + 2] >> qs_shift) & 0x03030303;
+    const uint32_t vals3 = (data_a_packed32[ib_k].qs[qs_idx + 3] >> qs_shift) & 0x03030303;
+
+    buf_a[buf_ib].qs[iqs] = vals0 | (vals1 << 2) | (vals2 << 4) | (vals3 << 6);
+
+    if (iqs == 0) {
+        buf_a[buf_ib].dm = FLOAT_TYPE_VEC2(data_a_packed32[ib_k].dm);
+        buf_a[buf_ib].scales = unpack8(data_a_packed16[ib_k].scales[iqs_k / 8]);
+    }
+}
+
+void block_a_to_registers(const uint reg_ib, const uint buf_ib) {
+    cache_a[reg_ib].dm = buf_a[buf_ib].dm;
+    cache_a[reg_ib].scales = buf_a[buf_ib].scales;
+
+    [[unroll]] for (uint iqs = 0; iqs < 2; iqs++) {
+        cache_a[reg_ib].qs[iqs] = buf_a[buf_ib].qs[iqs];
+    }
+}
+
+ACC_TYPE mmq_dot_product(const uint ib_a) {
+    int32_t sum_d = 0;
+    int32_t sum_m = 0;
+
+    [[unroll]] for (uint iqs = 0; iqs < 8; iqs++) {
+        const uint8_t scale = cache_a[ib_a].scales[iqs / 4];
+        const int32_t scale_m = int32_t(scale >> 4) * 0x01010101; // Duplicate 8-bit value across 32-bits.
+        const int32_t qs_a = int32_t((cache_a[ib_a].qs[iqs / 4] >> ((iqs % 4) * 2)) & 0x03030303);
+
+        sum_d += dotPacked4x8EXT(qs_a, cache_b.qs[iqs]) * (scale & 0xF);
+        sum_m += dotPacked4x8EXT(scale_m, cache_b.qs[iqs]);
+    }
+
+    return mul_q8_1(sum_d, sum_m, cache_a[ib_a].dm, cache_b.ds, 1);
+}
+#endif // MMQ_SHMEM
+#endif
+
+#if defined(DATA_A_Q3_K)
+// 2-byte loads for Q3_K blocks (110 bytes)
+#ifdef MMQ_SHMEM
+void block_a_to_shmem(const uint buf_ib, const uint ib, const uint iqs) {
+    const uint ib_k = ib / 8;
+    const uint hm_idx = iqs * QUANT_R_MMQ;
+    const uint iqs_k = (ib % 8) * 8 + hm_idx;
+
+    const uint qs_idx = (iqs_k / 32) * 8 + (iqs_k % 8);
+    const uint qs_shift = ((iqs_k % 32) / 8) * 2;
+    const uint hm_shift = iqs_k / 8;
+
+    // Repack 2x4 quants into one int
+    // Add the 3rd bit instead of subtracting it to allow packing the quants
+    const i8vec2 vals00 = unpack8(int16_t((data_a_packed16[ib_k].qs[qs_idx * 2        ] >> qs_shift) & uint16_t(0x0303))) |
+                          unpack8(int16_t(((data_a_packed16[ib_k].hmask[hm_idx * 2    ] >> hm_shift) & uint16_t(0x0101)) << 2));
+    const i8vec2 vals01 = unpack8(int16_t((data_a_packed16[ib_k].qs[qs_idx * 2 + 1    ] >> qs_shift) & uint16_t(0x0303))) |
+                          unpack8(int16_t(((data_a_packed16[ib_k].hmask[hm_idx * 2 + 1] >> hm_shift) & uint16_t(0x0101)) << 2));
+    const i8vec2 vals10 = unpack8(int16_t((data_a_packed16[ib_k].qs[qs_idx * 2 + 2    ] >> qs_shift) & uint16_t(0x0303))) |
+                          unpack8(int16_t(((data_a_packed16[ib_k].hmask[hm_idx * 2 + 2] >> hm_shift) & uint16_t(0x0101)) << 2));
+    const i8vec2 vals11 = unpack8(int16_t((data_a_packed16[ib_k].qs[qs_idx * 2 + 3    ] >> qs_shift) & uint16_t(0x0303))) |
+                          unpack8(int16_t(((data_a_packed16[ib_k].hmask[hm_idx * 2 + 3] >> hm_shift) & uint16_t(0x0101)) << 2));
+    buf_a[buf_ib].qs[iqs] = pack32(u8vec4(vals00.x, vals00.y, vals01.x, vals01.y)) |
+                           (pack32(u8vec4(vals10.x, vals10.y, vals11.x, vals11.y)) << 4);
+
+    if (iqs == 0) {
+        const uint is = iqs_k / 4;
+        const i8vec2 scales = i8vec2(unpack8(((data_a_packed16[ib_k].scales[(is % 8      ) / 2] >> (4 * (is / 8))) & 0x0F0F) |
+                                            (((data_a_packed16[ib_k].scales[(8 + (is % 4)) / 2] >> (2 * (is / 4))) & 0x0303) << 4)));
+
+        buf_a[buf_ib].d_scales = FLOAT_TYPE(data_a_packed16[ib_k].d) * FLOAT_TYPE_VEC2(scales - 32);
+    }
+}
+
+void block_a_to_registers(const uint reg_ib, const uint buf_ib) {
+    cache_a[reg_ib].d_scales = buf_a[buf_ib].d_scales;
+
+    [[unroll]] for (uint iqs = 0; iqs < 4; iqs++) {
+        cache_a[reg_ib].qs[iqs] = buf_a[buf_ib].qs[iqs];
+    }
+}
+
+ACC_TYPE mmq_dot_product(const uint ib_a) {
+    float result = 0.0;
+    int32_t q_sum = 0;
+
+    [[unroll]] for (uint iqs = 0; iqs < 4; iqs++) {
+        // Subtract 4 from the quants to correct the 3rd bit offset
+        const int32_t qs_a = pack32(unpack8(int32_t((cache_a[ib_a].qs[iqs / 2] >> ((iqs % 2) * 4)) & 0x0F0F0F0F)) - int8_t(4));
+
+        q_sum += dotPacked4x8EXT(qs_a, cache_b.qs[iqs]);
+    }
+    result += float(cache_a[ib_a].d_scales[0]) * float(q_sum);
+    q_sum = 0;
+
+    [[unroll]] for (uint iqs = 4; iqs < 8; iqs++) {
+        const int32_t qs_a = pack32(unpack8(int32_t((cache_a[ib_a].qs[iqs / 2] >> ((iqs % 2) * 4)) & 0x0F0F0F0F)) - int8_t(4));
+
+        q_sum += dotPacked4x8EXT(qs_a, cache_b.qs[iqs]);
+    }
+    result += float(cache_a[ib_a].d_scales[1]) * float(q_sum);
+
+    return ACC_TYPE(cache_b.ds.x * result);
+}
+#endif // MMQ_SHMEM
+#endif
+
+#if defined(DATA_A_Q4_K) || defined(DATA_A_Q5_K)
+// 4-byte loads for Q4_K blocks (144 bytes) and Q5_K blocks (176 bytes)
+ACC_TYPE mul_q8_1(const int32_t q_sum, const vec2 dma, const vec2 dsb, const int32_t sum_divisor) {
+    return ACC_TYPE(dsb.x * dma.x * float(q_sum) - dma.y * dsb.y);
+}
+
+#ifdef MMQ_SHMEM
+void block_a_to_shmem(const uint buf_ib, const uint ib, const uint iqs) {
+    const uint ib_k = ib / 8;
+    const uint iqs_k = (ib % 8) * 8 + iqs * QUANT_R_MMQ;
+
+    const uint qs_idx = (iqs_k / 16) * 8 + (iqs_k % 8);
+    const uint qs_shift = ((iqs_k % 16) / 8) * 4;
+
+    // Repack 2x4 quants into one int
+#if defined(DATA_A_Q4_K)
+    const uint32_t vals0 = (data_a_packed32[ib_k].qs[qs_idx    ] >> qs_shift) & 0x0F0F0F0F;
+    const uint32_t vals1 = (data_a_packed32[ib_k].qs[qs_idx + 1] >> qs_shift) & 0x0F0F0F0F;
+
+    buf_a[buf_ib].qs[iqs] = vals0 | (vals1 << 4);
+#else // defined(DATA_A_Q5_K)
+    const uint qh_idx = iqs * QUANT_R_MMQ;
+    const uint qh_shift = iqs_k / 8;
+
+    buf_a[buf_ib].qs[iqs] = int32_t(((data_a_packed32[ib_k].qs[qs_idx] >> qs_shift) & 0x0F0F0F0F) |
+                                   (((data_a_packed32[ib_k].qh[qh_idx] >> qh_shift) & 0x01010101) << 4));
+#endif
+
+
+    if (iqs == 0) {
+        // Scale index
+        const uint is = iqs_k / 8;
+        u8vec2 scale_dm;
+        if (is < 4) {
+            scale_dm = u8vec2(data_a[ib_k].scales[is] & 0x3F, data_a[ib_k].scales[is + 4] & 0x3F);
+        } else {
+            scale_dm = u8vec2((data_a[ib_k].scales[is+4] & 0xF) | ((data_a[ib_k].scales[is-4] & 0xC0) >> 2),
+                              (data_a[ib_k].scales[is+4] >>  4) | ((data_a[ib_k].scales[is  ] & 0xC0) >> 2));
+        }
+
+        buf_a[buf_ib].dm = FLOAT_TYPE_VEC2(data_a_packed32[ib_k].dm) * FLOAT_TYPE_VEC2(scale_dm);
+    }
+}
+
+void block_a_to_registers(const uint reg_ib, const uint buf_ib) {
+    cache_a[reg_ib].dm = buf_a[buf_ib].dm;
+
+    [[unroll]] for (uint iqs = 0; iqs < 8 / QUANT_R_MMQ; iqs++) {
+        cache_a[reg_ib].qs[iqs] = buf_a[buf_ib].qs[iqs];
+    }
+}
+
+ACC_TYPE mmq_dot_product(const uint ib_a) {
+    int32_t q_sum = 0;
+
+    [[unroll]] for (uint iqs = 0; iqs < 8; iqs++) {
+#if defined(DATA_A_Q4_K)
+        const int32_t qs_a = int32_t((cache_a[ib_a].qs[iqs / 2] >> ((iqs % 2) * 4)) & 0x0F0F0F0F);
+#else // defined(DATA_A_Q5_K)
+        const int32_t qs_a = cache_a[ib_a].qs[iqs];
+#endif
+
+        q_sum += dotPacked4x8EXT(qs_a, cache_b.qs[iqs]);
+    }
+
+    return mul_q8_1(q_sum, cache_a[ib_a].dm, cache_b.ds, 1);
+}
+#endif // MMQ_SHMEM
+#endif
+
+#ifdef MMQ_SHMEM
+void block_b_to_shmem(const uint buf_ib, const uint ib, const uint iqs) {
+    const uint ib_outer = ib / 4;
+    const uint ib_inner = ib % 4;
+
+    if (iqs == 0) {
+        buf_b[buf_ib].ds = FLOAT_TYPE_VEC2(data_b[ib_outer].ds[ib_inner]);
+    }
+
+    const ivec4 values = data_b[ib_outer].qs[ib_inner * 2 + iqs];
+    buf_b[buf_ib].qs[iqs * 4    ] = values.x;
+    buf_b[buf_ib].qs[iqs * 4 + 1] = values.y;
+    buf_b[buf_ib].qs[iqs * 4 + 2] = values.z;
+    buf_b[buf_ib].qs[iqs * 4 + 3] = values.w;
+}
+
+void block_b_to_registers(const uint ib) {
+    cache_b.ds = buf_b[ib].ds;
+    [[unroll]] for (uint iqs = 0; iqs < BK / 4; iqs++) {
+        cache_b.qs[iqs] = buf_b[ib].qs[iqs];
+    }
+}
+#endif
+
+#if defined(DATA_A_Q6_K)
+// 2-byte loads for Q6_K blocks (210 bytes)
+#ifdef MMQ_SHMEM
+void block_a_to_shmem(const uint buf_ib, const uint ib, const uint iqs) {
+    const uint ib_k = ib / 8;
+    const uint iqs_k = (ib % 8) * 8 + iqs;
+
+    const uint ql_idx = (iqs_k / 32) * 16 + iqs_k % 16;
+    const uint ql_shift = ((iqs_k % 32) / 16) * 4;
+
+    const uint qh_idx = (iqs_k / 32) * 8 + iqs;
+    const uint qh_shift = ((iqs_k % 32) / 8) * 2;
+
+    const i8vec2 vals00 = (unpack8(int16_t((data_a_packed16[ib_k].ql[ql_idx * 2    ] >> ql_shift) & uint16_t(0x0F0F))) |
+                          unpack8(int16_t(((data_a_packed16[ib_k].qh[qh_idx * 2    ] >> qh_shift) & uint16_t(0x0303)) << 4))) - int8_t(32);
+    const i8vec2 vals01 = (unpack8(int16_t((data_a_packed16[ib_k].ql[ql_idx * 2 + 1] >> ql_shift) & uint16_t(0x0F0F))) |
+                          unpack8(int16_t(((data_a_packed16[ib_k].qh[qh_idx * 2 + 1] >> qh_shift) & uint16_t(0x0303)) << 4))) - int8_t(32);
+    buf_a[buf_ib].qs[iqs] = pack32(i8vec4(vals00.x, vals00.y, vals01.x, vals01.y));
+
+    if (iqs == 0) {
+        const uint is = iqs_k / 4;
+        const i8vec2 scales = unpack8(data_a_packed16[ib_k].scales[is / 2]);
+
+        buf_a[buf_ib].d_scales = FLOAT_TYPE(data_a_packed16[ib_k].d) * FLOAT_TYPE_VEC2(scales);
+    }
+}
+
+void block_a_to_registers(const uint reg_ib, const uint buf_ib) {
+    cache_a[reg_ib].d_scales = buf_a[buf_ib].d_scales;
+
+    [[unroll]] for (uint iqs = 0; iqs < 8; iqs++) {
+        cache_a[reg_ib].qs[iqs] = buf_a[buf_ib].qs[iqs];
+    }
+}
+
+ACC_TYPE mmq_dot_product(const uint ib_a) {
+    float result = 0.0;
+    int32_t q_sum = 0;
+
+    [[unroll]] for (uint iqs = 0; iqs < 4; iqs++) {
+        const int32_t qs_a = cache_a[ib_a].qs[iqs];
+
+        q_sum += dotPacked4x8EXT(qs_a, cache_b.qs[iqs]);
+    }
+    result += float(cache_a[ib_a].d_scales[0]) * float(q_sum);
+    q_sum = 0;
+
+    [[unroll]] for (uint iqs = 4; iqs < 8; iqs++) {
+        const int32_t qs_a = cache_a[ib_a].qs[iqs];
+
+        q_sum += dotPacked4x8EXT(qs_a, cache_b.qs[iqs]);
+    }
+    result += float(cache_a[ib_a].d_scales[1]) * float(q_sum);
+
+    return ACC_TYPE(cache_b.ds.x * result);
+}
+#endif // MMQ_SHMEM
 #endif
 
 #if defined(DATA_A_Q4_0) || defined(DATA_A_Q5_0) || defined(DATA_A_Q8_0) || defined(DATA_A_IQ1_S) || defined(DATA_A_IQ2_XXS) || defined(DATA_A_IQ2_XS) || defined(DATA_A_IQ2_S) || defined(DATA_A_IQ3_XXS) || defined(DATA_A_IQ3_S) || defined(DATA_A_IQ4_XS) || defined(DATA_A_IQ4_NL)
@@ -103,3 +568,10 @@ FLOAT_TYPE_VEC2 get_dm(uint ib) {
     return FLOAT_TYPE_VEC2(data_a_packed32[ib].dm);
 }
 #endif
+
+#if defined(DATA_A_Q2_K)
+FLOAT_TYPE_VEC2 get_dm(uint ib) {
+    const uint ib_k = ib / 8;
+    return FLOAT_TYPE_VEC2(data_a_packed32[ib_k].dm);
+}
+#endif
diff --git a/ml/backend/ggml/ggml/src/ggml-vulkan/vulkan-shaders/mul_mmq_shmem_types.glsl b/ml/backend/ggml/ggml/src/ggml-vulkan/vulkan-shaders/mul_mmq_shmem_types.glsl
new file mode 100644
index 00000000..1c0f5306
--- /dev/null
+++ b/ml/backend/ggml/ggml/src/ggml-vulkan/vulkan-shaders/mul_mmq_shmem_types.glsl
@@ -0,0 +1,78 @@
+#if defined(DATA_A_Q4_0)
+#define QUANT_R_MMQ 2
+struct block_a_cache {
+    uint32_t qs[16/4];
+    FLOAT_TYPE dm;
+};
+#elif defined(DATA_A_Q4_1)
+#define QUANT_R_MMQ 2
+struct block_a_cache {
+    uint32_t qs[16/4];
+    FLOAT_TYPE_VEC2 dm;
+};
+#elif defined(DATA_A_Q5_0)
+#define QUANT_R_MMQ 2
+struct block_a_cache {
+    uint32_t qs[16/4];
+    uint32_t qh;
+    FLOAT_TYPE dm;
+};
+#elif defined(DATA_A_Q5_1)
+#define QUANT_R_MMQ 2
+struct block_a_cache {
+    uint32_t qs[16/4];
+    uint32_t qh;
+    FLOAT_TYPE_VEC2 dm;
+};
+#elif defined(DATA_A_Q8_0)
+#define QUANT_R_MMQ 1
+// AMD likes 4, Intel likes 1 and Nvidia likes 2
+// #define BK_STEP 1
+struct block_a_cache {
+    int32_t qs[32/4];
+    FLOAT_TYPE dm;
+};
+#elif defined(DATA_A_MXFP4)
+#define QUANT_R_MMQ 2
+struct block_a_cache {
+    int32_t qs[8];
+    FLOAT_TYPE d;
+};
+#elif defined(DATA_A_Q2_K)
+#define QUANT_R_MMQ 4
+struct block_a_cache {
+    uint32_t qs[2];
+    u8vec2 scales;
+    FLOAT_TYPE_VEC2 dm;
+};
+#elif defined(DATA_A_Q3_K)
+#define QUANT_R_MMQ 2
+struct block_a_cache {
+    uint32_t qs[4];
+    FLOAT_TYPE_VEC2 d_scales;
+};
+#elif defined(DATA_A_Q4_K)
+#define QUANT_R_MMQ 2
+struct block_a_cache {
+    uint32_t qs[4];
+    FLOAT_TYPE_VEC2 dm;
+};
+#elif defined(DATA_A_Q5_K)
+#define QUANT_R_MMQ 1
+struct block_a_cache {
+    int32_t qs[8];
+    FLOAT_TYPE_VEC2 dm;
+};
+#elif defined(DATA_A_Q6_K)
+#define QUANT_R_MMQ 1
+struct block_a_cache {
+    int32_t qs[8];
+    FLOAT_TYPE_VEC2 d_scales;
+};
+#endif
+
+struct block_b_cache
+{
+    int32_t qs[8];
+    FLOAT_TYPE_VEC2 ds;
+};
diff --git a/ml/backend/ggml/ggml/src/ggml-vulkan/vulkan-shaders/rope_head.glsl b/ml/backend/ggml/ggml/src/ggml-vulkan/vulkan-shaders/rope_head.glsl
index 50fc1f1e..0eda186c 100644
--- a/ml/backend/ggml/ggml/src/ggml-vulkan/vulkan-shaders/rope_head.glsl
+++ b/ml/backend/ggml/ggml/src/ggml-vulkan/vulkan-shaders/rope_head.glsl
@@ -10,6 +10,7 @@ layout (binding = 0) readonly buffer X {A_TYPE data_a[];};
 layout (binding = 1) readonly buffer Y {int data_pos[];};
 layout (binding = 2) readonly buffer Z {float data_ff[];};
 layout (binding = 3) writeonly buffer D {D_TYPE data_d[];};
+layout (binding = 4) readonly buffer I {uvec2 data_i[];}; // indices for set_rows
 
 layout (push_constant) uniform parameter {
     uint ncols;
@@ -27,6 +28,7 @@ layout (push_constant) uniform parameter {
     uint s2;
     int sections[4];
     uint is_back;
+    uint set_rows_stride;
 } p;
 
 float rope_yarn_ramp(const float low, const float high, const uint i0) {
diff --git a/ml/backend/ggml/ggml/src/ggml-vulkan/vulkan-shaders/rope_neox.comp b/ml/backend/ggml/ggml/src/ggml-vulkan/vulkan-shaders/rope_neox.comp
index 06e095be..9f453815 100644
--- a/ml/backend/ggml/ggml/src/ggml-vulkan/vulkan-shaders/rope_neox.comp
+++ b/ml/backend/ggml/ggml/src/ggml-vulkan/vulkan-shaders/rope_neox.comp
@@ -16,12 +16,19 @@ void main() {
     const uint row_x     = row_dst % ne1;
     const uint channel_x = row_dst / ne1;
 
-    const uint idst = row_dst*ne0 + i0/2;
+    uint idst = row_dst*ne0 + i0/2;
     const uint ix   = channel_x*p.s2 + row_x*p.s1 + i0/2;
 
+    // Fusion optimization: ROPE + VIEW + SET_ROWS..
+    // The rope output is viewed as a 1D tensor and offset based on a row index in data_i.
+    if (p.set_rows_stride != 0) {
+        idst = row_x*ne0 + i0/2;
+        idst += data_i[channel_x].x * p.set_rows_stride;
+    }
+
     if (i0 >= p.n_dims) {
-        data_d[idst + i0/2 + 0] = data_a[ix + i0/2 + 0];
-        data_d[idst + i0/2 + 1] = data_a[ix + i0/2 + 1];
+        data_d[idst + i0/2 + 0] = D_TYPE(data_a[ix + i0/2 + 0]);
+        data_d[idst + i0/2 + 1] = D_TYPE(data_a[ix + i0/2 + 1]);
 
         return;
     }
diff --git a/ml/backend/ggml/ggml/src/ggml-vulkan/vulkan-shaders/rope_norm.comp b/ml/backend/ggml/ggml/src/ggml-vulkan/vulkan-shaders/rope_norm.comp
index 6ba95754..f4209ed9 100644
--- a/ml/backend/ggml/ggml/src/ggml-vulkan/vulkan-shaders/rope_norm.comp
+++ b/ml/backend/ggml/ggml/src/ggml-vulkan/vulkan-shaders/rope_norm.comp
@@ -16,12 +16,19 @@ void main() {
     const uint row_x     = row_dst % ne1;
     const uint channel_x = row_dst / ne1;
 
-    const uint idst = row_dst*ne0 + i0;
+    uint idst = row_dst*ne0 + i0;
     const uint ix   = channel_x*p.s2 + row_x*p.s1 + i0;
 
+    // Fusion optimization: ROPE + VIEW + SET_ROWS..
+    // The rope output is viewed as a 1D tensor and offset based on a row index in data_i.
+    if (p.set_rows_stride != 0) {
+        idst = row_x*ne0 + i0;
+        idst += data_i[channel_x].x * p.set_rows_stride;
+    }
+
     if (i0 >= p.n_dims) {
-        data_d[idst + 0] = data_a[ix + 0];
-        data_d[idst + 1] = data_a[ix + 1];
+        data_d[idst + 0] = D_TYPE(data_a[ix + 0]);
+        data_d[idst + 1] = D_TYPE(data_a[ix + 1]);
 
         return;
     }
diff --git a/ml/backend/ggml/ggml/src/ggml-vulkan/vulkan-shaders/topk_moe.comp b/ml/backend/ggml/ggml/src/ggml-vulkan/vulkan-shaders/topk_moe.comp
index 9e56d5f8..bc1c278b 100644
--- a/ml/backend/ggml/ggml/src/ggml-vulkan/vulkan-shaders/topk_moe.comp
+++ b/ml/backend/ggml/ggml/src/ggml-vulkan/vulkan-shaders/topk_moe.comp
@@ -11,6 +11,8 @@ layout (push_constant) uniform parameter
 {
     uint n_rows;
     uint n_expert_used;
+    float clamp_min;
+    float clamp_max;
 };
 
 layout(local_size_x_id = 0, local_size_y = 4, local_size_z = 1) in;
@@ -18,6 +20,7 @@ layout(local_size_x_id = 0, local_size_y = 4, local_size_z = 1) in;
 layout(constant_id = 0) const uint WARP_SIZE = 32;
 layout(constant_id = 1) const uint n_experts = 512;
 layout(constant_id = 2) const bool with_norm = true;
+layout(constant_id = 3) const bool late_softmax = false;
 
 const uint experts_per_thread = (n_experts > WARP_SIZE) ? n_experts / WARP_SIZE : 1;
 
@@ -25,6 +28,52 @@ layout (binding = 0, std430) readonly buffer Logits {float logits[];};
 layout (binding = 1, std430) writeonly buffer Weights {float weights[];};
 layout (binding = 2, std430) writeonly buffer Ids {uint ids[];};
 
+const float INFINITY = 1.0 / 0.0;
+
+// Warp-local softmax used for both the pre-top-k logits and the post-top-k delayed path.
+void softmax_warp_inplace(inout float vals[experts_per_thread], const uint limit, const uint lane, const bool use_limit) {
+    float max_val = -INFINITY;
+
+    [[unroll]]
+    for (int i = 0; i < experts_per_thread; i++) {
+        const uint idx       = lane + i * WARP_SIZE;
+        const bool is_active = !use_limit || (idx < limit);
+        if (is_active) {
+            max_val = max(max_val, vals[i]);
+        }
+    }
+
+    max_val = subgroupMax(max_val);
+
+    float sum = 0.f;
+
+    [[unroll]]
+    for (int i = 0; i < experts_per_thread; i++) {
+        const uint idx       = lane + i * WARP_SIZE;
+        const bool is_active = !use_limit || (idx < limit);
+        if (is_active) {
+            const float val = exp(vals[i] - max_val);
+            vals[i]         = val;
+            sum += val;
+        } else {
+            vals[i] = 0.f;
+        }
+    }
+
+    sum = subgroupAdd(sum);
+
+    const float inv_sum = 1.0f / sum;
+
+    [[unroll]]
+    for (int i = 0; i < experts_per_thread; i++) {
+        const uint idx       = lane + i * WARP_SIZE;
+        const bool is_active = !use_limit || (idx < limit);
+        if (is_active) {
+            vals[i] *= inv_sum;
+        }
+    }
+}
+
 void main() {
     const uint row = gl_WorkGroupID.x * gl_WorkGroupSize.y + gl_LocalInvocationID.y;
     if (row >= n_rows) {
@@ -35,43 +84,16 @@ void main() {
     const uint weights_offset = n_expert_used * row;
     const uint ids_offset = n_experts * row;
 
-    float logits_r[experts_per_thread];
-
-    const float INFINITY = 1.0 / 0.0;
+    float wt[experts_per_thread];
 
     [[unroll]]
     for (uint i = 0; i < n_experts; i += WARP_SIZE) {
-        const uint expert        = i + gl_LocalInvocationID.x;
-        logits_r[i / WARP_SIZE] = n_experts % WARP_SIZE == 0 || expert < n_experts ? logits[logits_offset + expert] : -INFINITY;
+        const uint expert = i + gl_LocalInvocationID.x;
+        wt[i / WARP_SIZE] = (n_experts % WARP_SIZE == 0 || expert < n_experts) ? logits[logits_offset + expert] : -INFINITY;
     }
 
-    float max_val = logits_r[0];
-
-    [[unroll]]
-    for (int i = 1; i < experts_per_thread; i++) {
-        const float val = logits_r[i];
-        max_val         = max(val, max_val);
-    }
-
-    max_val = subgroupMax(max_val);
-
-    float wt[experts_per_thread];
-    float tmp = 0.f;
-
-    [[unroll]]
-    for (int i = 0; i < experts_per_thread; i++) {
-        const float val = logits_r[i];
-        wt[i]           = exp(val - max_val);
-        tmp += wt[i];
-    }
-
-    tmp = subgroupAdd(tmp);
-
-    const float inv_sum = 1.0f / tmp;
-
-    [[unroll]]
-    for (int i = 0; i < experts_per_thread; i++) {
-        wt[i] = wt[i] * inv_sum;
+    if (!late_softmax) {
+        softmax_warp_inplace(wt, n_experts, gl_LocalInvocationID.x, false);
     }
 
     // at this point, each thread holds a portion of softmax,
@@ -82,6 +104,11 @@ void main() {
 
     float output_weights[experts_per_thread];
 
+    [[unroll]]
+    for (int i = 0; i < experts_per_thread; i++) {
+        output_weights[i] = 0.f;
+    }
+
     for (int k = 0; k < n_expert_used; k++) {
         float max_val    = wt[0];
         uint   max_expert = gl_LocalInvocationID.x;
@@ -121,6 +148,7 @@ void main() {
 
     if (with_norm) {
         wt_sum              = subgroupAdd(wt_sum);
+        wt_sum              = clamp(wt_sum, clamp_min, clamp_max);
         const float inv_sum = 1.0f / wt_sum;
 
         [[unroll]]
@@ -129,6 +157,10 @@ void main() {
         }
     }
 
+    if (late_softmax) {
+        softmax_warp_inplace(output_weights, n_expert_used, gl_LocalInvocationID.x, true);
+    }
+
     [[unroll]]
     for (uint i = 0; i < experts_per_thread; ++i) {
         uint idx = i * WARP_SIZE + gl_LocalInvocationID.x;
diff --git a/ml/backend/ggml/ggml/src/ggml-vulkan/vulkan-shaders/types.glsl b/ml/backend/ggml/ggml/src/ggml-vulkan/vulkan-shaders/types.glsl
index 2fa54ce5..02578c77 100644
--- a/ml/backend/ggml/ggml/src/ggml-vulkan/vulkan-shaders/types.glsl
+++ b/ml/backend/ggml/ggml/src/ggml-vulkan/vulkan-shaders/types.glsl
@@ -66,6 +66,7 @@ struct block_q4_0_packed16
 #define QUANT_AUXF 1
 #define A_TYPE block_q4_0
 #define A_TYPE_PACKED16 block_q4_0_packed16
+#define DATA_A_QUANT_LEGACY
 #endif
 
 #define QUANT_K_Q4_1 32
@@ -98,6 +99,7 @@ struct block_q4_1_packed32
 #define A_TYPE block_q4_1
 #define A_TYPE_PACKED16 block_q4_1_packed16
 #define A_TYPE_PACKED32 block_q4_1_packed32
+#define DATA_A_QUANT_LEGACY
 #endif
 
 #define QUANT_K_Q5_0 32
@@ -123,6 +125,7 @@ struct block_q5_0_packed16
 #define QUANT_AUXF 1
 #define A_TYPE block_q5_0
 #define A_TYPE_PACKED16 block_q5_0_packed16
+#define DATA_A_QUANT_LEGACY
 #endif
 
 #define QUANT_K_Q5_1 32
@@ -158,6 +161,7 @@ struct block_q5_1_packed32
 #define A_TYPE block_q5_1
 #define A_TYPE_PACKED16 block_q5_1_packed16
 #define A_TYPE_PACKED32 block_q5_1_packed32
+#define DATA_A_QUANT_LEGACY
 #endif
 
 #define QUANT_K_Q8_0 32
@@ -186,6 +190,7 @@ struct block_q8_0_packed32
 #define A_TYPE block_q8_0
 #define A_TYPE_PACKED16 block_q8_0_packed16
 #define A_TYPE_PACKED32 block_q8_0_packed32
+#define DATA_A_QUANT_LEGACY
 #endif
 
 #define QUANT_K_Q8_1 32
@@ -226,21 +231,21 @@ struct block_q2_K
 {
     uint8_t scales[QUANT_K_Q2_K/16];
     uint8_t qs[QUANT_K_Q2_K/4];
-    f16vec2 d;
+    f16vec2 dm;
 };
 
 struct block_q2_K_packed16
 {
     uint16_t scales[QUANT_K_Q2_K/16/2];
     uint16_t qs[QUANT_K_Q2_K/4/2];
-    f16vec2 d;
+    f16vec2 dm;
 };
 
 struct block_q2_K_packed32
 {
     uint32_t scales[QUANT_K_Q2_K/16/4];
     uint32_t qs[QUANT_K_Q2_K/4/4];
-    f16vec2 d;
+    f16vec2 dm;
 };
 
 #if defined(DATA_A_Q2_K)
@@ -249,6 +254,8 @@ struct block_q2_K_packed32
 #define A_TYPE block_q2_K
 #define A_TYPE_PACKED16 block_q2_K_packed16
 #define A_TYPE_PACKED32 block_q2_K_packed32
+#define SCALES_PER_32 2
+#define DATA_A_QUANT_K
 #endif
 
 #define QUANT_K_Q3_K 256
@@ -274,27 +281,28 @@ struct block_q3_K_packed16
 #define QUANT_R 1
 #define A_TYPE block_q3_K
 #define A_TYPE_PACKED16 block_q3_K_packed16
+#define DATA_A_QUANT_K
 #endif
 
 #define QUANT_K_Q4_K 256
 
 struct block_q4_K
 {
-    f16vec2 d;
+    f16vec2 dm;
     uint8_t scales[3*QUANT_K_Q4_K/64];
     uint8_t qs[QUANT_K_Q4_K/2];
 };
 
 struct block_q4_K_packed16
 {
-    f16vec2 d;
+    f16vec2 dm;
     uint16_t scales[3*QUANT_K_Q4_K/64/2];
     uint16_t qs[QUANT_K_Q4_K/2/2];
 };
 
 struct block_q4_K_packed32
 {
-    f16vec2 d;
+    f16vec2 dm;
     uint32_t scales[3*QUANT_K_Q4_K/64/4];
     uint32_t qs[QUANT_K_Q4_K/2/4];
 };
@@ -310,13 +318,14 @@ struct block_q4_K_packed128
 #define A_TYPE block_q4_K
 #define A_TYPE_PACKED16 block_q4_K_packed16
 #define A_TYPE_PACKED32 block_q4_K_packed32
+#define DATA_A_QUANT_K
 #endif
 
 #define QUANT_K_Q5_K 256
 
 struct block_q5_K
 {
-    f16vec2 d;
+    f16vec2 dm;
     uint8_t scales[12];
     uint8_t qh[QUANT_K_Q5_K/8];
     uint8_t qs[QUANT_K_Q5_K/2];
@@ -324,12 +333,20 @@ struct block_q5_K
 
 struct block_q5_K_packed16
 {
-    f16vec2 d;
+    f16vec2 dm;
     uint16_t scales[12/2];
     uint16_t qh[QUANT_K_Q5_K/8/2];
     uint16_t qs[QUANT_K_Q5_K/2/2];
 };
 
+struct block_q5_K_packed32
+{
+    f16vec2 dm;
+    uint32_t scales[12/4];
+    uint32_t qh[QUANT_K_Q5_K/8/4];
+    uint32_t qs[QUANT_K_Q5_K/2/4];
+};
+
 struct block_q5_K_packed128
 {
     uvec4 q5k[11];
@@ -340,6 +357,8 @@ struct block_q5_K_packed128
 #define QUANT_R 1
 #define A_TYPE block_q5_K
 #define A_TYPE_PACKED16 block_q5_K_packed16
+#define A_TYPE_PACKED32 block_q5_K_packed32
+#define DATA_A_QUANT_K
 #endif
 
 #define QUANT_K_Q6_K 256
@@ -356,7 +375,7 @@ struct block_q6_K_packed16
 {
     uint16_t ql[QUANT_K_Q6_K/2/2];
     uint16_t qh[QUANT_K_Q6_K/4/2];
-    int8_t scales[QUANT_K_Q6_K/16];
+    int16_t scales[QUANT_K_Q6_K/16/2];
     float16_t d;
 };
 
@@ -365,6 +384,7 @@ struct block_q6_K_packed16
 #define QUANT_R 1
 #define A_TYPE block_q6_K
 #define A_TYPE_PACKED16 block_q6_K_packed16
+#define DATA_A_QUANT_K
 #endif
 
 // IQuants
@@ -1363,18 +1383,11 @@ struct block_mxfp4
     uint8_t qs[QUANT_K_MXFP4/2];
 };
 
-//struct block_mxfp4_packed16
-//{
-//    uint8_t e;
-//    uint16_t qs[QUANT_K_MXFP4/2/2];
-//};
-
 #if defined(DATA_A_MXFP4)
 #define QUANT_K QUANT_K_MXFP4
 #define QUANT_R QUANT_R_MXFP4
 #define QUANT_AUXF 1
 #define A_TYPE block_mxfp4
-//#define A_TYPE_PACKED16 block_mxfp4_packed16
 #endif
 
 #if defined(DATA_A_IQ4_NL) || defined(DATA_A_IQ4_XS)
@@ -1397,12 +1410,12 @@ void init_iq_shmem(uvec3 wgsize)
 #endif
 
 #if defined(DATA_A_MXFP4)
-const FLOAT_TYPE kvalues_mxfp4_const[16] = {
-    FLOAT_TYPE(0.0f), FLOAT_TYPE(0.5f), FLOAT_TYPE(1.0f), FLOAT_TYPE(1.5f), FLOAT_TYPE(2.0f), FLOAT_TYPE(3.0f), FLOAT_TYPE(4.0f), FLOAT_TYPE(6.0f),
-    FLOAT_TYPE(-0.0f), FLOAT_TYPE(-0.5f), FLOAT_TYPE(-1.0f), FLOAT_TYPE(-1.5f), FLOAT_TYPE(-2.0f), FLOAT_TYPE(-3.0f), FLOAT_TYPE(-4.0f), FLOAT_TYPE(-6.0f)
+const int8_t kvalues_mxfp4_const[16] = {
+    int8_t(0), int8_t(1), int8_t(2), int8_t(3), int8_t(4), int8_t(6), int8_t(8), int8_t(12),
+    int8_t(0), int8_t(-1), int8_t(-2), int8_t(-3), int8_t(-4), int8_t(-6), int8_t(-8), int8_t(-12),
 };
 
-shared FLOAT_TYPE kvalues_mxfp4[16];
+shared int8_t kvalues_mxfp4[16];
 
 #define NEEDS_INIT_IQ_SHMEM
 void init_iq_shmem(uvec3 wgsize)
diff --git a/ml/backend/ggml/ggml/src/ggml-vulkan/vulkan-shaders/vulkan-shaders-gen.cpp b/ml/backend/ggml/ggml/src/ggml-vulkan/vulkan-shaders/vulkan-shaders-gen.cpp
index 0f25ba34..e6ec589f 100644
--- a/ml/backend/ggml/ggml/src/ggml-vulkan/vulkan-shaders/vulkan-shaders-gen.cpp
+++ b/ml/backend/ggml/ggml/src/ggml-vulkan/vulkan-shaders/vulkan-shaders-gen.cpp
@@ -566,7 +566,8 @@ void matmul_shaders(bool fp16, MatMulIdType matmul_id_type, bool coopmat, bool c
         }
 
 #if defined(GGML_VULKAN_INTEGER_DOT_GLSLC_SUPPORT)
-        if (!coopmat && !coopmat2 && matmul_id_type == MatMulIdType::NONE && is_legacy_quant(tname)) {
+        // Integer dot mmq performs better with f32 accumulators
+        if (!f16acc && !coopmat && !coopmat2 && (is_legacy_quant(tname) || is_k_quant(tname) || tname == "mxfp4")) {
             string_to_spv(shader_name + "_" + tname + "_q8_1", "mul_mmq.comp", merge_maps(merge_maps(base_dict, float_type_dict), {{data_a_key, "1"}, {"D_TYPE", "float"},}), fp16, coopmat, coopmat2, f16acc);
         }
 #endif
@@ -574,7 +575,7 @@ void matmul_shaders(bool fp16, MatMulIdType matmul_id_type, bool coopmat, bool c
 }
 
 void process_shaders() {
-    std::map<std::string, std::string> base_dict = {{"FLOAT_TYPE", "float"}};
+    std::map<std::string, std::string> base_dict = {{"FLOAT_TYPE", "float"}, {"FLOAT_TYPE_VEC2", "vec2"}};
 
     // matmul
     for (const MatMulIdType& matmul_id_type : {MatMulIdType::NONE, MatMulIdType::DEFAULT, MatMulIdType::SUBGROUP}) {
@@ -841,10 +842,14 @@ void process_shaders() {
     string_to_spv("rope_norm_f32", "rope_norm.comp", {{"A_TYPE", "float"}, {"D_TYPE", "float"}});
     string_to_spv("rope_norm_f16", "rope_norm.comp", {{"A_TYPE", "float16_t"}, {"D_TYPE", "float16_t"}});
     string_to_spv("rope_norm_f16_rte", "rope_norm.comp", {{"A_TYPE", "float16_t"}, {"D_TYPE", "float16_t"}, {"RTE16", "1"}});
+    string_to_spv("rope_norm_f32_f16", "rope_norm.comp", {{"A_TYPE", "float"}, {"D_TYPE", "float16_t"}});
+    string_to_spv("rope_norm_f32_f16_rte", "rope_norm.comp", {{"A_TYPE", "float"}, {"D_TYPE", "float16_t"}, {"RTE16", "1"}});
 
     string_to_spv("rope_neox_f32", "rope_neox.comp", {{"A_TYPE", "float"}, {"D_TYPE", "float"}});
     string_to_spv("rope_neox_f16", "rope_neox.comp", {{"A_TYPE", "float16_t"}, {"D_TYPE", "float16_t"}});
     string_to_spv("rope_neox_f16_rte", "rope_neox.comp", {{"A_TYPE", "float16_t"}, {"D_TYPE", "float16_t"}, {"RTE16", "1"}});
+    string_to_spv("rope_neox_f32_f16", "rope_neox.comp", {{"A_TYPE", "float"}, {"D_TYPE", "float16_t"}});
+    string_to_spv("rope_neox_f32_f16_rte", "rope_neox.comp", {{"A_TYPE", "float"}, {"D_TYPE", "float16_t"}, {"RTE16", "1"}});
 
     string_to_spv("rope_multi_f32", "rope_multi.comp", {{"A_TYPE", "float"}, {"D_TYPE", "float"}});
     string_to_spv("rope_multi_f16", "rope_multi.comp", {{"A_TYPE", "float16_t"}, {"D_TYPE", "float16_t"}});
diff --git a/ml/backend/ggml/ggml_test.go b/ml/backend/ggml/ggml_test.go
index 31dfdb7b..efd3a455 100644
--- a/ml/backend/ggml/ggml_test.go
+++ b/ml/backend/ggml/ggml_test.go
@@ -2,6 +2,7 @@ package ggml
 
 import (
 	"errors"
+	"fmt"
 	"os"
 	"testing"
 
@@ -368,10 +369,714 @@ func TestPermute(t *testing.T) {
 	for _, tt := range cases {
 		t.Run(tt.name, func(t *testing.T) {
 			ctx := setup(t)
-			got := tt.input(ctx).Permute(ctx, tt.shape...).Contiguous(ctx)
+			got := tt.input(ctx).Permute(ctx, tt.shape...)
+			got = got.Contiguous(ctx)
 			if diff := cmp.Diff(tt.want(ctx), got, EquateTensors(ctx)); diff != "" {
 				t.Errorf("Permute() result mismatch (-want +got):\n%s", diff)
 			}
 		})
 	}
 }
+
+func TestSlice(t *testing.T) {
+	cases := []struct {
+		dim   int
+		low   int
+		high  int
+		step  int
+		input func(ml.Context) ml.Tensor
+		want  func(ml.Context) ml.Tensor
+	}{
+		{
+			dim: 0, low: 1, high: 3, step: 1,
+			input: func(ctx ml.Context) ml.Tensor {
+				return ctx.Arange(0, 4*4*4*4, 1, ml.DTypeF32).Reshape(ctx, 4, 4, 4, 4)
+			},
+			want: func(ctx ml.Context) ml.Tensor {
+				return ctx.FromFloats([]float32{
+					1, 2,
+					5, 6,
+					9, 10,
+					13, 14,
+
+					17, 18,
+					21, 22,
+					25, 26,
+					29, 30,
+
+					33, 34,
+					37, 38,
+					41, 42,
+					45, 46,
+
+					49, 50,
+					53, 54,
+					57, 58,
+					61, 62,
+
+					65, 66,
+					69, 70,
+					73, 74,
+					77, 78,
+
+					81, 82,
+					85, 86,
+					89, 90,
+					93, 94,
+
+					97, 98,
+					101, 102,
+					105, 106,
+					109, 110,
+
+					113, 114,
+					117, 118,
+					121, 122,
+					125, 126,
+
+					129, 130,
+					133, 134,
+					137, 138,
+					141, 142,
+
+					145, 146,
+					149, 150,
+					153, 154,
+					157, 158,
+
+					161, 162,
+					165, 166,
+					169, 170,
+					173, 174,
+
+					177, 178,
+					181, 182,
+					185, 186,
+					189, 190,
+
+					193, 194,
+					197, 198,
+					201, 202,
+					205, 206,
+
+					209, 210,
+					213, 214,
+					217, 218,
+					221, 222,
+
+					225, 226,
+					229, 230,
+					233, 234,
+					237, 238,
+
+					241, 242,
+					245, 246,
+					249, 250,
+					253, 254,
+				}, 2, 4, 4, 4)
+			},
+		},
+		{
+			dim: 1, low: 1, high: 3, step: 1,
+			input: func(ctx ml.Context) ml.Tensor {
+				return ctx.Arange(0, 4*4*4*4, 1, ml.DTypeF32).Reshape(ctx, 4, 4, 4, 4)
+			},
+			want: func(ctx ml.Context) ml.Tensor {
+				return ctx.FromFloats([]float32{
+					4, 5, 6, 7,
+					8, 9, 10, 11,
+
+					20, 21, 22, 23,
+					24, 25, 26, 27,
+
+					36, 37, 38, 39,
+					40, 41, 42, 43,
+
+					52, 53, 54, 55,
+					56, 57, 58, 59,
+
+					68, 69, 70, 71,
+					72, 73, 74, 75,
+
+					84, 85, 86, 87,
+					88, 89, 90, 91,
+
+					100, 101, 102, 103,
+					104, 105, 106, 107,
+
+					116, 117, 118, 119,
+					120, 121, 122, 123,
+
+					132, 133, 134, 135,
+					136, 137, 138, 139,
+
+					148, 149, 150, 151,
+					152, 153, 154, 155,
+
+					164, 165, 166, 167,
+					168, 169, 170, 171,
+
+					180, 181, 182, 183,
+					184, 185, 186, 187,
+
+					196, 197, 198, 199,
+					200, 201, 202, 203,
+
+					212, 213, 214, 215,
+					216, 217, 218, 219,
+
+					228, 229, 230, 231,
+					232, 233, 234, 235,
+
+					244, 245, 246, 247,
+					248, 249, 250, 251,
+				}, 4, 2, 4, 4)
+			},
+		},
+		{
+			dim: 2, low: 1, high: 3, step: 1,
+			input: func(ctx ml.Context) ml.Tensor {
+				return ctx.Arange(0, 4*4*4*4, 1, ml.DTypeF32).Reshape(ctx, 4, 4, 4, 4)
+			},
+			want: func(ctx ml.Context) ml.Tensor {
+				return ctx.FromFloats([]float32{
+					16, 17, 18, 19,
+					20, 21, 22, 23,
+					24, 25, 26, 27,
+					28, 29, 30, 31,
+
+					32, 33, 34, 35,
+					36, 37, 38, 39,
+					40, 41, 42, 43,
+					44, 45, 46, 47,
+
+					80, 81, 82, 83,
+					84, 85, 86, 87,
+					88, 89, 90, 91,
+					92, 93, 94, 95,
+
+					96, 97, 98, 99,
+					100, 101, 102, 103,
+					104, 105, 106, 107,
+					108, 109, 110, 111,
+
+					144, 145, 146, 147,
+					148, 149, 150, 151,
+					152, 153, 154, 155,
+					156, 157, 158, 159,
+
+					160, 161, 162, 163,
+					164, 165, 166, 167,
+					168, 169, 170, 171,
+					172, 173, 174, 175,
+
+					208, 209, 210, 211,
+					212, 213, 214, 215,
+					216, 217, 218, 219,
+					220, 221, 222, 223,
+
+					224, 225, 226, 227,
+					228, 229, 230, 231,
+					232, 233, 234, 235,
+					236, 237, 238, 239,
+				}, 4, 4, 2, 4)
+			},
+		},
+		{
+			dim: 3, low: 1, high: 3, step: 1,
+			input: func(ctx ml.Context) ml.Tensor {
+				return ctx.Arange(0, 4*4*4*4, 1, ml.DTypeF32).Reshape(ctx, 4, 4, 4, 4)
+			},
+			want: func(ctx ml.Context) ml.Tensor {
+				return ctx.FromFloats([]float32{
+					64, 65, 66, 67,
+					68, 69, 70, 71,
+					72, 73, 74, 75,
+					76, 77, 78, 79,
+
+					80, 81, 82, 83,
+					84, 85, 86, 87,
+					88, 89, 90, 91,
+					92, 93, 94, 95,
+
+					96, 97, 98, 99,
+					100, 101, 102, 103,
+					104, 105, 106, 107,
+					108, 109, 110, 111,
+
+					112, 113, 114, 115,
+					116, 117, 118, 119,
+					120, 121, 122, 123,
+					124, 125, 126, 127,
+
+					128, 129, 130, 131,
+					132, 133, 134, 135,
+					136, 137, 138, 139,
+					140, 141, 142, 143,
+
+					144, 145, 146, 147,
+					148, 149, 150, 151,
+					152, 153, 154, 155,
+					156, 157, 158, 159,
+
+					160, 161, 162, 163,
+					164, 165, 166, 167,
+					168, 169, 170, 171,
+					172, 173, 174, 175,
+
+					176, 177, 178, 179,
+					180, 181, 182, 183,
+					184, 185, 186, 187,
+					188, 189, 190, 191,
+				}, 4, 4, 4, 2)
+			},
+		},
+		{
+			dim: 0, low: 0, high: 4, step: 2,
+			input: func(ctx ml.Context) ml.Tensor {
+				return ctx.Arange(0, 4*4*4*4, 1, ml.DTypeF32).Reshape(ctx, 4, 4, 4, 4)
+			},
+			want: func(ctx ml.Context) ml.Tensor {
+				return ctx.FromFloats([]float32{
+					0, 2,
+					4, 6,
+					8, 10,
+					12, 14,
+
+					16, 18,
+					20, 22,
+					24, 26,
+					28, 30,
+
+					32, 34,
+					36, 38,
+					40, 42,
+					44, 46,
+
+					48, 50,
+					52, 54,
+					56, 58,
+					60, 62,
+
+					64, 66,
+					68, 70,
+					72, 74,
+					76, 78,
+
+					80, 82,
+					84, 86,
+					88, 90,
+					92, 94,
+
+					96, 98,
+					100, 102,
+					104, 106,
+					108, 110,
+
+					112, 114,
+					116, 118,
+					120, 122,
+					124, 126,
+
+					128, 130,
+					132, 134,
+					136, 138,
+					140, 142,
+
+					144, 146,
+					148, 150,
+					152, 154,
+					156, 158,
+
+					160, 162,
+					164, 166,
+					168, 170,
+					172, 174,
+
+					176, 178,
+					180, 182,
+					184, 186,
+					188, 190,
+
+					192, 194,
+					196, 198,
+					200, 202,
+					204, 206,
+
+					208, 210,
+					212, 214,
+					216, 218,
+					220, 222,
+
+					224, 226,
+					228, 230,
+					232, 234,
+					236, 238,
+
+					240, 242,
+					244, 246,
+					248, 250,
+					252, 254,
+				}, 2, 4, 4, 4)
+			},
+		},
+		{
+			dim: 1, low: 0, high: 4, step: 2,
+			input: func(ctx ml.Context) ml.Tensor {
+				return ctx.Arange(0, 4*4*4*4, 1, ml.DTypeF32).Reshape(ctx, 4, 4, 4, 4)
+			},
+			want: func(ctx ml.Context) ml.Tensor {
+				return ctx.FromFloats([]float32{
+					0, 1, 2, 3,
+					8, 9, 10, 11,
+
+					16, 17, 18, 19,
+					24, 25, 26, 27,
+
+					32, 33, 34, 35,
+					40, 41, 42, 43,
+
+					48, 49, 50, 51,
+					56, 57, 58, 59,
+
+					64, 65, 66, 67,
+					72, 73, 74, 75,
+
+					80, 81, 82, 83,
+					88, 89, 90, 91,
+
+					96, 97, 98, 99,
+					104, 105, 106, 107,
+
+					112, 113, 114, 115,
+					120, 121, 122, 123,
+
+					128, 129, 130, 131,
+					136, 137, 138, 139,
+
+					144, 145, 146, 147,
+					152, 153, 154, 155,
+
+					160, 161, 162, 163,
+					168, 169, 170, 171,
+
+					176, 177, 178, 179,
+					184, 185, 186, 187,
+
+					192, 193, 194, 195,
+					200, 201, 202, 203,
+
+					208, 209, 210, 211,
+					216, 217, 218, 219,
+
+					224, 225, 226, 227,
+					232, 233, 234, 235,
+
+					240, 241, 242, 243,
+					248, 249, 250, 251,
+				}, 4, 2, 4, 4)
+			},
+		},
+		{
+			dim: 2, low: 0, high: 4, step: 2,
+			input: func(ctx ml.Context) ml.Tensor {
+				return ctx.Arange(0, 4*4*4*4, 1, ml.DTypeF32).Reshape(ctx, 4, 4, 4, 4)
+			},
+			want: func(ctx ml.Context) ml.Tensor {
+				return ctx.FromFloats([]float32{
+					0, 1, 2, 3,
+					4, 5, 6, 7,
+					8, 9, 10, 11,
+					12, 13, 14, 15,
+
+					32, 33, 34, 35,
+					36, 37, 38, 39,
+					40, 41, 42, 43,
+					44, 45, 46, 47,
+
+					64, 65, 66, 67,
+					68, 69, 70, 71,
+					72, 73, 74, 75,
+					76, 77, 78, 79,
+
+					96, 97, 98, 99,
+					100, 101, 102, 103,
+					104, 105, 106, 107,
+					108, 109, 110, 111,
+
+					128, 129, 130, 131,
+					132, 133, 134, 135,
+					136, 137, 138, 139,
+					140, 141, 142, 143,
+
+					160, 161, 162, 163,
+					164, 165, 166, 167,
+					168, 169, 170, 171,
+					172, 173, 174, 175,
+
+					192, 193, 194, 195,
+					196, 197, 198, 199,
+					200, 201, 202, 203,
+					204, 205, 206, 207,
+
+					224, 225, 226, 227,
+					228, 229, 230, 231,
+					232, 233, 234, 235,
+					236, 237, 238, 239,
+				}, 4, 4, 2, 4)
+			},
+		},
+		{
+			dim: 3, low: 0, high: 4, step: 2,
+			input: func(ctx ml.Context) ml.Tensor {
+				return ctx.Arange(0, 4*4*4*4, 1, ml.DTypeF32).Reshape(ctx, 4, 4, 4, 4)
+			},
+			want: func(ctx ml.Context) ml.Tensor {
+				return ctx.FromFloats([]float32{
+					0, 1, 2, 3,
+					4, 5, 6, 7,
+					8, 9, 10, 11,
+					12, 13, 14, 15,
+
+					16, 17, 18, 19,
+					20, 21, 22, 23,
+					24, 25, 26, 27,
+					28, 29, 30, 31,
+
+					32, 33, 34, 35,
+					36, 37, 38, 39,
+					40, 41, 42, 43,
+					44, 45, 46, 47,
+
+					48, 49, 50, 51,
+					52, 53, 54, 55,
+					56, 57, 58, 59,
+					60, 61, 62, 63,
+
+					128, 129, 130, 131,
+					132, 133, 134, 135,
+					136, 137, 138, 139,
+					140, 141, 142, 143,
+
+					144, 145, 146, 147,
+					148, 149, 150, 151,
+					152, 153, 154, 155,
+					156, 157, 158, 159,
+
+					160, 161, 162, 163,
+					164, 165, 166, 167,
+					168, 169, 170, 171,
+					172, 173, 174, 175,
+
+					176, 177, 178, 179,
+					180, 181, 182, 183,
+					184, 185, 186, 187,
+					188, 189, 190, 191,
+				}, 4, 4, 4, 2)
+			},
+		},
+	}
+
+	for _, tt := range cases {
+		name := fmt.Sprintf("dim=%d,low=%d,high=%d,step=%d", tt.dim, tt.low, tt.high, tt.step)
+		t.Run(name, func(t *testing.T) {
+			ctx := setup(t)
+			got := tt.input(ctx).Slice(ctx, tt.dim, tt.low, tt.high, tt.step)
+			got = got.Contiguous(ctx)
+			if diff := cmp.Diff(tt.want(ctx), got, EquateTensors(ctx)); diff != "" {
+				t.Errorf("Slice() result mismatch (-want +got):\n%s", diff)
+			}
+		})
+	}
+}
+
+func TestSplitSections(t *testing.T) {
+	cases := []struct {
+		dim      int
+		sections []int
+		input    func(ml.Context) ml.Tensor
+		want     []func(ml.Context) ml.Tensor
+	}{
+		{
+			dim: 0, sections: []int{1, 1, 1},
+			input: func(ctx ml.Context) ml.Tensor {
+				return ctx.Arange(0, 12, 1, ml.DTypeF32).Reshape(ctx, 3, 4)
+			},
+			want: []func(ml.Context) ml.Tensor{
+				func(ctx ml.Context) ml.Tensor {
+					return ctx.FromFloats([]float32{0, 3, 6, 9}, 1, 4)
+				},
+				func(ctx ml.Context) ml.Tensor {
+					return ctx.FromFloats([]float32{1, 4, 7, 10}, 1, 4)
+				},
+				func(ctx ml.Context) ml.Tensor {
+					return ctx.FromFloats([]float32{2, 5, 8, 11}, 1, 4)
+				},
+			},
+		},
+		{
+			dim: 1, sections: []int{1, 3},
+			input: func(ctx ml.Context) ml.Tensor {
+				return ctx.Arange(0, 12, 1, ml.DTypeF32).Reshape(ctx, 3, 4)
+			},
+			want: []func(ml.Context) ml.Tensor{
+				func(ctx ml.Context) ml.Tensor {
+					return ctx.FromFloats([]float32{0, 1, 2}, 3, 1)
+				},
+				func(ctx ml.Context) ml.Tensor {
+					return ctx.FromFloats([]float32{
+						3, 4, 5,
+						6, 7, 8,
+						9, 10, 11,
+					}, 3, 3)
+				},
+			},
+		},
+		{
+			dim: 0, sections: []int{2, 2},
+			input: func(ctx ml.Context) ml.Tensor {
+				return ctx.Arange(0, 12, 1, ml.DTypeF32).Reshape(ctx, 4, 3)
+			},
+			want: []func(ml.Context) ml.Tensor{
+				func(ctx ml.Context) ml.Tensor {
+					return ctx.FromFloats([]float32{
+						0, 1,
+						4, 5,
+						8, 9,
+					}, 2, 3)
+				},
+				func(ctx ml.Context) ml.Tensor {
+					return ctx.FromFloats([]float32{
+						2, 3,
+						6, 7,
+						10, 11,
+					}, 2, 3)
+				},
+			},
+		},
+		{
+			dim: 1, sections: []int{1, 2},
+			input: func(ctx ml.Context) ml.Tensor {
+				return ctx.Arange(0, 12, 1, ml.DTypeF32).Reshape(ctx, 4, 3)
+			},
+			want: []func(ml.Context) ml.Tensor{
+				func(ctx ml.Context) ml.Tensor {
+					return ctx.FromFloats([]float32{0, 1, 2, 3}, 4, 1)
+				},
+				func(ctx ml.Context) ml.Tensor {
+					return ctx.FromFloats([]float32{
+						4, 5, 6, 7,
+						8, 9, 10, 11,
+					}, 4, 2)
+				},
+			},
+		},
+	}
+
+	for _, tt := range cases {
+		t.Run(fmt.Sprintf("sections=%v", tt.sections), func(t *testing.T) {
+			ctx := setup(t)
+			got := tt.input(ctx).ChunkSections(ctx, tt.dim, tt.sections...)
+
+			for i := range got {
+				got[i] = got[i].Contiguous(ctx)
+			}
+
+			ctx.Forward(got...).Compute(got...)
+			for i, want := range tt.want {
+				if diff := cmp.Diff(want(ctx), got[i], EquateTensors(ctx)); diff != "" {
+					t.Errorf("SplitSections() section %d mismatch (-want +got):\n%s", i, diff)
+				}
+			}
+		})
+	}
+}
+
+func TestChunk(t *testing.T) {
+	cases := []struct {
+		dim   int
+		chunk int
+		input func(ml.Context) ml.Tensor
+		want  []func(ml.Context) ml.Tensor
+	}{
+		{
+			dim: 0, chunk: 1,
+			input: func(ctx ml.Context) ml.Tensor {
+				return ctx.Arange(0, 12, 1, ml.DTypeF32).Reshape(ctx, 3, 4)
+			},
+			want: []func(ml.Context) ml.Tensor{
+				func(ctx ml.Context) ml.Tensor {
+					return ctx.FromFloats([]float32{0, 3, 6, 9}, 1, 4)
+				},
+				func(ctx ml.Context) ml.Tensor {
+					return ctx.FromFloats([]float32{1, 4, 7, 10}, 1, 4)
+				},
+				func(ctx ml.Context) ml.Tensor {
+					return ctx.FromFloats([]float32{2, 5, 8, 11}, 1, 4)
+				},
+			},
+		},
+		{
+			dim: 1, chunk: 2,
+			input: func(ctx ml.Context) ml.Tensor {
+				return ctx.Arange(0, 12, 1, ml.DTypeF32).Reshape(ctx, 3, 4)
+			},
+			want: []func(ml.Context) ml.Tensor{
+				func(ctx ml.Context) ml.Tensor {
+					return ctx.FromFloats([]float32{
+						0, 1, 2,
+						3, 4, 5,
+					}, 3, 2)
+				},
+				func(ctx ml.Context) ml.Tensor {
+					return ctx.FromFloats([]float32{
+						6, 7, 8,
+						9, 10, 11,
+					}, 3, 2)
+				},
+			},
+		},
+		{
+			dim: 0, chunk: 2,
+			input: func(ctx ml.Context) ml.Tensor {
+				return ctx.Arange(0, 12, 1, ml.DTypeF32).Reshape(ctx, 3, 4)
+			},
+			want: []func(ml.Context) ml.Tensor{
+				func(ctx ml.Context) ml.Tensor {
+					return ctx.FromFloats([]float32{
+						0, 1,
+						3, 4,
+						6, 7,
+						9, 10,
+					}, 2, 4)
+				},
+				func(ctx ml.Context) ml.Tensor {
+					return ctx.FromFloats([]float32{
+						2,
+						5,
+						8,
+						11,
+					}, 1, 4)
+				},
+			},
+		},
+	}
+
+	for _, tt := range cases {
+		t.Run(fmt.Sprintf("dim=%d,chunk=%d", tt.dim, tt.chunk), func(t *testing.T) {
+			ctx := setup(t)
+			got := tt.input(ctx).Chunk(ctx, tt.dim, tt.chunk)
+
+			for i := range got {
+				got[i] = got[i].Contiguous(ctx)
+			}
+
+			ctx.Forward(got...).Compute(got...)
+			for i, want := range tt.want {
+				if diff := cmp.Diff(want(ctx), got[i], EquateTensors(ctx)); diff != "" {
+					t.Errorf("Split() section %d mismatch (-want +got):\n%s", i, diff)
+				}
+			}
+		})
+	}
+}
diff --git a/ml/device.go b/ml/device.go
index dc91359f..f0654127 100644
--- a/ml/device.go
+++ b/ml/device.go
@@ -8,6 +8,7 @@ import (
 	"hash/maphash"
 	"io"
 	"log/slog"
+	"math"
 	"net/http"
 	"runtime"
 	"slices"
@@ -28,6 +29,22 @@ type GPULayers struct {
 	Layers []int
 }
 
+// FirstLayer returns the smallest layer index scheduled on this GPU, or MaxInt when empty.
+func (g GPULayers) FirstLayer() int {
+	if len(g.Layers) == 0 {
+		return math.MaxInt
+	}
+
+	first := g.Layers[0]
+	for i := 1; i < len(g.Layers); i++ {
+		if g.Layers[i] < first {
+			first = g.Layers[i]
+		}
+	}
+
+	return first
+}
+
 func (g GPULayers) String() string {
 	if len(g.Layers) == 0 {
 		return ""
@@ -54,6 +71,17 @@ func (g GPULayers) String() string {
 // GPULayersList is a set of layer allocations across multiple GPUs
 type GPULayersList []GPULayers
 
+func (l GPULayersList) Len() int      { return len(l) }
+func (l GPULayersList) Swap(i, j int) { l[i], l[j] = l[j], l[i] }
+
+// Sort by the ordering of the layers offloaded
+func (l GPULayersList) Less(i, j int) bool {
+	li := l[i].FirstLayer()
+	lj := l[j].FirstLayer()
+
+	return li < lj
+}
+
 func (l GPULayersList) String() string {
 	if l.Sum() > 0 {
 		return fmt.Sprintf("%v%v", l.Sum(), []GPULayers(l))
@@ -339,6 +367,28 @@ func (a ByFreeMemory) Less(i, j int) bool {
 	return a[i].FreeMemory < a[j].FreeMemory
 }
 
+// ByPerformance groups devices by similar speed
+func ByPerformance(l []DeviceInfo) [][]DeviceInfo {
+	resp := [][]DeviceInfo{}
+	scores := []bool{}
+	for _, info := range l {
+		found := false
+		requested := info.Integrated
+		for i, score := range scores {
+			if score == requested {
+				resp[i] = append(resp[i], info)
+				found = true
+				break
+			}
+		}
+		if !found {
+			scores = append(scores, requested)
+			resp = append(resp, []DeviceInfo{info})
+		}
+	}
+	return resp
+}
+
 func ByLibrary(l []DeviceInfo) [][]DeviceInfo {
 	resp := [][]DeviceInfo{}
 	libs := []string{}
diff --git a/ml/nn/pooling/pooling.go b/ml/nn/pooling/pooling.go
index 63b63b3a..47af8746 100644
--- a/ml/nn/pooling/pooling.go
+++ b/ml/nn/pooling/pooling.go
@@ -32,10 +32,9 @@ func (t Type) Forward(ctx ml.Context, hiddenStates ml.Tensor) ml.Tensor {
 		hiddenStates = hiddenStates.Permute(ctx, 1, 0, 2, 3).Contiguous(ctx).Mean(ctx)
 		return hiddenStates.Permute(ctx, 1, 0, 2, 3).Contiguous(ctx)
 	case TypeCLS:
-		return hiddenStates.View(ctx, 0, hiddenStates.Dim(0))
+		return hiddenStates.Slice(ctx, 1, 0, 1, 1)
 	case TypeLast:
-		hiddenStates = hiddenStates.View(ctx, (hiddenStates.Dim(1)-1)*hiddenStates.Stride(1), hiddenStates.Dim(0))
-		return hiddenStates
+		return hiddenStates.Slice(ctx, 1, hiddenStates.Dim(1)-1, hiddenStates.Dim(1), 1)
 	default:
 		panic("unknown pooling type")
 	}
diff --git a/model/models/bert/embed.go b/model/models/bert/embed.go
index 2d78710f..f2dd1deb 100644
--- a/model/models/bert/embed.go
+++ b/model/models/bert/embed.go
@@ -29,7 +29,7 @@ type Model struct {
 // Forward implements model.Model.
 func (m *Model) Forward(ctx ml.Context, batch input.Batch) (ml.Tensor, error) {
 	hiddenStates := m.TokenEmbedding.Forward(ctx, batch.Inputs)
-	hiddenStates = hiddenStates.Add(ctx, m.TypeEmbedding.Weight.View(ctx, 0, m.hiddenSize))
+	hiddenStates = hiddenStates.Add(ctx, m.TypeEmbedding.Weight.Slice(ctx, 1, 0, 1, 1))
 	hiddenStates = hiddenStates.Add(ctx, m.PositionEmbedding.Forward(ctx, ctx.Input().FromInts(batch.Positions, len(batch.Positions))))
 	hiddenStates = m.TokenEmbeddingNorm.Forward(ctx, hiddenStates, m.eps)
 
diff --git a/model/models/deepseek2/model.go b/model/models/deepseek2/model.go
index cfd579ca..68b12cd9 100644
--- a/model/models/deepseek2/model.go
+++ b/model/models/deepseek2/model.go
@@ -78,44 +78,31 @@ func (attn *Attention) Forward(ctx ml.Context, hiddenStates, positions ml.Tensor
 	}
 
 	query = query.Reshape(ctx, query.Dim(0)/opts.numHeads, opts.numHeads, seqLength)
-
-	qPass := query.View(ctx, 0,
-		opts.qkNopeHeadDim, query.Stride(1),
-		query.Dim(1), query.Stride(2),
-		query.Dim(2))
-
-	qRot := query.View(ctx, opts.qkNopeHeadDim*query.Stride(0),
-		opts.qkRopeHeadDim, query.Stride(1),
-		query.Dim(1), query.Stride(2),
-		query.Dim(2))
+	queryChunks := query.ChunkSections(ctx, 0, opts.qkNopeHeadDim, opts.qkRopeHeadDim)
 
 	compressedKV := attn.KVA.Forward(ctx, hiddenStates)
-
-	kPass := compressedKV.View(ctx, 0, opts.kvLoraRank, compressedKV.Stride(1), compressedKV.Dim(1))
-	kRot := compressedKV.View(ctx, opts.kvLoraRank*compressedKV.Stride(0),
-		opts.qkRopeHeadDim, compressedKV.Stride(1),
-		1, compressedKV.Stride(1),
-		compressedKV.Dim(1))
+	kPass := compressedKV.Slice(ctx, 0, 0, opts.kvLoraRank, 1)
+	kRot := compressedKV.View(ctx,
+		opts.kvLoraRank*compressedKV.Stride(0), opts.qkRopeHeadDim,
+		compressedKV.Stride(1), 1,
+		compressedKV.Stride(1), compressedKV.Dim(1),
+	)
 
 	kPass = attn.KVANorm.Forward(ctx, kPass, opts.eps)
 	kPass = attn.KVB.Forward(ctx, kPass)
 
 	kv := kPass.Reshape(ctx, kPass.Dim(0)/opts.numKVHeads, opts.numKVHeads, seqLength)
-	kPass = kv.View(ctx, 0, opts.kqNopeHeadDim, kv.Stride(1), kv.Dim(1), kv.Stride(2), kv.Dim(2))
-	value := kv.View(ctx, opts.kqNopeHeadDim*kv.Stride(0),
-		opts.vHeadDim, kv.Stride(1),
-		kv.Dim(1), kv.Stride(2),
-		kv.Dim(2)).Contiguous(ctx)
+	kvChunks := kv.ChunkSections(ctx, 0, opts.kqNopeHeadDim, opts.vHeadDim)
 
-	qRot = fast.RoPE(ctx, qRot, positions, opts.qkRopeHeadDim, opts.ropeBase, 1./opts.ropeScale, opts.RoPEOptions()...)
+	qRot := fast.RoPE(ctx, queryChunks[1], positions, opts.qkRopeHeadDim, opts.ropeBase, 1./opts.ropeScale, opts.RoPEOptions()...)
 	kRot = fast.RoPE(ctx, kRot, positions, opts.qkRopeHeadDim, opts.ropeBase, 1./opts.ropeScale, opts.RoPEOptions()...)
 
-	kRot = kRot.Repeat(ctx, 1, qPass.Dim(1))
+	kRot = kRot.Repeat(ctx, 1, queryChunks[0].Dim(1))
 
-	query = qRot.Concat(ctx, qPass, 0)
-	key := kRot.Concat(ctx, kPass, 0)
+	query = qRot.Concat(ctx, queryChunks[0], 0)
+	key := kRot.Concat(ctx, kvChunks[0], 0)
 
-	attention := nn.Attention(ctx, query, key, value, opts.kqScale, cache)
+	attention := nn.Attention(ctx, query, key, kvChunks[1], opts.kqScale, cache)
 	attention = attention.Reshape(ctx, attention.Dim(0)*attention.Dim(1), seqLength)
 	return attn.Output.Forward(ctx, attention)
 }
@@ -142,6 +129,7 @@ func (moe *sparse) Moe(ctx ml.Context, hiddenStates, topKIndices, topKWeights ml
 
 	experts := moe.Down.Weight.MulmatID(ctx, hiddenStates, topKIndices)
 	experts = experts.Mul(ctx, topKWeights)
+
 	nextStates := experts.View(ctx, 0, experts.Dim(0), experts.Stride(2), experts.Dim(2))
 	for i := 1; i < opts.numExpertsUsed; i++ {
 		nextStates = nextStates.Add(ctx, experts.View(ctx, i*experts.Stride(1), experts.Dim(0), experts.Stride(2), experts.Dim(2)))
diff --git a/model/models/gemma3n/model_text.go b/model/models/gemma3n/model_text.go
index ec038a28..3a89afe7 100644
--- a/model/models/gemma3n/model_text.go
+++ b/model/models/gemma3n/model_text.go
@@ -64,18 +64,18 @@ func (m *TextModel) Forward(ctx ml.Context, batch input.Batch, cache kvcache.Cac
 
 		cache.(*kvcache.WrapperCache).SetLayerType(layerType)
 
-		// inputPerLayer = inputsPerLayer[:, i, :]
-		inputPerLayer := inputsPerLayer.View(ctx, i*inputsPerLayer.Stride(1), inputsPerLayer.Dim(0), inputsPerLayer.Stride(2), inputsPerLayer.Dim(2)).Contiguous(ctx)
+		// inputPerLayer = inputsPerLayer[:, i, :].squeeze(1)
+		inputPerLayer := inputsPerLayer.View(ctx, i*inputsPerLayer.Stride(1), inputsPerLayer.Dim(0), inputsPerLayer.Stride(2), inputsPerLayer.Dim(2))
 		hiddenStates = layer.Forward(ctx, hiddenStates, inputPerLayer, positions, one, cache, i >= firstSharedKeyValue, ropeBase, float64(m.activationSparsityScale[i]), &m.TextOptions)
 	}
 
 	// hiddenStates = hiddenStates[:, :, 0]
-	hiddenStates0 := hiddenStates.View(ctx, 0, hiddenStates.Dim(0), hiddenStates.Stride(1), hiddenStates.Dim(1))
+	hiddenStates0 := hiddenStates.Slice(ctx, 2, 0, 1, 1)
 	targetMagnitude = hiddenStates0.Sqr(ctx).Mean(ctx).Sqrt(ctx)
 	targetMagnitude = targetMagnitude.Repeat(ctx, 2, m.altupInputs-1)
 
 	// hiddenState = hiddenStates[:, :, 1:]
-	hiddenState = hiddenStates.View(ctx, hiddenStates.Stride(2), hiddenStates.Dim(0), hiddenStates.Stride(1), hiddenStates.Dim(1), hiddenStates.Stride(2), m.altupInputs-1)
+	hiddenState = hiddenStates.Slice(ctx, 2, 1, hiddenStates.Dim(2), 1)
 	altupUnembdProj := m.AltupUnembd.Forward(ctx, hiddenState)
 	altupUnembdProj = altupUnembdProj.Mul(ctx, targetMagnitude.Div(ctx, altupUnembdProj.Sqr(ctx).Mean(ctx).Sqrt(ctx)))
 
@@ -176,10 +176,10 @@ func (d TextLayer) Forward(ctx ml.Context, hiddenStates, perLayerInput, position
 	active = d.PostPerLayerNorm.Forward(ctx, active, opts.eps)
 
 	// inactive := predictions[:, :, 1:]
-	inactive := predictions.View(ctx, predictions.Stride(2), predictions.Dim(0), predictions.Stride(1), predictions.Dim(1), predictions.Stride(2), predictions.Dim(2)-1)
+	inactive := predictions.Slice(ctx, 2, 1, predictions.Dim(2), 1)
 	active = inactive.Add(ctx, active)
 
-	predictions0 := predictions.View(ctx, 0, predictions.Dim(0), predictions.Stride(1), predictions.Dim(1))
+	predictions0 := predictions.Slice(ctx, 2, 0, 1, 1)
 	return predictions0.Concat(ctx, active, 2)
 }
 
@@ -319,7 +319,7 @@ type TextOptions struct {
 
 func (o *TextOptions) altupActive(ctx ml.Context, t ml.Tensor) ml.Tensor {
 	// t[:, :, o.altupActiveIndex]
-	return t.View(ctx, o.altupActiveIndex*t.Stride(2), t.Dim(0), t.Stride(1), t.Dim(1))
+	return t.Slice(ctx, 2, o.altupActiveIndex, o.altupActiveIndex+1, 1)
 }
 
 func (o *TextOptions) headDim() int {
diff --git a/model/models/gptoss/model.go b/model/models/gptoss/model.go
index c10920f1..da08ed96 100644
--- a/model/models/gptoss/model.go
+++ b/model/models/gptoss/model.go
@@ -121,30 +121,9 @@ func (attn *AttentionBlock) Forward(ctx ml.Context, hiddenStates, positions ml.T
 	var query, key, value ml.Tensor
 	if attn.QKV != nil {
 		qkv := attn.QKV.Forward(ctx, hiddenStates)
-
-		// query = qkv[..., : num_attention_heads * head_dim].reshape(batch_size, num_attention_heads, head_dim)
-		query = qkv.View(ctx,
-			0,
-			opts.headDim(), qkv.Stride(0)*opts.headDim(),
-			opts.numHeads, qkv.Stride(1),
-			batchSize,
-		)
-
-		// key = qkv[..., num_attention_heads * head_dim:(num_attention_heads + num_key_value_heads) * head_dim].reshape(batch_size, num_key_value_heads, head_dim)
-		key = qkv.View(ctx,
-			qkv.Stride(0)*opts.headDim()*opts.numHeads,
-			opts.headDim(), qkv.Stride(0)*opts.headDim(),
-			opts.numKVHeads, qkv.Stride(1),
-			batchSize,
-		)
-
-		// value = qkv[..., (num_attention_heads  + num_key_value_heads) * head_dim:].reshape(batch_size, num_key_value_heads, head_dim)
-		value = qkv.View(ctx,
-			qkv.Stride(0)*opts.headDim()*(opts.numHeads+opts.numKVHeads),
-			opts.headDim(), qkv.Stride(0)*opts.headDim(),
-			opts.numKVHeads, qkv.Stride(1),
-			batchSize,
-		)
+		qkv = qkv.Reshape(ctx, opts.headDim(), -1, batchSize)
+		chunks := qkv.ChunkSections(ctx, 1, opts.numHeads, opts.numKVHeads, opts.numKVHeads)
+		query, key, value = chunks[0], chunks[1], chunks[2]
 	} else {
 		query = attn.Query.Forward(ctx, hiddenStates)
 		query = query.Reshape(ctx, opts.headDim(), opts.numHeads, batchSize)
@@ -195,15 +174,8 @@ func (mlp *MLPBlock) Forward(ctx ml.Context, hiddenStates ml.Tensor, opts *Optio
 	var gate, up ml.Tensor
 	if mlp.GateUp != nil {
 		hiddenStates = mlp.GateUp.Forward(ctx, hiddenStates, selectedExperts)
-		hiddenStates = hiddenStates.Reshape(ctx, 2, hiddenStates.Dim(0)/2, hiddenStates.Dim(1), hiddenStates.Dim(2))
-
-		dimStride := []int{hiddenStates.Dim(0) / 2, hiddenStates.Stride(1), hiddenStates.Dim(1), hiddenStates.Stride(2), hiddenStates.Dim(2), hiddenStates.Stride(3), hiddenStates.Dim(3)}
-
-		gate = hiddenStates.View(ctx, 0, dimStride...)
-		gate = gate.Contiguous(ctx, gate.Dim(0)*gate.Dim(1), gate.Dim(2), gate.Dim(3))
-
-		up = hiddenStates.View(ctx, hiddenStates.Stride(0), dimStride...)
-		up = up.Contiguous(ctx, up.Dim(0)*up.Dim(1), up.Dim(2), up.Dim(3))
+		gate = hiddenStates.Slice(ctx, 0, 0, hiddenStates.Dim(0), 2)
+		up = hiddenStates.Slice(ctx, 0, 1, hiddenStates.Dim(0), 2)
 	} else {
 		gate = mlp.Gate.Forward(ctx, hiddenStates, selectedExperts)
 		up = mlp.Up.Forward(ctx, hiddenStates, selectedExperts)
diff --git a/model/models/llama4/model.go b/model/models/llama4/model.go
index 5eeac07c..4a22bc4b 100644
--- a/model/models/llama4/model.go
+++ b/model/models/llama4/model.go
@@ -105,9 +105,7 @@ func (m *Model) EncodeMultimodal(ctx ml.Context, multimodalData []byte) ([]input
 
 		for range aspectRatio.Y {
 			for x := range aspectRatio.X {
-				view := projectedOutputs.View(ctx, projectedOutputs.Stride(1)*offset,
-					projectedOutputs.Dim(0), projectedOutputs.Stride(1),
-					patchesPerChunk)
+				view := projectedOutputs.Slice(ctx, 1, offset, offset+patchesPerChunk, 1)
 				var separator separator
 				if x < aspectRatio.X-1 {
 					separator.x = true // <|tile_x_separator|>
@@ -120,9 +118,7 @@ func (m *Model) EncodeMultimodal(ctx ml.Context, multimodalData []byte) ([]input
 		}
 	}
 
-	view := projectedOutputs.View(ctx, projectedOutputs.Stride(1)*offset,
-		projectedOutputs.Dim(0), projectedOutputs.Stride(1),
-		patchesPerChunk)
+	view := projectedOutputs.Slice(ctx, 1, offset, offset+patchesPerChunk, 1)
 	multimodal = append(multimodal, input.Multimodal{Tensor: view, Data: &separator{}})
 
 	return multimodal, nil
diff --git a/model/models/llama4/model_vision.go b/model/models/llama4/model_vision.go
index 1aa50aec..ff6b7fcf 100644
--- a/model/models/llama4/model_vision.go
+++ b/model/models/llama4/model_vision.go
@@ -37,27 +37,23 @@ type VisionAttention struct {
 func applyVisionRotaryEmbedding(ctx ml.Context, t, cos, sin ml.Tensor) ml.Tensor {
 	width, height, channels, tiles := t.Dim(0), t.Dim(1), t.Dim(2), t.Dim(3)
 
-	t = t.Reshape(ctx, 2, t.Dim(0)/2, t.Dim(1)*t.Dim(2)*t.Dim(3))
-
 	// t1 = t[..., 0::2]
-	t1 := t.View(ctx, 0, 1, t.Stride(1), t.Dim(1), t.Stride(2), t.Dim(2)).Contiguous(ctx)
-	t1 = t1.Reshape(ctx, width/2, height, channels, tiles)
+	t1 := t.Slice(ctx, 0, 0, t.Dim(0), 2)
 
 	// t2 = t[..., 1::2]
-	t2 := t.View(ctx, t.Stride(0), 1, t.Stride(1), t.Dim(1), t.Stride(2), t.Dim(2)).Contiguous(ctx)
-	t2 = t2.Reshape(ctx, width/2, height, channels, tiles)
+	t2 := t.Slice(ctx, 0, 1, t.Dim(0), 2)
 
 	// cos_out = torch.stack((t1 * cos, t2 * cos), dim=-1)
 	cosOut := t1.Mul(ctx, cos).Concat(ctx, t2.Mul(ctx, cos), 0)
-	cosOut = cosOut.Reshape(ctx, cosOut.Dim(0)/2, 2, cosOut.Dim(1)*cosOut.Dim(2)*cosOut.Dim(3))
-	cosOut = cosOut.Permute(ctx, 1, 0, 2, 3).Contiguous(ctx)
-	cosOut = cosOut.Reshape(ctx, width, height, channels, tiles)
+	cosOut = cosOut.Reshape(ctx, cosOut.Dim(0)/2, 2, -1)
+	cosOut = cosOut.Permute(ctx, 1, 0, 2, 3)
+	cosOut = cosOut.Contiguous(ctx, width, height, channels, tiles)
 
 	// sin_out = torch.stack((-t2 * sin, t1 * sin), dim=-1)
-	sinOut := t2.Neg(ctx).Mul(ctx, sin).Concat(ctx, t1.Mul(ctx, sin), 0)
-	sinOut = sinOut.Reshape(ctx, sinOut.Dim(0)/2, 2, sinOut.Dim(1)*sinOut.Dim(2)*sinOut.Dim(3))
-	sinOut = sinOut.Permute(ctx, 1, 0, 2, 3).Contiguous(ctx)
-	sinOut = sinOut.Reshape(ctx, width, height, channels, tiles)
+	sinOut := t2.Scale(ctx, -1).Mul(ctx, sin).Concat(ctx, t1.Mul(ctx, sin), 0)
+	sinOut = sinOut.Reshape(ctx, sinOut.Dim(0)/2, 2, -1)
+	sinOut = sinOut.Permute(ctx, 1, 0, 2, 3)
+	sinOut = sinOut.Contiguous(ctx, width, height, channels, tiles)
 
 	return cosOut.Add(ctx, sinOut)
 }
diff --git a/model/models/mistral3/model_vision.go b/model/models/mistral3/model_vision.go
index ce3110c7..d763df7a 100644
--- a/model/models/mistral3/model_vision.go
+++ b/model/models/mistral3/model_vision.go
@@ -11,9 +11,9 @@ import (
 var batchSize int = 1
 
 func rotateHalf(ctx ml.Context, t ml.Tensor) ml.Tensor {
-	x1 := t.View(ctx, 0, t.Dim(0)/2, t.Stride(1), t.Dim(1), t.Stride(2), t.Dim(2), t.Stride(3), t.Dim(3))
-	x2 := t.View(ctx, t.Stride(0)*t.Dim(0)/2, t.Dim(0)/2, t.Stride(1), t.Dim(1), t.Stride(2), t.Dim(2), t.Stride(3), t.Dim(3)).Contiguous(ctx)
-	return x2.Neg(ctx).Concat(ctx, x1, 0)
+	x1 := t.Slice(ctx, 0, 0, t.Dim(0)/2, 1)
+	x2 := t.Slice(ctx, 0, t.Dim(0)/2, t.Dim(0), 1).Contiguous(ctx)
+	return x2.Scale(ctx, -1).Concat(ctx, x1, 0)
 }
 
 func applyRotaryPositionalEmbedding(ctx ml.Context, t, cos, sin ml.Tensor) ml.Tensor {
diff --git a/model/models/qwen25vl/model_vision.go b/model/models/qwen25vl/model_vision.go
index 88b2c005..5cbb01f7 100644
--- a/model/models/qwen25vl/model_vision.go
+++ b/model/models/qwen25vl/model_vision.go
@@ -13,9 +13,9 @@ import (
 var batchSize int = 1
 
 func rotateHalf(ctx ml.Context, t ml.Tensor) ml.Tensor {
-	x1 := t.View(ctx, 0, t.Dim(0)/2, t.Stride(1), t.Dim(1), t.Stride(2), t.Dim(2), t.Stride(3), t.Dim(3))
-	x2 := t.View(ctx, t.Stride(0)*t.Dim(0)/2, t.Dim(0)/2, t.Stride(1), t.Dim(1), t.Stride(2), t.Dim(2), t.Stride(3), t.Dim(3)).Contiguous(ctx)
-	return x2.Neg(ctx).Concat(ctx, x1, 0)
+	x1 := t.Slice(ctx, 0, 0, t.Dim(0)/2, 1)
+	x2 := t.Slice(ctx, 0, t.Dim(0)/2, t.Dim(0), 1).Contiguous(ctx)
+	return x2.Scale(ctx, -1).Concat(ctx, x1, 0)
 }
 
 func applyRotaryPositionalEmbedding(ctx ml.Context, t, cos, sin ml.Tensor) ml.Tensor {
diff --git a/model/models/qwen3vl/model_vision.go b/model/models/qwen3vl/model_vision.go
index 69118666..b22ac305 100644
--- a/model/models/qwen3vl/model_vision.go
+++ b/model/models/qwen3vl/model_vision.go
@@ -18,8 +18,8 @@ type VisionAttention struct {
 }
 
 func rotateHalf(ctx ml.Context, t ml.Tensor) ml.Tensor {
-	x1 := t.View(ctx, 0, t.Dim(0)/2, t.Stride(1), t.Dim(1), t.Stride(2), t.Dim(2), t.Stride(3), t.Dim(3))
-	x2 := t.View(ctx, t.Stride(0)*t.Dim(0)/2, t.Dim(0)/2, t.Stride(1), t.Dim(1), t.Stride(2), t.Dim(2), t.Stride(3), t.Dim(3)).Contiguous(ctx)
+	x1 := t.Slice(ctx, 0, 0, t.Dim(0)/2, 1)
+	x2 := t.Slice(ctx, 0, t.Dim(0)/2, t.Dim(0), 1).Contiguous(ctx)
 	return x2.Scale(ctx, -1).Concat(ctx, x1, 0)
 }
 
@@ -160,10 +160,11 @@ func (m *VisionPositionEmbedding) Forward(ctx ml.Context, hiddenStates ml.Tensor
 	positionEmbeds = positionEmbeds.Mul(ctx, weights)
 	positionEmbeds = positionEmbeds.Reshape(ctx, n, -1, 4)
 
-	positionEmbeds = positionEmbeds.View(ctx, 0, n, positionEmbeds.Stride(1), grid.Height*grid.Width).
-		Add(ctx, positionEmbeds.View(ctx, 1*positionEmbeds.Stride(2), n, positionEmbeds.Stride(1), grid.Height*grid.Width)).
-		Add(ctx, positionEmbeds.View(ctx, 2*positionEmbeds.Stride(2), n, positionEmbeds.Stride(1), grid.Height*grid.Width)).
-		Add(ctx, positionEmbeds.View(ctx, 3*positionEmbeds.Stride(2), n, positionEmbeds.Stride(1), grid.Height*grid.Width))
+	positionEmbedsChunks := positionEmbeds.Chunk(ctx, 2, 1)
+	positionEmbeds = positionEmbedsChunks[0].
+		Add(ctx, positionEmbedsChunks[1]).
+		Add(ctx, positionEmbedsChunks[2]).
+		Add(ctx, positionEmbedsChunks[3])
 
 	positionEmbeds = positionEmbeds.Reshape(ctx, -1, grid.Width/opts.spatialMergeSize, opts.spatialMergeSize, grid.Height/opts.spatialMergeSize)
 	positionEmbeds = positionEmbeds.Permute(ctx, 0, 2, 1, 3).Contiguous(ctx, n, -1)
diff --git a/openai/openai.go b/openai/openai.go
index d4fd26c2..4713d481 100644
--- a/openai/openai.go
+++ b/openai/openai.go
@@ -40,22 +40,29 @@ type Message struct {
 	ToolCallID string     `json:"tool_call_id,omitempty"`
 }
 
+type ChoiceLogprobs struct {
+	Content []api.Logprob `json:"content"`
+}
+
 type Choice struct {
-	Index        int     `json:"index"`
-	Message      Message `json:"message"`
-	FinishReason *string `json:"finish_reason"`
+	Index        int             `json:"index"`
+	Message      Message         `json:"message"`
+	FinishReason *string         `json:"finish_reason"`
+	Logprobs     *ChoiceLogprobs `json:"logprobs,omitempty"`
 }
 
 type ChunkChoice struct {
-	Index        int     `json:"index"`
-	Delta        Message `json:"delta"`
-	FinishReason *string `json:"finish_reason"`
+	Index        int             `json:"index"`
+	Delta        Message         `json:"delta"`
+	FinishReason *string         `json:"finish_reason"`
+	Logprobs     *ChoiceLogprobs `json:"logprobs,omitempty"`
 }
 
 type CompleteChunkChoice struct {
-	Text         string  `json:"text"`
-	Index        int     `json:"index"`
-	FinishReason *string `json:"finish_reason"`
+	Text         string          `json:"text"`
+	Index        int             `json:"index"`
+	FinishReason *string         `json:"finish_reason"`
+	Logprobs     *ChoiceLogprobs `json:"logprobs,omitempty"`
 }
 
 type Usage struct {
@@ -104,6 +111,8 @@ type ChatCompletionRequest struct {
 	Tools            []api.Tool      `json:"tools"`
 	Reasoning        *Reasoning      `json:"reasoning,omitempty"`
 	ReasoningEffort  *string         `json:"reasoning_effort,omitempty"`
+	Logprobs         *bool           `json:"logprobs"`
+	TopLogprobs      int             `json:"top_logprobs"`
 	DebugRenderOnly  bool            `json:"_debug_render_only"`
 }
 
@@ -142,6 +151,7 @@ type CompletionRequest struct {
 	Temperature      *float32       `json:"temperature"`
 	TopP             float32        `json:"top_p"`
 	Suffix           string         `json:"suffix"`
+	Logprobs         *int           `json:"logprobs"`
 	DebugRenderOnly  bool           `json:"_debug_render_only"`
 }
 
@@ -251,6 +261,12 @@ func ToToolCalls(tc []api.ToolCall) []ToolCall {
 // ToChatCompletion converts an api.ChatResponse to ChatCompletion
 func ToChatCompletion(id string, r api.ChatResponse) ChatCompletion {
 	toolCalls := ToToolCalls(r.Message.ToolCalls)
+
+	var logprobs *ChoiceLogprobs
+	if len(r.Logprobs) > 0 {
+		logprobs = &ChoiceLogprobs{Content: r.Logprobs}
+	}
+
 	return ChatCompletion{
 		Id:                id,
 		Object:            "chat.completion",
@@ -269,6 +285,7 @@ func ToChatCompletion(id string, r api.ChatResponse) ChatCompletion {
 				}
 				return nil
 			}(r.DoneReason),
+			Logprobs: logprobs,
 		}}, Usage: ToUsage(r),
 		DebugInfo: r.DebugInfo,
 	}
@@ -277,6 +294,12 @@ func ToChatCompletion(id string, r api.ChatResponse) ChatCompletion {
 // ToChunk converts an api.ChatResponse to ChatCompletionChunk
 func ToChunk(id string, r api.ChatResponse, toolCallSent bool) ChatCompletionChunk {
 	toolCalls := ToToolCalls(r.Message.ToolCalls)
+
+	var logprobs *ChoiceLogprobs
+	if len(r.Logprobs) > 0 {
+		logprobs = &ChoiceLogprobs{Content: r.Logprobs}
+	}
+
 	return ChatCompletionChunk{
 		Id:                id,
 		Object:            "chat.completion.chunk",
@@ -295,6 +318,7 @@ func ToChunk(id string, r api.ChatResponse, toolCallSent bool) ChatCompletionChu
 				}
 				return nil
 			}(r.DoneReason),
+			Logprobs: logprobs,
 		}},
 	}
 }
@@ -604,6 +628,8 @@ func FromChatRequest(r ChatCompletionRequest) (*api.ChatRequest, error) {
 		Stream:          &r.Stream,
 		Tools:           r.Tools,
 		Think:           think,
+		Logprobs:        r.Logprobs != nil && *r.Logprobs,
+		TopLogprobs:     r.TopLogprobs,
 		DebugRenderOnly: r.DebugRenderOnly,
 	}, nil
 }
@@ -680,12 +706,21 @@ func FromCompleteRequest(r CompletionRequest) (api.GenerateRequest, error) {
 		options["top_p"] = 1.0
 	}
 
+	var logprobs bool
+	var topLogprobs int
+	if r.Logprobs != nil && *r.Logprobs > 0 {
+		logprobs = true
+		topLogprobs = *r.Logprobs
+	}
+
 	return api.GenerateRequest{
 		Model:           r.Model,
 		Prompt:          r.Prompt,
 		Options:         options,
 		Stream:          &r.Stream,
 		Suffix:          r.Suffix,
+		Logprobs:        logprobs,
+		TopLogprobs:     topLogprobs,
 		DebugRenderOnly: r.DebugRenderOnly,
 	}, nil
 }
diff --git a/openai/openai_test.go b/openai/openai_test.go
index 6a42f915..51e243de 100644
--- a/openai/openai_test.go
+++ b/openai/openai_test.go
@@ -3,6 +3,7 @@ package openai
 import (
 	"encoding/base64"
 	"testing"
+	"time"
 
 	"github.com/google/go-cmp/cmp"
 
@@ -218,3 +219,218 @@ func TestToToolCallsPreservesIDs(t *testing.T) {
 		t.Errorf("input tool calls mutated (-want +got):\n%s", diff)
 	}
 }
+
+func TestFromChatRequest_WithLogprobs(t *testing.T) {
+	trueVal := true
+
+	req := ChatCompletionRequest{
+		Model: "test-model",
+		Messages: []Message{
+			{Role: "user", Content: "Hello"},
+		},
+		Logprobs:    &trueVal,
+		TopLogprobs: 5,
+	}
+
+	result, err := FromChatRequest(req)
+	if err != nil {
+		t.Fatalf("unexpected error: %v", err)
+	}
+
+	if !result.Logprobs {
+		t.Error("expected Logprobs to be true")
+	}
+
+	if result.TopLogprobs != 5 {
+		t.Errorf("expected TopLogprobs to be 5, got %d", result.TopLogprobs)
+	}
+}
+
+func TestFromChatRequest_LogprobsDefault(t *testing.T) {
+	req := ChatCompletionRequest{
+		Model: "test-model",
+		Messages: []Message{
+			{Role: "user", Content: "Hello"},
+		},
+	}
+
+	result, err := FromChatRequest(req)
+	if err != nil {
+		t.Fatalf("unexpected error: %v", err)
+	}
+
+	if result.Logprobs {
+		t.Error("expected Logprobs to be false by default")
+	}
+
+	if result.TopLogprobs != 0 {
+		t.Errorf("expected TopLogprobs to be 0 by default, got %d", result.TopLogprobs)
+	}
+}
+
+func TestFromCompleteRequest_WithLogprobs(t *testing.T) {
+	logprobsVal := 5
+
+	req := CompletionRequest{
+		Model:    "test-model",
+		Prompt:   "Hello",
+		Logprobs: &logprobsVal,
+	}
+
+	result, err := FromCompleteRequest(req)
+	if err != nil {
+		t.Fatalf("unexpected error: %v", err)
+	}
+
+	if !result.Logprobs {
+		t.Error("expected Logprobs to be true")
+	}
+
+	if result.TopLogprobs != 5 {
+		t.Errorf("expected TopLogprobs to be 5, got %d", result.TopLogprobs)
+	}
+}
+
+func TestToChatCompletion_WithLogprobs(t *testing.T) {
+	createdAt := time.Unix(1234567890, 0)
+	resp := api.ChatResponse{
+		Model:     "test-model",
+		CreatedAt: createdAt,
+		Message:   api.Message{Role: "assistant", Content: "Hello there"},
+		Logprobs: []api.Logprob{
+			{
+				TokenLogprob: api.TokenLogprob{
+					Token:   "Hello",
+					Logprob: -0.5,
+				},
+				TopLogprobs: []api.TokenLogprob{
+					{Token: "Hello", Logprob: -0.5},
+					{Token: "Hi", Logprob: -1.2},
+				},
+			},
+			{
+				TokenLogprob: api.TokenLogprob{
+					Token:   " there",
+					Logprob: -0.3,
+				},
+				TopLogprobs: []api.TokenLogprob{
+					{Token: " there", Logprob: -0.3},
+					{Token: " world", Logprob: -1.5},
+				},
+			},
+		},
+		Done: true,
+		Metrics: api.Metrics{
+			PromptEvalCount: 5,
+			EvalCount:       2,
+		},
+	}
+
+	id := "test-id"
+
+	result := ToChatCompletion(id, resp)
+
+	if result.Id != id {
+		t.Errorf("expected Id %q, got %q", id, result.Id)
+	}
+
+	if result.Created != 1234567890 {
+		t.Errorf("expected Created %d, got %d", int64(1234567890), result.Created)
+	}
+
+	if len(result.Choices) != 1 {
+		t.Fatalf("expected 1 choice, got %d", len(result.Choices))
+	}
+
+	choice := result.Choices[0]
+	if choice.Message.Content != "Hello there" {
+		t.Errorf("expected content %q, got %q", "Hello there", choice.Message.Content)
+	}
+
+	if choice.Logprobs == nil {
+		t.Fatal("expected Logprobs to be present")
+	}
+
+	if len(choice.Logprobs.Content) != 2 {
+		t.Fatalf("expected 2 logprobs, got %d", len(choice.Logprobs.Content))
+	}
+
+	// Verify first logprob
+	if choice.Logprobs.Content[0].Token != "Hello" {
+		t.Errorf("expected first token %q, got %q", "Hello", choice.Logprobs.Content[0].Token)
+	}
+	if choice.Logprobs.Content[0].Logprob != -0.5 {
+		t.Errorf("expected first logprob -0.5, got %f", choice.Logprobs.Content[0].Logprob)
+	}
+	if len(choice.Logprobs.Content[0].TopLogprobs) != 2 {
+		t.Errorf("expected 2 top_logprobs, got %d", len(choice.Logprobs.Content[0].TopLogprobs))
+	}
+
+	// Verify second logprob
+	if choice.Logprobs.Content[1].Token != " there" {
+		t.Errorf("expected second token %q, got %q", " there", choice.Logprobs.Content[1].Token)
+	}
+}
+
+func TestToChatCompletion_WithoutLogprobs(t *testing.T) {
+	createdAt := time.Unix(1234567890, 0)
+	resp := api.ChatResponse{
+		Model:     "test-model",
+		CreatedAt: createdAt,
+		Message:   api.Message{Role: "assistant", Content: "Hello"},
+		Done:      true,
+		Metrics: api.Metrics{
+			PromptEvalCount: 5,
+			EvalCount:       1,
+		},
+	}
+
+	id := "test-id"
+
+	result := ToChatCompletion(id, resp)
+
+	if len(result.Choices) != 1 {
+		t.Fatalf("expected 1 choice, got %d", len(result.Choices))
+	}
+
+	// When no logprobs, Logprobs should be nil
+	if result.Choices[0].Logprobs != nil {
+		t.Error("expected Logprobs to be nil when not requested")
+	}
+}
+
+func TestFromChatRequest_TopLogprobsRange(t *testing.T) {
+	tests := []struct {
+		name        string
+		topLogprobs int
+		expectValid bool
+	}{
+		{name: "valid: 0", topLogprobs: 0, expectValid: true},
+		{name: "valid: 1", topLogprobs: 1, expectValid: true},
+		{name: "valid: 10", topLogprobs: 10, expectValid: true},
+		{name: "valid: 20", topLogprobs: 20, expectValid: true},
+	}
+
+	for _, tt := range tests {
+		t.Run(tt.name, func(t *testing.T) {
+			trueVal := true
+			req := ChatCompletionRequest{
+				Model: "test-model",
+				Messages: []Message{
+					{Role: "user", Content: "Hello"},
+				},
+				Logprobs:    &trueVal,
+				TopLogprobs: tt.topLogprobs,
+			}
+
+			result, err := FromChatRequest(req)
+			if err != nil {
+				t.Fatalf("unexpected error: %v", err)
+			}
+
+			if result.TopLogprobs != tt.topLogprobs {
+				t.Errorf("expected TopLogprobs %d, got %d", tt.topLogprobs, result.TopLogprobs)
+			}
+		})
+	}
+}
diff --git a/runner/common/logprob.go b/runner/common/logprob.go
new file mode 100644
index 00000000..a0d764a3
--- /dev/null
+++ b/runner/common/logprob.go
@@ -0,0 +1,79 @@
+package common
+
+import (
+	"math"
+	"sort"
+
+	"github.com/ollama/ollama/llm"
+)
+
+// TokenDecoderFunc is a function that converts token IDs to text.
+type TokenDecoderFunc func(tokenID int) string
+
+// CalculateLogprobs converts raw logits to log probabilities and finds top K tokens.
+// It uses numerically stable softmax to compute log probabilities.
+func CalculateLogprobs(logits []float32, selectedToken int, topK int, decoder TokenDecoderFunc) []llm.Logprob {
+	if len(logits) == 0 {
+		return nil
+	}
+
+	// Step 1: Convert logits to log probabilities using numerically stable softmax
+	maxLogit := logits[0]
+	for _, logit := range logits[1:] {
+		if logit > maxLogit {
+			maxLogit = logit
+		}
+	}
+
+	var sumExp float64
+	for _, logit := range logits {
+		sumExp += math.Exp(float64(logit - maxLogit))
+	}
+	logSumExp := float32(math.Log(sumExp))
+
+	logProbs := make([]float32, len(logits))
+	for i, logit := range logits {
+		logProbs[i] = (logit - maxLogit) - logSumExp
+	}
+
+	// Step 2: Get selected token's information
+	selectedLogprob := logProbs[selectedToken]
+	selectedText := decoder(selectedToken)
+
+	result := llm.Logprob{
+		TokenLogprob: llm.TokenLogprob{
+			Token:   selectedText,
+			Logprob: float64(selectedLogprob),
+		},
+	}
+
+	// Step 3: If topK requested, find the top K tokens
+	if topK > 0 {
+		type tokenLogprobPair struct {
+			tokenID int
+			logprob float32
+		}
+
+		pairs := make([]tokenLogprobPair, len(logProbs))
+		for i, lp := range logProbs {
+			pairs[i] = tokenLogprobPair{tokenID: i, logprob: lp}
+		}
+
+		sort.Slice(pairs, func(i, j int) bool {
+			return pairs[i].logprob > pairs[j].logprob
+		})
+
+		k := min(topK, len(pairs))
+		topLogprobs := make([]llm.TokenLogprob, k)
+		for i := range k {
+			tokenText := decoder(pairs[i].tokenID)
+			topLogprobs[i] = llm.TokenLogprob{
+				Token:   tokenText,
+				Logprob: float64(pairs[i].logprob),
+			}
+		}
+		result.TopLogprobs = topLogprobs
+	}
+
+	return []llm.Logprob{result}
+}
diff --git a/runner/common/logprob_test.go b/runner/common/logprob_test.go
new file mode 100644
index 00000000..c798f3f4
--- /dev/null
+++ b/runner/common/logprob_test.go
@@ -0,0 +1,498 @@
+package common
+
+import (
+	"math"
+	"testing"
+
+	"github.com/ollama/ollama/llm"
+)
+
+func TestCalculateLogprobs(t *testing.T) {
+	tokens := map[int]string{
+		0: "hello",
+		1: "hi",
+		2: "hey",
+		3: "world",
+	}
+	decoder := func(tokenID int) string {
+		if text, ok := tokens[tokenID]; ok {
+			return text
+		}
+		return ""
+	}
+
+	tests := []struct {
+		name          string
+		logits        []float32
+		selectedToken int
+		topK          int
+		wantLen       int
+		wantToken     string
+	}{
+		{
+			name:          "Empty logits",
+			logits:        []float32{},
+			selectedToken: 0,
+			topK:          0,
+			wantLen:       0,
+		},
+		{
+			name:          "Single token without top logprobs",
+			logits:        []float32{1.0, 0.5, 0.3, 0.1},
+			selectedToken: 0,
+			topK:          0,
+			wantLen:       1,
+			wantToken:     "hello",
+		},
+		{
+			name:          "Single token with top logprobs",
+			logits:        []float32{1.0, 0.5, 0.3, 0.1},
+			selectedToken: 0,
+			topK:          3,
+			wantLen:       1,
+			wantToken:     "hello",
+		},
+	}
+
+	for _, tt := range tests {
+		t.Run(tt.name, func(t *testing.T) {
+			result := CalculateLogprobs(tt.logits, tt.selectedToken, tt.topK, decoder)
+			if len(result) != tt.wantLen {
+				t.Errorf("CalculateLogprobs() returned %d results, want %d", len(result), tt.wantLen)
+			}
+			if tt.wantLen > 0 && result[0].Token != tt.wantToken {
+				t.Errorf("CalculateLogprobs() token = %s, want %s", result[0].Token, tt.wantToken)
+			}
+			if tt.topK > 0 && len(result) > 0 {
+				if len(result[0].TopLogprobs) != tt.topK {
+					t.Errorf("CalculateLogprobs() top logprobs count = %d, want %d", len(result[0].TopLogprobs), tt.topK)
+				}
+			}
+		})
+	}
+}
+
+func TestCalculateLogprobsNumericalStability(t *testing.T) {
+	tokens := map[int]string{
+		0: "a",
+		1: "b",
+		2: "c",
+	}
+	decoder := func(tokenID int) string {
+		if text, ok := tokens[tokenID]; ok {
+			return text
+		}
+		return ""
+	}
+
+	// Test with very large logits to ensure numerical stability
+	logits := []float32{1000.0, 999.0, 998.0}
+	result := CalculateLogprobs(logits, 0, 3, decoder)
+
+	if len(result) != 1 {
+		t.Fatalf("Expected 1 result, got %d", len(result))
+	}
+
+	// Check that log probabilities are finite and reasonable
+	if math.IsInf(result[0].Logprob, 0) || math.IsNaN(result[0].Logprob) {
+		t.Errorf("Selected token logprob is not finite: %f", result[0].Logprob)
+	}
+
+	for i, tlp := range result[0].TopLogprobs {
+		if math.IsInf(tlp.Logprob, 0) || math.IsNaN(tlp.Logprob) {
+			t.Errorf("Top logprob[%d] is not finite: %f", i, tlp.Logprob)
+		}
+	}
+
+	// Top logprobs should be in descending order
+	for i := 1; i < len(result[0].TopLogprobs); i++ {
+		if result[0].TopLogprobs[i].Logprob > result[0].TopLogprobs[i-1].Logprob {
+			t.Errorf("Top logprobs not in descending order: %f > %f",
+				result[0].TopLogprobs[i].Logprob, result[0].TopLogprobs[i-1].Logprob)
+		}
+	}
+}
+
+func TestCalculateLogprobsProbabilityCorrectness(t *testing.T) {
+	tokens := map[int]string{
+		0: "hello",
+		1: "world",
+		2: "foo",
+		3: "bar",
+	}
+	decoder := func(tokenID int) string {
+		if text, ok := tokens[tokenID]; ok {
+			return text
+		}
+		return ""
+	}
+
+	tests := []struct {
+		name          string
+		logits        []float32
+		selectedToken int
+		topK          int
+	}{
+		{
+			name:          "Uniform logits",
+			logits:        []float32{1.0, 1.0, 1.0, 1.0},
+			selectedToken: 0,
+			topK:          4,
+		},
+		{
+			name:          "Different logits",
+			logits:        []float32{2.0, 1.0, 0.5, 0.1},
+			selectedToken: 0,
+			topK:          4,
+		},
+		{
+			name:          "Negative logits",
+			logits:        []float32{-1.0, -2.0, -3.0, -4.0},
+			selectedToken: 0,
+			topK:          4,
+		},
+		{
+			name:          "Mixed logits",
+			logits:        []float32{5.0, -5.0, 0.0, 2.5},
+			selectedToken: 0,
+			topK:          4,
+		},
+	}
+
+	for _, tt := range tests {
+		t.Run(tt.name, func(t *testing.T) {
+			result := CalculateLogprobs(tt.logits, tt.selectedToken, tt.topK, decoder)
+
+			if len(result) != 1 {
+				t.Fatalf("Expected 1 result, got %d", len(result))
+			}
+
+			// Verify all probabilities are non-positive (log probabilities should be <= 0)
+			if result[0].Logprob > 0 {
+				t.Errorf("Selected token logprob should be <= 0, got %f", result[0].Logprob)
+			}
+
+			for i, tlp := range result[0].TopLogprobs {
+				if tlp.Logprob > 0 {
+					t.Errorf("Top logprob[%d] should be <= 0, got %f", i, tlp.Logprob)
+				}
+			}
+
+			// Verify that probabilities sum to approximately 1
+			// Sum of exp(logprob) for all tokens should equal 1
+			var probSum float64
+			for _, lp := range result[0].TopLogprobs {
+				probSum += math.Exp(lp.Logprob)
+			}
+
+			// For uniform logits, each probability should be 1/n
+			if tt.name == "Uniform logits" {
+				expectedProb := 1.0 / float64(len(tt.logits))
+				actualProb := math.Exp(result[0].Logprob)
+				if math.Abs(actualProb-expectedProb) > 1e-6 {
+					t.Errorf("For uniform logits, expected probability %f, got %f",
+						expectedProb, actualProb)
+				}
+			}
+
+			// Verify top logprobs are sorted in descending order
+			for i := 1; i < len(result[0].TopLogprobs); i++ {
+				if result[0].TopLogprobs[i].Logprob > result[0].TopLogprobs[i-1].Logprob {
+					t.Errorf("Top logprobs not sorted: position %d (%f) > position %d (%f)",
+						i, result[0].TopLogprobs[i].Logprob,
+						i-1, result[0].TopLogprobs[i-1].Logprob)
+				}
+			}
+
+			// Verify the selected token appears in top logprobs
+			selectedText := decoder(tt.selectedToken)
+			found := false
+			for _, tlp := range result[0].TopLogprobs {
+				if tlp.Token == selectedText {
+					found = true
+					// The logprob in top logprobs should match the selected token's logprob
+					if math.Abs(tlp.Logprob-result[0].Logprob) > 1e-6 {
+						t.Errorf("Selected token logprob mismatch: main=%f, in top=%f",
+							result[0].Logprob, tlp.Logprob)
+					}
+					break
+				}
+			}
+			if !found {
+				t.Errorf("Selected token %q not found in top logprobs", selectedText)
+			}
+		})
+	}
+}
+
+func TestCalculateLogprobsSoftmaxCorrectness(t *testing.T) {
+	// Test that softmax calculation is correct by verifying probabilities sum to 1
+	decoder := func(tokenID int) string {
+		return string(rune('A' + tokenID))
+	}
+
+	tests := []struct {
+		name   string
+		logits []float32
+	}{
+		{
+			name:   "Small vocabulary",
+			logits: []float32{1.0, 2.0, 3.0},
+		},
+		{
+			name:   "Large differences",
+			logits: []float32{10.0, 0.0, -10.0},
+		},
+		{
+			name:   "All equal",
+			logits: []float32{5.0, 5.0, 5.0, 5.0, 5.0},
+		},
+		{
+			name:   "Very large values",
+			logits: []float32{500.0, 499.0, 498.0},
+		},
+		{
+			name:   "Very small values",
+			logits: []float32{-500.0, -499.0, -498.0},
+		},
+	}
+
+	for _, tt := range tests {
+		t.Run(tt.name, func(t *testing.T) {
+			// Calculate logprobs for all tokens
+			var totalProb float64
+			for i := range tt.logits {
+				result := CalculateLogprobs(tt.logits, i, 0, decoder)
+				if len(result) != 1 {
+					t.Fatalf("Expected 1 result, got %d", len(result))
+				}
+				prob := math.Exp(result[0].Logprob)
+				totalProb += prob
+
+				// Verify each probability is between 0 and 1
+				if prob < 0 || prob > 1 {
+					t.Errorf("Token %d probability %f is out of range [0, 1]", i, prob)
+				}
+			}
+
+			// Total probability should be very close to 1.0 (allowing for floating point errors)
+			if math.Abs(totalProb-1.0) > 1e-5 {
+				t.Errorf("Total probability sum is %f, expected 1.0", totalProb)
+			}
+		})
+	}
+}
+
+func TestCalculateLogprobsSelectedTokenCorrectness(t *testing.T) {
+	decoder := func(tokenID int) string {
+		return string(rune('A' + tokenID))
+	}
+
+	logits := []float32{3.0, 1.0, 2.0, 0.5}
+
+	// Test that selecting different tokens gives the correct probabilities
+	// and that the highest logit has the highest probability
+	maxLogitIndex := 0
+	maxLogitValue := logits[0]
+	for i, logit := range logits[1:] {
+		if logit > maxLogitValue {
+			maxLogitValue = logit
+			maxLogitIndex = i + 1
+		}
+	}
+
+	var maxProb float64
+	var maxProbIndex int
+
+	for i := range logits {
+		result := CalculateLogprobs(logits, i, 0, decoder)
+		prob := math.Exp(result[0].Logprob)
+
+		if prob > maxProb {
+			maxProb = prob
+			maxProbIndex = i
+		}
+
+		// Verify the token matches
+		expectedToken := decoder(i)
+		if result[0].Token != expectedToken {
+			t.Errorf("Token %d: expected token %q, got %q", i, expectedToken, result[0].Token)
+		}
+	}
+
+	// The token with the highest logit should have the highest probability
+	if maxProbIndex != maxLogitIndex {
+		t.Errorf("Token with highest probability (%d) doesn't match token with highest logit (%d)",
+			maxProbIndex, maxLogitIndex)
+	}
+}
+
+func TestCalculateLogprobsTopKOrdering(t *testing.T) {
+	tokens := map[int]string{
+		0: "first",
+		1: "second",
+		2: "third",
+		3: "fourth",
+		4: "fifth",
+	}
+	decoder := func(tokenID int) string {
+		return tokens[tokenID]
+	}
+
+	// Logits in non-sorted order
+	logits := []float32{2.0, 5.0, 1.0, 4.0, 3.0}
+	// Expected order by probability: 1 (5.0), 3 (4.0), 4 (3.0), 0 (2.0), 2 (1.0)
+	expectedOrder := []string{"second", "fourth", "fifth", "first", "third"}
+
+	result := CalculateLogprobs(logits, 0, 5, decoder)
+
+	if len(result) != 1 {
+		t.Fatalf("Expected 1 result, got %d", len(result))
+	}
+
+	if len(result[0].TopLogprobs) != 5 {
+		t.Fatalf("Expected 5 top logprobs, got %d", len(result[0].TopLogprobs))
+	}
+
+	// Verify ordering matches expected
+	for i, tlp := range result[0].TopLogprobs {
+		if tlp.Token != expectedOrder[i] {
+			t.Errorf("Position %d: expected token %q, got %q", i, expectedOrder[i], tlp.Token)
+		}
+	}
+
+	// Verify probabilities are in descending order
+	for i := 1; i < len(result[0].TopLogprobs); i++ {
+		if result[0].TopLogprobs[i].Logprob > result[0].TopLogprobs[i-1].Logprob {
+			t.Errorf("Probabilities not in descending order at position %d: %f > %f",
+				i, result[0].TopLogprobs[i].Logprob, result[0].TopLogprobs[i-1].Logprob)
+		}
+	}
+}
+
+func TestLogprobsWithStopSequences(t *testing.T) {
+	tests := []struct {
+		name              string
+		pendingResponses  []string
+		pendingLogprobs   []llm.Logprob
+		stop              string
+		expectedResponses []string
+		expectedLogprobs  int
+	}{
+		{
+			name:             "Single token stop",
+			pendingResponses: []string{"Hello", " world", "!"},
+			pendingLogprobs: []llm.Logprob{
+				{TokenLogprob: llm.TokenLogprob{Token: "Hello", Logprob: -0.1}},
+				{TokenLogprob: llm.TokenLogprob{Token: " world", Logprob: -0.2}},
+				{TokenLogprob: llm.TokenLogprob{Token: "!", Logprob: -0.3}},
+			},
+			stop:              "!",
+			expectedResponses: []string{"Hello", " world"},
+			expectedLogprobs:  2,
+		},
+		{
+			name:             "Multi-token stop sequence",
+			pendingResponses: []string{"Hello", " ", "there", "STOP"},
+			pendingLogprobs: []llm.Logprob{
+				{TokenLogprob: llm.TokenLogprob{Token: "Hello", Logprob: -0.1}},
+				{TokenLogprob: llm.TokenLogprob{Token: " ", Logprob: -0.2}},
+				{TokenLogprob: llm.TokenLogprob{Token: "there", Logprob: -0.3}},
+				{TokenLogprob: llm.TokenLogprob{Token: "STOP", Logprob: -0.4}},
+			},
+			stop:              "STOP",
+			expectedResponses: []string{"Hello", " ", "there"},
+			expectedLogprobs:  3,
+		},
+		{
+			name:             "Partial token stop",
+			pendingResponses: []string{"Hello", " the", "re!"},
+			pendingLogprobs: []llm.Logprob{
+				{TokenLogprob: llm.TokenLogprob{Token: "Hello", Logprob: -0.1}},
+				{TokenLogprob: llm.TokenLogprob{Token: " the", Logprob: -0.2}},
+				{TokenLogprob: llm.TokenLogprob{Token: "re!", Logprob: -0.3}},
+			},
+			stop:              "there!",
+			expectedResponses: []string{"Hello", " "},
+			expectedLogprobs:  2,
+		},
+		{
+			name:             "Stop at beginning of last token",
+			pendingResponses: []string{"Hello", " world", "END"},
+			pendingLogprobs: []llm.Logprob{
+				{TokenLogprob: llm.TokenLogprob{Token: "Hello", Logprob: -0.1}},
+				{TokenLogprob: llm.TokenLogprob{Token: " world", Logprob: -0.2}},
+				{TokenLogprob: llm.TokenLogprob{Token: "END", Logprob: -0.3}},
+			},
+			stop:              "END",
+			expectedResponses: []string{"Hello", " world"},
+			expectedLogprobs:  2,
+		},
+		{
+			name:             "Multi-token stop across tokens",
+			pendingResponses: []string{"Text", " ", "with", " ", "stop", " ", "word"},
+			pendingLogprobs: []llm.Logprob{
+				{TokenLogprob: llm.TokenLogprob{Token: "Text", Logprob: -0.1}},
+				{TokenLogprob: llm.TokenLogprob{Token: " ", Logprob: -0.2}},
+				{TokenLogprob: llm.TokenLogprob{Token: "with", Logprob: -0.3}},
+				{TokenLogprob: llm.TokenLogprob{Token: " ", Logprob: -0.4}},
+				{TokenLogprob: llm.TokenLogprob{Token: "stop", Logprob: -0.5}},
+				{TokenLogprob: llm.TokenLogprob{Token: " ", Logprob: -0.6}},
+				{TokenLogprob: llm.TokenLogprob{Token: "word", Logprob: -0.7}},
+			},
+			stop:              "stop word",
+			expectedResponses: []string{"Text", " ", "with", " "},
+			expectedLogprobs:  4,
+		},
+	}
+
+	for _, tt := range tests {
+		t.Run(tt.name, func(t *testing.T) {
+			// Simulate the stop sequence detection and truncation
+			origLen := len(tt.pendingResponses)
+			responses, tokenTruncated := TruncateStop(tt.pendingResponses, tt.stop)
+			newLen := len(responses)
+
+			// Simulate logprobs truncation
+			logprobs := make([]llm.Logprob, len(tt.pendingLogprobs))
+			copy(logprobs, tt.pendingLogprobs)
+
+			origLogprobsLen := len(logprobs)
+			numTokensRemoved := origLen - newLen
+			newLogprobsLen := origLogprobsLen - numTokensRemoved
+			if newLogprobsLen < 0 {
+				newLogprobsLen = 0
+			}
+			logprobs = logprobs[:newLogprobsLen]
+
+			// Verify responses were truncated correctly
+			if len(responses) != len(tt.expectedResponses) {
+				t.Errorf("Expected %d responses, got %d", len(tt.expectedResponses), len(responses))
+			}
+
+			// Verify logprobs count matches truncated responses
+			if len(logprobs) != tt.expectedLogprobs {
+				t.Errorf("Expected %d logprobs after truncation, got %d", tt.expectedLogprobs, len(logprobs))
+			}
+
+			// Verify logprobs count matches response count
+			if len(logprobs) != len(responses) {
+				t.Errorf("Logprobs count (%d) doesn't match responses count (%d)", len(logprobs), len(responses))
+			}
+
+			// Verify the correct logprobs were kept (skip last token if it was truncated)
+			// When tokenTruncated is true, the last response token may not match the logprob token
+			checkLen := len(logprobs)
+			if tokenTruncated && checkLen > 0 {
+				checkLen-- // Skip checking the last token when it was partially truncated
+			}
+
+			for i := range checkLen {
+				if i < len(responses) && logprobs[i].Token != responses[i] {
+					t.Errorf("Logprob[%d] token %q doesn't match response[%d] %q",
+						i, logprobs[i].Token, i, responses[i])
+				}
+			}
+		})
+	}
+}
diff --git a/runner/llamarunner/runner.go b/runner/llamarunner/runner.go
index 87b43256..a23ddd61 100644
--- a/runner/llamarunner/runner.go
+++ b/runner/llamarunner/runner.go
@@ -12,6 +12,7 @@ import (
 	"net/http"
 	"os"
 	"regexp"
+	"sort"
 	"strconv"
 	"strings"
 	"sync"
@@ -28,6 +29,12 @@ import (
 	"github.com/ollama/ollama/runner/common"
 )
 
+// response contains a piece of generated text along with optional logprobs
+type response struct {
+	content  string
+	logprobs []llm.Logprob
+}
+
 // input is an element of the prompt to process, either
 // a token or an image embedding (generated from a vision projector)
 type input struct {
@@ -53,11 +60,14 @@ type Sequence struct {
 	// tokens that have been generated but not returned yet (e.g. for stop sequences)
 	pendingResponses []string
 
+	// logprobs for tokens that haven't been returned yet
+	pendingLogprobs []llm.Logprob
+
 	// input cache being used by this sequence
 	cache *InputCacheSlot
 
 	// channel to send responses over
-	responses chan string
+	responses chan response
 
 	// channel to stop decoding (such as if the remote connection is closed)
 	quit chan bool
@@ -84,6 +94,10 @@ type Sequence struct {
 
 	doneReason llm.DoneReason
 
+	// logprobs configuration
+	logprobs    bool
+	topLogprobs int
+
 	// Metrics
 	processingDuration time.Duration
 	generationDuration time.Duration
@@ -99,6 +113,8 @@ type NewSequenceParams struct {
 	embedding      bool
 	shift          bool
 	truncate       bool
+	logprobs       bool
+	topLogprobs    int
 }
 
 var errorInputTooLong = errors.New("the input length exceeds the context length")
@@ -155,7 +171,7 @@ func (s *Server) NewSequence(prompt string, images []llm.ImageData, params NewSe
 		numPromptInputs:  len(inputs),
 		numPredict:       params.numPredict,
 		pendingResponses: make([]string, 0),
-		responses:        make(chan string, 100),
+		responses:        make(chan response, 100),
 		quit:             make(chan bool, 1),
 		embedding:        make(chan []float32, 1),
 		samplingCtx:      sc,
@@ -163,9 +179,16 @@ func (s *Server) NewSequence(prompt string, images []llm.ImageData, params NewSe
 		stop:             params.stop,
 		numKeep:          params.numKeep,
 		shift:            params.shift,
+		logprobs:         params.logprobs,
+		topLogprobs:      params.topLogprobs,
 	}, nil
 }
 
+// calculateLogprobsLlama converts raw logits to log probabilities and finds top K tokens
+func calculateLogprobsLlama(logits []float32, selectedToken int, topK int, model *llama.Model) []llm.Logprob {
+	return common.CalculateLogprobs(logits, selectedToken, topK, model.TokenToPiece)
+}
+
 // inputs processes the prompt and images into a list of inputs
 // by splitting the prompt on [img-<n>] tags, tokenizing text and
 // generating image embeddings for each image
@@ -294,7 +317,9 @@ func (s *Server) allNil() bool {
 
 func flushPending(seq *Sequence) bool {
 	joined := strings.Join(seq.pendingResponses, "")
+	logprobs := seq.pendingLogprobs
 	seq.pendingResponses = []string{}
+	seq.pendingLogprobs = []llm.Logprob{}
 
 	// Check if there are any partial UTF-8 characters remaining.
 	// We already check and queue as we are generating but some may
@@ -311,7 +336,7 @@ func flushPending(seq *Sequence) bool {
 	}
 
 	select {
-	case seq.responses <- joined:
+	case seq.responses <- response{content: joined, logprobs: logprobs}:
 		return true
 	case <-seq.quit:
 		return false
@@ -526,6 +551,15 @@ func (s *Server) processBatch(tokenBatch *llama.Batch, embedBatch *llama.Batch)
 			continue
 		}
 
+		// Calculate logprobs if requested (after EOS check to avoid logprobs for EOS tokens)
+		if seq.logprobs {
+			logits := s.lc.GetLogitsIth(seq.iBatch)
+			if logits != nil {
+				logprobs := calculateLogprobsLlama(logits, token, seq.topLogprobs, s.model)
+				seq.pendingLogprobs = append(seq.pendingLogprobs, logprobs...)
+			}
+		}
+
 		seq.inputs = []input{{token: token}}
 
 		seq.pendingResponses = append(seq.pendingResponses, piece)
@@ -539,6 +573,17 @@ func (s *Server) processBatch(tokenBatch *llama.Batch, embedBatch *llama.Batch)
 			seq.pendingResponses, tokenTruncated = common.TruncateStop(seq.pendingResponses, stop)
 			newLen := len(seq.pendingResponses)
 
+			// Truncate logprobs to match the truncated responses
+			if seq.logprobs {
+				origLogprobsLen := len(seq.pendingLogprobs)
+				numTokensRemoved := origLen - newLen
+				newLogprobsLen := origLogprobsLen - numTokensRemoved
+				if newLogprobsLen < 0 {
+					newLogprobsLen = 0
+				}
+				seq.pendingLogprobs = seq.pendingLogprobs[:newLogprobsLen]
+			}
+
 			// Update the cache based on the tokens that will be returned:
 			// - We have 1 token more than is currently in the cache because
 			// the last one generated wasn't submitted to Decode
@@ -618,6 +663,8 @@ func (s *Server) completion(w http.ResponseWriter, r *http.Request) {
 		embedding:      false,
 		shift:          req.Shift,
 		truncate:       req.Truncate,
+		logprobs:       req.Logprobs,
+		topLogprobs:    req.TopLogprobs,
 	})
 	if err != nil {
 		if errors.Is(err, errorInputTooLong) {
@@ -669,10 +716,11 @@ func (s *Server) completion(w http.ResponseWriter, r *http.Request) {
 		case <-r.Context().Done():
 			close(seq.quit)
 			return
-		case content, ok := <-seq.responses:
+		case resp, ok := <-seq.responses:
 			if ok {
 				if err := json.NewEncoder(w).Encode(&llm.CompletionResponse{
-					Content: content,
+					Content:  resp.content,
+					Logprobs: resp.logprobs,
 				}); err != nil {
 					http.Error(w, fmt.Sprintf("failed to encode response: %v", err), http.StatusInternalServerError)
 					close(seq.quit)
@@ -853,19 +901,24 @@ func (s *Server) load(w http.ResponseWriter, r *http.Request) {
 		s.seqs = make([]*Sequence, s.parallel)
 		s.seqsSem = semaphore.NewWeighted(int64(s.parallel))
 
-		gpuIDs := llama.EnumerateGPUs()
-		tensorSplit := make([]float32, len(gpuIDs))
 		numGPU := 0
-		for i := range gpuIDs {
-			for _, layers := range req.GPULayers {
-				if gpuIDs[i] == layers.DeviceID {
-					tensorSplit[i] = float32(len(layers.Layers))
+		var tensorSplit []float32
+		var llamaIDs []uint64
+
+		gpuIDs := llama.EnumerateGPUs()
+		sort.Sort(req.GPULayers)
+		for _, layers := range req.GPULayers {
+			for i := range gpuIDs {
+				if gpuIDs[i].DeviceID == layers.DeviceID {
 					numGPU += len(layers.Layers)
+					tensorSplit = append(tensorSplit, float32(len(layers.Layers)))
+					llamaIDs = append(llamaIDs, gpuIDs[i].LlamaID)
 				}
 			}
 		}
 
 		params := llama.ModelParams{
+			Devices:      llamaIDs,
 			NumGpuLayers: numGPU,
 			MainGpu:      req.MainGPU,
 			UseMmap:      req.UseMmap && len(req.LoraPath) == 0,
diff --git a/runner/ollamarunner/runner.go b/runner/ollamarunner/runner.go
index 3e8c1e22..15339086 100644
--- a/runner/ollamarunner/runner.go
+++ b/runner/ollamarunner/runner.go
@@ -41,6 +41,12 @@ import (
 	_ "github.com/ollama/ollama/model/models"
 )
 
+// response contains a piece of generated text along with optional logprobs
+type response struct {
+	content  string
+	logprobs []llm.Logprob
+}
+
 type Sequence struct {
 	// ctxs are used for allocating tensors that last the lifetime of the sequence, such as
 	// multimodal embeddings
@@ -61,11 +67,14 @@ type Sequence struct {
 	// tokens that have been generated but not returned yet (e.g. for stop sequences)
 	pendingResponses []string
 
+	// logprobs for tokens that haven't been returned yet
+	pendingLogprobs []llm.Logprob
+
 	// input cache being used by this sequence
 	cache *InputCacheSlot
 
 	// channel to send responses over
-	responses chan string
+	responses chan response
 
 	// channel to stop decoding (such as if the remote connection is closed)
 	quit chan bool
@@ -93,6 +102,10 @@ type Sequence struct {
 
 	doneReason llm.DoneReason
 
+	// logprobs configuration
+	logprobs    bool
+	topLogprobs int
+
 	// Metrics
 	startedAt, lastUpdatedAt time.Time
 	processingDuration       time.Duration
@@ -102,13 +115,15 @@ type Sequence struct {
 }
 
 type NewSequenceParams struct {
-	numPredict int
-	stop       []string
-	numKeep    int32
-	sampler    sample.Sampler
-	embedding  bool
-	shift      bool
-	truncate   bool
+	numPredict  int
+	stop        []string
+	numKeep     int32
+	sampler     sample.Sampler
+	embedding   bool
+	shift       bool
+	truncate    bool
+	logprobs    bool
+	topLogprobs int
 }
 
 var errorInputTooLong = errors.New("the input length exceeds the context length")
@@ -181,7 +196,7 @@ func (s *Server) NewSequence(prompt string, images []llm.ImageData, params NewSe
 		numPromptInputs:  len(inputs),
 		numPredict:       params.numPredict,
 		pendingResponses: make([]string, 0),
-		responses:        make(chan string, 100),
+		responses:        make(chan response, 100),
 		quit:             make(chan bool, 1),
 		embedding:        make(chan []float32, 1),
 		sampler:          params.sampler,
@@ -189,9 +204,20 @@ func (s *Server) NewSequence(prompt string, images []llm.ImageData, params NewSe
 		stop:             params.stop,
 		numKeep:          params.numKeep,
 		shift:            params.shift,
+		logprobs:         params.logprobs,
+		topLogprobs:      params.topLogprobs,
 	}, nil
 }
 
+// calculateLogprobs converts raw logits to log probabilities and finds top K tokens
+func calculateLogprobs(logits []float32, selectedToken int32, topK int, textProcessor model.TextProcessor) []llm.Logprob {
+	decoder := func(tokenID int) string {
+		text, _ := textProcessor.Decode([]int32{int32(tokenID)})
+		return text
+	}
+	return common.CalculateLogprobs(logits, int(selectedToken), topK, decoder)
+}
+
 // inputs processes the prompt and images into a list of inputs
 // by splitting the prompt on [img-<n>] tags, tokenizing text and
 // decoding images
@@ -371,7 +397,9 @@ func (s *Server) allNil() bool {
 
 func flushPending(seq *Sequence) bool {
 	joined := strings.Join(seq.pendingResponses, "")
+	logprobs := seq.pendingLogprobs
 	seq.pendingResponses = []string{}
+	seq.pendingLogprobs = []llm.Logprob{}
 
 	// Check if there are any partial UTF-8 characters remaining.
 	// We already check and queue as we are generating but some may
@@ -388,7 +416,7 @@ func flushPending(seq *Sequence) bool {
 	}
 
 	select {
-	case seq.responses <- joined:
+	case seq.responses <- response{content: joined, logprobs: logprobs}:
 		return true
 	case <-seq.quit:
 		return false
@@ -729,7 +757,8 @@ func (s *Server) computeBatch(activeBatch batchState) {
 		// sample a token
 		vocabSize := len(outputs) / activeBatch.batch.Outputs.Dim(0)
 		logutil.Trace("computeBatch: vocab details", "batchID", activeBatch.id, "seqIdx", i, "len(logits)", len(outputs), "len(activeBatch.batch.Outputs)", activeBatch.batch.Outputs.Dim(0), "vocabSize", vocabSize, "iBatches", iBatches)
-		token, err := seq.sampler.Sample(outputs[iBatches[i]*vocabSize : (iBatches[i]+1)*vocabSize])
+		logits := outputs[iBatches[i]*vocabSize : (iBatches[i]+1)*vocabSize]
+		token, err := seq.sampler.Sample(logits)
 		if err != nil {
 			panic("failed to sample token")
 		}
@@ -751,6 +780,12 @@ func (s *Server) computeBatch(activeBatch batchState) {
 			panic("failed to decode token")
 		}
 
+		// Calculate logprobs if requested (after EOS check to avoid logprobs for EOS tokens)
+		if seq.logprobs {
+			logprobs := calculateLogprobs(logits, token, seq.topLogprobs, s.model.(model.TextProcessor))
+			seq.pendingLogprobs = append(seq.pendingLogprobs, logprobs...)
+		}
+
 		seq.pendingResponses = append(seq.pendingResponses, piece)
 		sequence := strings.Join(seq.pendingResponses, "")
 
@@ -762,6 +797,17 @@ func (s *Server) computeBatch(activeBatch batchState) {
 			seq.pendingResponses, tokenTruncated = common.TruncateStop(seq.pendingResponses, stop)
 			newLen := len(seq.pendingResponses)
 
+			// Truncate logprobs to match the truncated responses
+			if seq.logprobs {
+				origLogprobsLen := len(seq.pendingLogprobs)
+				numTokensRemoved := origLen - newLen
+				newLogprobsLen := origLogprobsLen - numTokensRemoved
+				if newLogprobsLen < 0 {
+					newLogprobsLen = 0
+				}
+				seq.pendingLogprobs = seq.pendingLogprobs[:newLogprobsLen]
+			}
+
 			// Update the cache based on the tokens that will be returned:
 			// - We have 1 token more than is currently in the cache because
 			// the last one generated wasn't submitted to Decode
@@ -845,13 +891,15 @@ func (s *Server) completion(w http.ResponseWriter, r *http.Request) {
 	)
 
 	seq, err := s.NewSequence(req.Prompt, req.Images, NewSequenceParams{
-		numPredict: req.Options.NumPredict,
-		stop:       req.Options.Stop,
-		numKeep:    int32(req.Options.NumKeep),
-		sampler:    sampler,
-		embedding:  false,
-		shift:      req.Shift,
-		truncate:   req.Truncate,
+		numPredict:  req.Options.NumPredict,
+		stop:        req.Options.Stop,
+		numKeep:     int32(req.Options.NumKeep),
+		sampler:     sampler,
+		embedding:   false,
+		shift:       req.Shift,
+		truncate:    req.Truncate,
+		logprobs:    req.Logprobs,
+		topLogprobs: req.TopLogprobs,
 	})
 	if err != nil {
 		if errors.Is(err, errorInputTooLong) {
@@ -903,10 +951,11 @@ func (s *Server) completion(w http.ResponseWriter, r *http.Request) {
 		case <-r.Context().Done():
 			close(seq.quit)
 			return
-		case content, ok := <-seq.responses:
+		case resp, ok := <-seq.responses:
 			if ok {
 				if err := json.NewEncoder(w).Encode(&llm.CompletionResponse{
-					Content: content,
+					Content:  resp.content,
+					Logprobs: resp.logprobs,
 				}); err != nil {
 					http.Error(w, fmt.Sprintf("failed to encode response: %v", err), http.StatusInternalServerError)
 					close(seq.quit)
diff --git a/scripts/build_linux.sh b/scripts/build_linux.sh
index 8287c11c..618722d1 100755
--- a/scripts/build_linux.sh
+++ b/scripts/build_linux.sh
@@ -13,13 +13,12 @@ set -eu
 . $(dirname $0)/env.sh
 
 mkdir -p dist
-NOVULKAN=${NOVULKAN:-""}
 
 docker buildx build \
         --output type=local,dest=./dist/ \
         --platform=${PLATFORM} \
         ${OLLAMA_COMMON_BUILD_ARGS} \
-        --target archive${NOVULKAN} \
+        --target archive \
         -f Dockerfile \
         .
 
diff --git a/server/logprob.go b/server/logprob.go
new file mode 100644
index 00000000..4a6e1408
--- /dev/null
+++ b/server/logprob.go
@@ -0,0 +1,44 @@
+package server
+
+import (
+	"github.com/ollama/ollama/api"
+	"github.com/ollama/ollama/llm"
+)
+
+// toAPILogprobs converts llm.Logprobs to api.Logprobs
+func toAPILogprobs(logprobs []llm.Logprob) []api.Logprob {
+	result := make([]api.Logprob, len(logprobs))
+	for i, lp := range logprobs {
+		result[i] = api.Logprob{
+			TokenLogprob: api.TokenLogprob{
+				Token:   lp.Token,
+				Bytes:   stringToByteInts(lp.Token),
+				Logprob: lp.Logprob,
+			},
+		}
+		if len(lp.TopLogprobs) > 0 {
+			result[i].TopLogprobs = make([]api.TokenLogprob, len(lp.TopLogprobs))
+			for j, tlp := range lp.TopLogprobs {
+				result[i].TopLogprobs[j] = api.TokenLogprob{
+					Token:   tlp.Token,
+					Bytes:   stringToByteInts(tlp.Token),
+					Logprob: tlp.Logprob,
+				}
+			}
+		}
+	}
+	return result
+}
+
+func stringToByteInts(s string) []int {
+	if s == "" {
+		return nil
+	}
+
+	raw := []byte(s)
+	ints := make([]int, len(raw))
+	for i, b := range raw {
+		ints[i] = int(b)
+	}
+	return ints
+}
diff --git a/server/routes.go b/server/routes.go
index 28d70d62..38ce4e4d 100644
--- a/server/routes.go
+++ b/server/routes.go
@@ -183,6 +183,11 @@ func (s *Server) GenerateHandler(c *gin.Context) {
 		return
 	}
 
+	if req.TopLogprobs < 0 || req.TopLogprobs > 20 {
+		c.AbortWithStatusJSON(http.StatusBadRequest, gin.H{"error": "top_logprobs must be between 0 and 20"})
+		return
+	}
+
 	name := model.ParseName(req.Model)
 	if !name.IsValid() {
 		// Ideally this is "invalid model name" but we're keeping with
@@ -212,6 +217,11 @@ func (s *Server) GenerateHandler(c *gin.Context) {
 		return
 	}
 
+	if req.TopLogprobs < 0 || req.TopLogprobs > 20 {
+		c.AbortWithStatusJSON(http.StatusBadRequest, gin.H{"error": "top_logprobs must be between 0 and 20"})
+		return
+	}
+
 	if m.Config.RemoteHost != "" && m.Config.RemoteModel != "" {
 		origModel := req.Model
 
@@ -502,12 +512,14 @@ func (s *Server) GenerateHandler(c *gin.Context) {
 		var sb strings.Builder
 		defer close(ch)
 		if err := r.Completion(c.Request.Context(), llm.CompletionRequest{
-			Prompt:   prompt,
-			Images:   images,
-			Format:   req.Format,
-			Options:  opts,
-			Shift:    req.Shift == nil || *req.Shift,
-			Truncate: req.Truncate == nil || *req.Truncate,
+			Prompt:      prompt,
+			Images:      images,
+			Format:      req.Format,
+			Options:     opts,
+			Shift:       req.Shift == nil || *req.Shift,
+			Truncate:    req.Truncate == nil || *req.Truncate,
+			Logprobs:    req.Logprobs,
+			TopLogprobs: req.TopLogprobs,
 		}, func(cr llm.CompletionResponse) {
 			res := api.GenerateResponse{
 				Model:     req.Model,
@@ -520,6 +532,7 @@ func (s *Server) GenerateHandler(c *gin.Context) {
 					EvalCount:          cr.EvalCount,
 					EvalDuration:       cr.EvalDuration,
 				},
+				Logprobs: toAPILogprobs(cr.Logprobs),
 			}
 
 			if builtinParser != nil {
@@ -580,6 +593,7 @@ func (s *Server) GenerateHandler(c *gin.Context) {
 
 	if req.Stream != nil && !*req.Stream {
 		var r api.GenerateResponse
+		var allLogprobs []api.Logprob
 		var sbThinking strings.Builder
 		var sbContent strings.Builder
 		for rr := range ch {
@@ -588,6 +602,10 @@ func (s *Server) GenerateHandler(c *gin.Context) {
 				sbThinking.WriteString(t.Thinking)
 				sbContent.WriteString(t.Response)
 				r = t
+				// Accumulate logprobs from all chunks for non-streaming response
+				if len(t.Logprobs) > 0 {
+					allLogprobs = append(allLogprobs, t.Logprobs...)
+				}
 			case gin.H:
 				msg, ok := t["error"].(string)
 				if !ok {
@@ -609,6 +627,7 @@ func (s *Server) GenerateHandler(c *gin.Context) {
 
 		r.Thinking = sbThinking.String()
 		r.Response = sbContent.String()
+		r.Logprobs = allLogprobs
 
 		c.JSON(http.StatusOK, r)
 		return
@@ -1834,6 +1853,11 @@ func (s *Server) ChatHandler(c *gin.Context) {
 		return
 	}
 
+	if req.TopLogprobs < 0 || req.TopLogprobs > 20 {
+		c.AbortWithStatusJSON(http.StatusBadRequest, gin.H{"error": "top_logprobs must be between 0 and 20"})
+		return
+	}
+
 	name := model.ParseName(req.Model)
 	if !name.IsValid() {
 		c.JSON(http.StatusBadRequest, gin.H{"error": "model is required"})
@@ -1859,6 +1883,11 @@ func (s *Server) ChatHandler(c *gin.Context) {
 		return
 	}
 
+	if req.TopLogprobs < 0 || req.TopLogprobs > 20 {
+		c.AbortWithStatusJSON(http.StatusBadRequest, gin.H{"error": "top_logprobs must be between 0 and 20"})
+		return
+	}
+
 	// expire the runner
 	if len(req.Messages) == 0 && req.KeepAlive != nil && req.KeepAlive.Duration == 0 {
 		s.sched.expireRunner(m)
@@ -2104,12 +2133,14 @@ func (s *Server) ChatHandler(c *gin.Context) {
 			// sets up new context given parent context per request
 			ctx, cancel := context.WithCancel(c.Request.Context())
 			err := r.Completion(ctx, llm.CompletionRequest{
-				Prompt:   prompt,
-				Images:   images,
-				Format:   currentFormat,
-				Options:  opts,
-				Shift:    req.Shift == nil || *req.Shift,
-				Truncate: truncate,
+				Prompt:      prompt,
+				Images:      images,
+				Format:      currentFormat,
+				Options:     opts,
+				Shift:       req.Shift == nil || *req.Shift,
+				Truncate:    truncate,
+				Logprobs:    req.Logprobs,
+				TopLogprobs: req.TopLogprobs,
 			}, func(r llm.CompletionResponse) {
 				res := api.ChatResponse{
 					Model:     req.Model,
@@ -2122,7 +2153,9 @@ func (s *Server) ChatHandler(c *gin.Context) {
 						EvalCount:          r.EvalCount,
 						EvalDuration:       r.EvalDuration,
 					},
+					Logprobs: toAPILogprobs(r.Logprobs),
 				}
+
 				if r.Done {
 					res.DoneReason = r.DoneReason.String()
 					res.TotalDuration = time.Since(checkpointStart)
@@ -2251,6 +2284,7 @@ func (s *Server) ChatHandler(c *gin.Context) {
 	if req.Stream != nil && !*req.Stream {
 		var resp api.ChatResponse
 		var toolCalls []api.ToolCall
+		var allLogprobs []api.Logprob
 		var sbThinking strings.Builder
 		var sbContent strings.Builder
 		for rr := range ch {
@@ -2262,6 +2296,10 @@ func (s *Server) ChatHandler(c *gin.Context) {
 				if len(req.Tools) > 0 {
 					toolCalls = append(toolCalls, t.Message.ToolCalls...)
 				}
+				// Accumulate logprobs from all chunks for non-streaming response
+				if len(t.Logprobs) > 0 {
+					allLogprobs = append(allLogprobs, t.Logprobs...)
+				}
 			case gin.H:
 				msg, ok := t["error"].(string)
 				if !ok {
@@ -2283,6 +2321,7 @@ func (s *Server) ChatHandler(c *gin.Context) {
 
 		resp.Message.Content = sbContent.String()
 		resp.Message.Thinking = sbThinking.String()
+		resp.Logprobs = allLogprobs
 
 		if len(toolCalls) > 0 {
 			resp.Message.ToolCalls = toolCalls
diff --git a/server/routes_generate_test.go b/server/routes_generate_test.go
index ed5922f2..a9931ea2 100644
--- a/server/routes_generate_test.go
+++ b/server/routes_generate_test.go
@@ -1184,6 +1184,355 @@ func TestGenerate(t *testing.T) {
 	})
 }
 
+func TestGenerateLogprobs(t *testing.T) {
+	t.Run("invalid top_logprobs negative", func(t *testing.T) {
+		gin.SetMode(gin.TestMode)
+		s := Server{}
+		w := createRequest(t, s.GenerateHandler, api.GenerateRequest{
+			Model:       "test",
+			Prompt:      "Hello",
+			TopLogprobs: -1,
+		})
+
+		if w.Code != http.StatusBadRequest {
+			t.Errorf("expected status 400, got %d", w.Code)
+		}
+
+		if diff := cmp.Diff(w.Body.String(), `{"error":"top_logprobs must be between 0 and 20"}`); diff != "" {
+			t.Errorf("mismatch (-got +want):\n%s", diff)
+		}
+	})
+
+	t.Run("invalid top_logprobs too high", func(t *testing.T) {
+		gin.SetMode(gin.TestMode)
+		s := Server{}
+		w := createRequest(t, s.GenerateHandler, api.GenerateRequest{
+			Model:       "test",
+			Prompt:      "Hello",
+			TopLogprobs: 21,
+		})
+
+		if w.Code != http.StatusBadRequest {
+			t.Errorf("expected status 400, got %d", w.Code)
+		}
+
+		if diff := cmp.Diff(w.Body.String(), `{"error":"top_logprobs must be between 0 and 20"}`); diff != "" {
+			t.Errorf("mismatch (-got +want):\n%s", diff)
+		}
+	})
+
+	t.Run("returns logprob bytes when requested", func(t *testing.T) {
+		gin.SetMode(gin.TestMode)
+
+		mock := &mockRunner{}
+		expectedPrimary := llm.TokenLogprob{
+			Token:   "Hi",
+			Logprob: -0.01,
+		}
+		expectedAlternatives := []llm.TokenLogprob{
+			{
+				Token:   "Hello",
+				Logprob: -0.25,
+			},
+			{
+				Token:   "Hey",
+				Logprob: -0.5,
+			},
+		}
+
+		mock.CompletionFn = func(ctx context.Context, r llm.CompletionRequest, fn func(llm.CompletionResponse)) error {
+			fn(llm.CompletionResponse{
+				Content:            "Hi",
+				Done:               true,
+				DoneReason:         llm.DoneReasonStop,
+				PromptEvalCount:    1,
+				PromptEvalDuration: 1,
+				EvalCount:          1,
+				EvalDuration:       1,
+				Logprobs: []llm.Logprob{
+					{
+						TokenLogprob: expectedPrimary,
+						TopLogprobs:  expectedAlternatives,
+					},
+				},
+			})
+			return nil
+		}
+
+		s := &Server{
+			sched: &Scheduler{
+				pendingReqCh:    make(chan *LlmRequest, 1),
+				finishedReqCh:   make(chan *LlmRequest, 1),
+				expiredCh:       make(chan *runnerRef, 1),
+				unloadedCh:      make(chan any, 1),
+				loaded:          make(map[string]*runnerRef),
+				newServerFn:     newMockServer(mock),
+				getGpuFn:        getGpuFn,
+				getSystemInfoFn: getSystemInfoFn,
+				waitForRecovery: 250 * time.Millisecond,
+				loadFn: func(req *LlmRequest, _ *ggml.GGML, _ ml.SystemInfo, _ []ml.DeviceInfo, _ bool) bool {
+					req.successCh <- &runnerRef{llama: mock}
+					return false
+				},
+			},
+		}
+
+		go s.sched.Run(t.Context())
+
+		_, digest := createBinFile(t, ggml.KV{
+			"general.architecture":          "llama",
+			"llama.block_count":             uint32(1),
+			"llama.context_length":          uint32(8192),
+			"llama.embedding_length":        uint32(4096),
+			"llama.attention.head_count":    uint32(32),
+			"llama.attention.head_count_kv": uint32(8),
+			"tokenizer.ggml.tokens":         []string{""},
+			"tokenizer.ggml.scores":         []float32{0},
+			"tokenizer.ggml.token_type":     []int32{0},
+		}, []*ggml.Tensor{
+			{Name: "token_embd.weight", Shape: []uint64{1}, WriterTo: bytes.NewReader(make([]byte, 4))},
+			{Name: "blk.0.attn_norm.weight", Shape: []uint64{1}, WriterTo: bytes.NewReader(make([]byte, 4))},
+			{Name: "blk.0.ffn_down.weight", Shape: []uint64{1}, WriterTo: bytes.NewReader(make([]byte, 4))},
+			{Name: "blk.0.ffn_gate.weight", Shape: []uint64{1}, WriterTo: bytes.NewReader(make([]byte, 4))},
+			{Name: "blk.0.ffn_up.weight", Shape: []uint64{1}, WriterTo: bytes.NewReader(make([]byte, 4))},
+			{Name: "blk.0.ffn_norm.weight", Shape: []uint64{1}, WriterTo: bytes.NewReader(make([]byte, 4))},
+			{Name: "blk.0.attn_k.weight", Shape: []uint64{1}, WriterTo: bytes.NewReader(make([]byte, 4))},
+			{Name: "blk.0.attn_output.weight", Shape: []uint64{1}, WriterTo: bytes.NewReader(make([]byte, 4))},
+			{Name: "blk.0.attn_q.weight", Shape: []uint64{1}, WriterTo: bytes.NewReader(make([]byte, 4))},
+			{Name: "blk.0.attn_v.weight", Shape: []uint64{1}, WriterTo: bytes.NewReader(make([]byte, 4))},
+			{Name: "output.weight", Shape: []uint64{1}, WriterTo: bytes.NewReader(make([]byte, 4))},
+		})
+
+		if w := createRequest(t, s.CreateHandler, api.CreateRequest{
+			Model:    "test-logprob-bytes",
+			Files:    map[string]string{"file.gguf": digest},
+			Template: `{{ .Prompt }}`,
+			Stream:   &stream,
+		}); w.Code != http.StatusOK {
+			t.Fatalf("expected status 200, got %d", w.Code)
+		}
+
+		stream := false
+		w := createRequest(t, s.GenerateHandler, api.GenerateRequest{
+			Model:       "test-logprob-bytes",
+			Prompt:      "Hi",
+			Stream:      &stream,
+			Logprobs:    true,
+			TopLogprobs: len(expectedAlternatives),
+		})
+
+		if w.Code != http.StatusOK {
+			t.Fatalf("expected status 200, got %d", w.Code)
+		}
+
+		var resp api.GenerateResponse
+		if err := json.NewDecoder(w.Body).Decode(&resp); err != nil {
+			t.Fatalf("failed to decode response: %v", err)
+		}
+
+		if len(resp.Logprobs) != 1 {
+			t.Fatalf("expected 1 logprob entry, got %d", len(resp.Logprobs))
+		}
+
+		expectedPrimaryBytes := stringToByteInts(expectedPrimary.Token)
+		expectedAlternativesBytes := make([][]int, len(expectedAlternatives))
+		for i, alternative := range expectedAlternatives {
+			expectedAlternativesBytes[i] = stringToByteInts(alternative.Token)
+		}
+		if diff := cmp.Diff(expectedPrimaryBytes, resp.Logprobs[0].Bytes); diff != "" {
+			t.Fatalf("primary token bytes mismatch (-want +got):\n%s", diff)
+		}
+
+		if len(resp.Logprobs[0].TopLogprobs) != len(expectedAlternatives) {
+			t.Fatalf("expected %d top logprobs, got %d", len(expectedAlternatives), len(resp.Logprobs[0].TopLogprobs))
+		}
+
+		for i, top := range resp.Logprobs[0].TopLogprobs {
+			if diff := cmp.Diff(expectedAlternativesBytes[i], top.Bytes); diff != "" {
+				t.Fatalf("top logprob[%d] bytes mismatch (-want +got):\n%s", i, diff)
+			}
+		}
+	})
+}
+
+func TestChatLogprobs(t *testing.T) {
+	t.Run("invalid top_logprobs negative", func(t *testing.T) {
+		gin.SetMode(gin.TestMode)
+		s := Server{}
+		w := createRequest(t, s.ChatHandler, api.ChatRequest{
+			Model: "test",
+			Messages: []api.Message{
+				{Role: "user", Content: "Hello"},
+			},
+			TopLogprobs: -1,
+		})
+
+		if w.Code != http.StatusBadRequest {
+			t.Errorf("expected status 400, got %d", w.Code)
+		}
+
+		if diff := cmp.Diff(w.Body.String(), `{"error":"top_logprobs must be between 0 and 20"}`); diff != "" {
+			t.Errorf("mismatch (-got +want):\n%s", diff)
+		}
+	})
+
+	t.Run("invalid top_logprobs too high", func(t *testing.T) {
+		gin.SetMode(gin.TestMode)
+		s := Server{}
+		w := createRequest(t, s.ChatHandler, api.ChatRequest{
+			Model: "test",
+			Messages: []api.Message{
+				{Role: "user", Content: "Hello"},
+			},
+			TopLogprobs: 21,
+		})
+
+		if w.Code != http.StatusBadRequest {
+			t.Errorf("expected status 400, got %d", w.Code)
+		}
+
+		if diff := cmp.Diff(w.Body.String(), `{"error":"top_logprobs must be between 0 and 20"}`); diff != "" {
+			t.Errorf("mismatch (-got +want):\n%s", diff)
+		}
+	})
+
+	t.Run("returns logprob bytes when requested", func(t *testing.T) {
+		gin.SetMode(gin.TestMode)
+
+		mock := &mockRunner{}
+		expectedPrimary := llm.TokenLogprob{
+			Token:   "Hi",
+			Logprob: -0.02,
+		}
+		expectedAlternatives := []llm.TokenLogprob{
+			{
+				Token:   "Hello",
+				Logprob: -0.3,
+			},
+			{
+				Token:   "Hey",
+				Logprob: -0.45,
+			},
+		}
+		expectedPrimaryBytes := stringToByteInts(expectedPrimary.Token)
+		expectedAlternativesBytes := make([][]int, len(expectedAlternatives))
+		for i, alternative := range expectedAlternatives {
+			expectedAlternativesBytes[i] = stringToByteInts(alternative.Token)
+		}
+
+		mock.CompletionFn = func(ctx context.Context, r llm.CompletionRequest, fn func(llm.CompletionResponse)) error {
+			fn(llm.CompletionResponse{
+				Content:            "Hi",
+				Done:               true,
+				DoneReason:         llm.DoneReasonStop,
+				PromptEvalCount:    1,
+				PromptEvalDuration: 1,
+				EvalCount:          1,
+				EvalDuration:       1,
+				Logprobs: []llm.Logprob{
+					{
+						TokenLogprob: expectedPrimary,
+						TopLogprobs:  expectedAlternatives,
+					},
+				},
+			})
+			return nil
+		}
+
+		s := &Server{
+			sched: &Scheduler{
+				pendingReqCh:    make(chan *LlmRequest, 1),
+				finishedReqCh:   make(chan *LlmRequest, 1),
+				expiredCh:       make(chan *runnerRef, 1),
+				unloadedCh:      make(chan any, 1),
+				loaded:          make(map[string]*runnerRef),
+				newServerFn:     newMockServer(mock),
+				getGpuFn:        getGpuFn,
+				getSystemInfoFn: getSystemInfoFn,
+				waitForRecovery: 250 * time.Millisecond,
+				loadFn: func(req *LlmRequest, _ *ggml.GGML, _ ml.SystemInfo, _ []ml.DeviceInfo, _ bool) bool {
+					req.successCh <- &runnerRef{llama: mock}
+					return false
+				},
+			},
+		}
+
+		go s.sched.Run(t.Context())
+
+		_, digest := createBinFile(t, ggml.KV{
+			"general.architecture":          "llama",
+			"llama.block_count":             uint32(1),
+			"llama.context_length":          uint32(8192),
+			"llama.embedding_length":        uint32(4096),
+			"llama.attention.head_count":    uint32(32),
+			"llama.attention.head_count_kv": uint32(8),
+			"tokenizer.ggml.tokens":         []string{""},
+			"tokenizer.ggml.scores":         []float32{0},
+			"tokenizer.ggml.token_type":     []int32{0},
+		}, []*ggml.Tensor{
+			{Name: "token_embd.weight", Shape: []uint64{1}, WriterTo: bytes.NewReader(make([]byte, 4))},
+			{Name: "blk.0.attn_norm.weight", Shape: []uint64{1}, WriterTo: bytes.NewReader(make([]byte, 4))},
+			{Name: "blk.0.ffn_down.weight", Shape: []uint64{1}, WriterTo: bytes.NewReader(make([]byte, 4))},
+			{Name: "blk.0.ffn_gate.weight", Shape: []uint64{1}, WriterTo: bytes.NewReader(make([]byte, 4))},
+			{Name: "blk.0.ffn_up.weight", Shape: []uint64{1}, WriterTo: bytes.NewReader(make([]byte, 4))},
+			{Name: "blk.0.ffn_norm.weight", Shape: []uint64{1}, WriterTo: bytes.NewReader(make([]byte, 4))},
+			{Name: "blk.0.attn_k.weight", Shape: []uint64{1}, WriterTo: bytes.NewReader(make([]byte, 4))},
+			{Name: "blk.0.attn_output.weight", Shape: []uint64{1}, WriterTo: bytes.NewReader(make([]byte, 4))},
+			{Name: "blk.0.attn_q.weight", Shape: []uint64{1}, WriterTo: bytes.NewReader(make([]byte, 4))},
+			{Name: "blk.0.attn_v.weight", Shape: []uint64{1}, WriterTo: bytes.NewReader(make([]byte, 4))},
+			{Name: "output.weight", Shape: []uint64{1}, WriterTo: bytes.NewReader(make([]byte, 4))},
+		})
+
+		if w := createRequest(t, s.CreateHandler, api.CreateRequest{
+			Model: "test-chat-logprob-bytes",
+			Files: map[string]string{"file.gguf": digest},
+			Template: `{{- range .Messages }}{{ .Role }}: {{ .Content }}
+{{ end }}`,
+			Stream: &stream,
+		}); w.Code != http.StatusOK {
+			t.Fatalf("expected status 200, got %d", w.Code)
+		}
+
+		stream := false
+		w := createRequest(t, s.ChatHandler, api.ChatRequest{
+			Model: "test-chat-logprob-bytes",
+			Messages: []api.Message{
+				{Role: "user", Content: "Say hi"},
+			},
+			Stream:      &stream,
+			Logprobs:    true,
+			TopLogprobs: len(expectedAlternatives),
+		})
+
+		if w.Code != http.StatusOK {
+			t.Fatalf("expected status 200, got %d", w.Code)
+		}
+
+		var resp api.ChatResponse
+		if err := json.NewDecoder(w.Body).Decode(&resp); err != nil {
+			t.Fatalf("failed to decode response: %v", err)
+		}
+
+		if len(resp.Logprobs) != 1 {
+			t.Fatalf("expected 1 logprob entry, got %d", len(resp.Logprobs))
+		}
+
+		if diff := cmp.Diff(expectedPrimaryBytes, resp.Logprobs[0].Bytes); diff != "" {
+			t.Fatalf("primary token bytes mismatch (-want +got):\n%s", diff)
+		}
+
+		if len(resp.Logprobs[0].TopLogprobs) != len(expectedAlternatives) {
+			t.Fatalf("expected %d top logprobs, got %d", len(expectedAlternatives), len(resp.Logprobs[0].TopLogprobs))
+		}
+
+		for i, top := range resp.Logprobs[0].TopLogprobs {
+			if diff := cmp.Diff(expectedAlternativesBytes[i], top.Bytes); diff != "" {
+				t.Fatalf("top logprob[%d] bytes mismatch (-want +got):\n%s", i, diff)
+			}
+		}
+	})
+}
+
 func TestChatWithPromptEndingInThinkTag(t *testing.T) {
 	gin.SetMode(gin.TestMode)
 
diff --git a/server/sched.go b/server/sched.go
index 5ae42efd..c5bc6692 100644
--- a/server/sched.go
+++ b/server/sched.go
@@ -437,6 +437,23 @@ func (s *Scheduler) load(req *LlmRequest, f *ggml.GGML, systemInfo ml.SystemInfo
 
 	s.loadedMu.Unlock()
 
+	systemTotalMemory := systemInfo.TotalMemory
+	systemFreeMemory := systemInfo.FreeMemory
+	systemSwapFreeMemory := systemInfo.FreeSwap
+	slog.Info("system memory", "total", format.HumanBytes2(systemTotalMemory), "free", format.HumanBytes2(systemFreeMemory), "free_swap", format.HumanBytes2(systemSwapFreeMemory))
+
+	for _, gpu := range gpus {
+		available := gpu.FreeMemory - envconfig.GpuOverhead() - gpu.MinimumMemory()
+		if gpu.FreeMemory < envconfig.GpuOverhead()+gpu.MinimumMemory() {
+			available = 0
+		}
+		slog.Info("gpu memory", "id", gpu.ID, "library", gpu.Library,
+			"available", format.HumanBytes2(available),
+			"free", format.HumanBytes2(gpu.FreeMemory),
+			"minimum", format.HumanBytes2(gpu.MinimumMemory()),
+			"overhead", format.HumanBytes2(envconfig.GpuOverhead()))
+	}
+
 	gpuIDs, err := llama.Load(req.ctx, systemInfo, gpus, requireFull)
 	if err != nil {
 		if errors.Is(err, llm.ErrLoadRequiredFull) {