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docs: add reference to docs.ollama.com (#12800)
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docs/capabilities/vision.mdx
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docs/capabilities/vision.mdx
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---
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title: Vision
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---
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Vision models accept images alongside text so the model can describe, classify, and answer questions about what it sees.
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## Quick start
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```shell
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ollama run gemma3 ./image.png whats in this image?
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```
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## Usage with Ollama's API
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Provide an `images` array. SDKs accept file paths, URLs or raw bytes while the REST API expects base64-encoded image data.
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<Tabs>
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<Tab title="cURL">
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```shell
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# 1. Download a sample image
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curl -L -o test.jpg "https://upload.wikimedia.org/wikipedia/commons/3/3a/Cat03.jpg"
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# 2. Encode the image
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IMG=$(base64 < test.jpg | tr -d '\n')
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# 3. Send it to Ollama
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curl -X POST http://localhost:11434/api/chat \
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-H "Content-Type: application/json" \
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-d '{
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"model": "gemma3",
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"messages": [{
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"role": "user",
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"content": "What is in this image?",
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"images": ["'"$IMG"'"]
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}],
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"stream": false
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}'
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"
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```
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</Tab>
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<Tab title="Python">
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```python
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from ollama import chat
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# from pathlib import Path
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# Pass in the path to the image
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path = input('Please enter the path to the image: ')
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# You can also pass in base64 encoded image data
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# img = base64.b64encode(Path(path).read_bytes()).decode()
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# or the raw bytes
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# img = Path(path).read_bytes()
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response = chat(
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model='gemma3',
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messages=[
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{
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'role': 'user',
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'content': 'What is in this image? Be concise.',
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'images': [path],
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}
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],
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)
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print(response.message.content)
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```
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</Tab>
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<Tab title="JavaScript">
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```javascript
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import ollama from 'ollama'
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const imagePath = '/absolute/path/to/image.jpg'
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const response = await ollama.chat({
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model: 'gemma3',
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messages: [
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{ role: 'user', content: 'What is in this image?', images: [imagePath] }
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],
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stream: false,
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})
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console.log(response.message.content)
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```
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</Tab>
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</Tabs>
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