ollama/docs/capabilities/image-generation.mdx

---
title: Image Generation
---

<Warning>
Image generation is experimental and currently only available on macOS. This feature may change in future versions.
</Warning>

Image generation models create images from text prompts. Ollama supports diffusion-based image generation models through both Ollama's API and OpenAI-compatible endpoints.

## Usage

<Tabs>
  <Tab title="CLI">
    ```shell
    ollama run x/z-image-turbo "a sunset over mountains"
    ```
    The generated image will be saved to the current directory.
  </Tab>
  <Tab title="cURL">
    ```shell
    curl http://localhost:11434/api/generate -d '{
      "model": "x/z-image-turbo",
      "prompt": "a sunset over mountains",
      "stream": false
    }'
    ```
  </Tab>
  <Tab title="Python">
    ```python
    import ollama
    import base64

    response = ollama.generate(
        model='x/z-image-turbo',
        prompt='a sunset over mountains',
    )

    # Save the generated image
    with open('output.png', 'wb') as f:
        f.write(base64.b64decode(response['image']))

    print('Image saved to output.png')
    ```
  </Tab>
  <Tab title="JavaScript">
    ```javascript
    import ollama from 'ollama'
    import { writeFileSync } from 'fs'

    const response = await ollama.generate({
      model: 'x/z-image-turbo',
      prompt: 'a sunset over mountains',
    })

    // Save the generated image
    const imageBuffer = Buffer.from(response.image, 'base64')
    writeFileSync('output.png', imageBuffer)

    console.log('Image saved to output.png')
    ```
  </Tab>
</Tabs>

### Response

The response includes an `image` field containing the base64-encoded image data:

```json
{
  "model": "x/z-image-turbo",
  "created_at": "2024-01-15T10:30:15.000000Z",
  "image": "iVBORw0KGgoAAAANSUhEUg...",
  "done": true,
  "done_reason": "stop",
  "total_duration": 15000000000,
  "load_duration": 2000000000
}
```

## Image dimensions

Customize the output image size using the `width` and `height` parameters:

<Tabs>
  <Tab title="cURL">
    ```shell
    curl http://localhost:11434/api/generate -d '{
      "model": "x/z-image-turbo",
      "prompt": "a portrait of a robot artist",
      "width": 768,
      "height": 1024,
      "stream": false
    }'
    ```
  </Tab>
  <Tab title="Python">
    ```python
    import ollama

    response = ollama.generate(
        model='x/z-image-turbo',
        prompt='a portrait of a robot artist',
        width=768,
        height=1024,
    )
    ```
  </Tab>
  <Tab title="JavaScript">
    ```javascript
    import ollama from 'ollama'

    const response = await ollama.generate({
      model: 'x/z-image-turbo',
      prompt: 'a portrait of a robot artist',
      width: 768,
      height: 1024,
    })
    ```
  </Tab>
</Tabs>

## Streaming progress

When streaming is enabled (the default), progress updates are sent during image generation:

```json
{
  "model": "x/z-image-turbo",
  "created_at": "2024-01-15T10:30:00.000000Z",
  "completed": 5,
  "total": 20,
  "done": false
}
```

The `completed` and `total` fields indicate the current progress through the diffusion steps.

## Parameters

| Parameter | Description | Default |
|-----------|-------------|---------|
| `prompt` | Text description of the image to generate | Required |
| `width` | Width of the generated image in pixels | Model default |
| `height` | Height of the generated image in pixels | Model default |
| `steps` | Number of diffusion steps | Model default |

## OpenAI compatibility

Image generation is also available through the OpenAI-compatible `/v1/images/generations` endpoint:

<Tabs>
  <Tab title="cURL">
    ```shell
    curl http://localhost:11434/v1/images/generations \
      -H "Content-Type: application/json" \
      -d '{
        "model": "x/z-image-turbo",
        "prompt": "a sunset over mountains",
        "size": "1024x1024",
        "response_format": "b64_json"
      }'
    ```
  </Tab>
  <Tab title="Python">
    ```python
    from openai import OpenAI

    client = OpenAI(
        base_url='http://localhost:11434/v1/',
        api_key='ollama',  # required but ignored
    )

    response = client.images.generate(
        model='x/z-image-turbo',
        prompt='a sunset over mountains',
        size='1024x1024',
        response_format='b64_json',
    )

    print(response.data[0].b64_json[:50] + '...')
    ```
  </Tab>
  <Tab title="JavaScript">
    ```javascript
    import OpenAI from 'openai'

    const openai = new OpenAI({
      baseURL: 'http://localhost:11434/v1/',
      apiKey: 'ollama', // required but ignored
    })

    const response = await openai.images.generate({
      model: 'x/z-image-turbo',
      prompt: 'a sunset over mountains',
      size: '1024x1024',
      response_format: 'b64_json',
    })

    console.log(response.data[0].b64_json.slice(0, 50) + '...')
    ```
  </Tab>
</Tabs>

See [OpenAI compatibility](/api/openai-compatibility#v1imagesgenerations-experimental) for more details.