---
title: "AWS Bedrock - Image Generation"
url: "/docs/providers/bedrock_image_gen"
canonical_url: "https://docs.litellm.ai/docs/providers/bedrock_image_gen"
type: "docs"
last_updated: "2026-10-09"
summary: "Use Bedrock for image generation with Stable Diffusion, Amazon Titan Image Generator, and Amazon Nova Canvas models."
related:
  - "/docs/providers/bedrock_imported"
  - "/docs/providers/bedrock_rerank"
---
# AWS Bedrock - Image Generation

> Index of all LiteLLM docs: https://docs.litellm.ai/llms.txt


Use Bedrock for image generation with Stable Diffusion, Amazon Titan Image Generator, and Amazon Nova Canvas models.

## Supported Models

| Model Name              | Function Call                               | Cost Tracking |
|-------------------------|---------------------------------------------|---------------|
| Stable Diffusion 3 - v0 | `image_generation(model="bedrock/stability.stability.sd3-large-v1:0", prompt=prompt)` | ✅ |
| Stable Diffusion - v0   | `image_generation(model="bedrock/stability.stable-diffusion-xl-v0", prompt=prompt)` | ✅ |
| Stable Diffusion - v1   | `image_generation(model="bedrock/stability.stable-diffusion-xl-v1", prompt=prompt)` | ✅ |
| Amazon Titan Image Generator - v1 | `image_generation(model="bedrock/amazon.titan-image-generator-v1", prompt=prompt)` | ✅ |
| Amazon Titan Image Generator - v2 | `image_generation(model="bedrock/amazon.titan-image-generator-v2:0", prompt=prompt)` | ✅ |
| Amazon Nova Canvas - v1 | `image_generation(model="bedrock/amazon.nova-canvas-v1:0", prompt=prompt)` | ✅ |

## Usage

**SDK**

### Basic Usage

```python
import os
from litellm import image_generation

os.environ["AWS_ACCESS_KEY_ID"] = ""
os.environ["AWS_SECRET_ACCESS_KEY"] = ""
os.environ["AWS_REGION_NAME"] = ""

response = image_generation(
    prompt="A cute baby sea otter",
    model="bedrock/stability.stable-diffusion-xl-v0",
)
print(f"response: {response}")
```

### Set Optional Parameters

```python
import os
from litellm import image_generation

os.environ["AWS_ACCESS_KEY_ID"] = ""
os.environ["AWS_SECRET_ACCESS_KEY"] = ""
os.environ["AWS_REGION_NAME"] = ""

response = image_generation(
    prompt="A cute baby sea otter",
    model="bedrock/stability.stable-diffusion-xl-v0",
    ### OPENAI-COMPATIBLE ###
    size="128x512", # width=128, height=512
    ### PROVIDER-SPECIFIC ### see `AmazonStabilityConfig` in bedrock.py for all params
    seed=30
)
print(f"response: {response}")
```

**PROXY**

### 1. Setup config.yaml

```yaml
model_list:
  - model_name: amazon.nova-canvas-v1:0
    litellm_params:
      model: bedrock/amazon.nova-canvas-v1:0
      aws_region_name: "us-east-1"
      aws_access_key_id: my-id # OPTIONAL - all boto3 auth params supported
      aws_secret_access_key: my-key # OPTIONAL - all boto3 auth params supported
```

### 2. Start proxy 

```bash
litellm --config /path/to/config.yaml
```

### 3. Test it! 

**Text to Image:**

```bash
curl -L -X POST 'http://0.0.0.0:4000/v1/images/generations' \
-H 'Content-Type: application/json' \
-H 'Authorization: Bearer $LITELLM_VIRTUAL_KEY' \
-d '{
    "model": "amazon.nova-canvas-v1:0",
    "prompt": "A cute baby sea otter"
}'
```

**Color Guided Generation:**

```bash
curl -L -X POST 'http://0.0.0.0:4000/v1/images/generations' \
-H 'Content-Type: application/json' \
-H 'Authorization: Bearer $LITELLM_VIRTUAL_KEY' \
-d '{
    "model": "amazon.nova-canvas-v1:0",
    "prompt": "A cute baby sea otter",
    "taskType": "COLOR_GUIDED_GENERATION",
    "colorGuidedGenerationParams":{"colors":["#FFFFFF"]}
}'
```

## Amazon Nova Canvas - Image Edit

Use OpenAI-compatible `image_edit()` with Bedrock Nova Canvas (`amazon.nova-canvas-v1:0`). Requests use the same `InvokeModel` API as generation; LiteLLM maps inputs to [Nova Canvas task types](https://docs.aws.amazon.com/nova/latest/userguide/image-gen-access.html):

| Scenario | `taskType` sent to Bedrock |
|----------|----------------------------|
| Image + prompt (no mask) | `IMAGE_VARIATION` |
| Image + prompt + mask | `INPAINTING` (`inPaintingParams.image`, `maskImage` or `maskPrompt`) |
| `taskType: OUTPAINTING` + `mask` or `maskPrompt` | `OUTPAINTING` (Bedrock requires one; LiteLLM raises a clear error if both are missing) |
| `taskType: BACKGROUND_REMOVAL` | `BACKGROUND_REMOVAL` |

```python
from litellm import image_edit

response = image_edit(
    image=open("photo.png", "rb"),
    prompt="Add soft sunset lighting",
    model="bedrock/amazon.nova-canvas-v1:0",
)
```

For **`BACKGROUND_REMOVAL`**, the AWS request must not include `imageGenerationConfig`; LiteLLM omits it for that task even if you pass `size`, `n`, `seed`, etc. Additional Nova Canvas inference IDs for image edit should set **`supports_nova_canvas_image_edit`: true** in `model_prices_and_context_window.json` (see `amazon.nova-canvas-v1:0`).

## Using Inference Profiles with Image Generation

For AWS Bedrock Application Inference Profiles with image generation, use the `model_id` parameter to specify the inference profile ARN:

**SDK**

```python
from litellm import image_generation

response = image_generation(
    model="bedrock/amazon.nova-canvas-v1:0",
    model_id="arn:aws:bedrock:eu-west-1:000000000000:application-inference-profile/a0a0a0a0a0a0",
    prompt="A cute baby sea otter"
)
print(f"response: {response}")
```

**PROXY**

```yaml
model_list:
  - model_name: nova-canvas-inference-profile
    litellm_params:
      model: bedrock/amazon.nova-canvas-v1:0
      model_id: arn:aws:bedrock:eu-west-1:000000000000:application-inference-profile/a0a0a0a0a0a0
      aws_region_name: "eu-west-1"
```

## Authentication

All standard Bedrock authentication methods are supported for image generation. See [Bedrock Authentication](./bedrock#boto3---authentication) for details.

## Related pages

- [Bedrock Imported Models](https://docs.litellm.ai/docs/providers/bedrock_imported.md)
- [AWS Bedrock - Rerank API](https://docs.litellm.ai/docs/providers/bedrock_rerank.md)