---
title: "AWS Bedrock - Image Generation"
description: "import Tabs from '@theme/Tabs'; import TabItem from '@theme/TabItem';"
type: skill
canonical_url: https://claudary.paisolsolutions.com/skills/bedrock-image-gen
source: "Claudary"
difficulty: intermediate
author: "Claude Code Knowledge Pack"
date: 2026-07-10T11:08:18.777Z
license: CC-BY-4.0
attribution: "AWS Bedrock - Image Generation — Claudary (https://claudary.paisolsolutions.com/skills/bedrock-image-gen)"
---

# AWS Bedrock - Image Generation
import Tabs from '@theme/Tabs'; import TabItem from '@theme/TabItem';

## Overview

import Tabs from '@theme/Tabs';
import TabItem from '@theme/TabItem';

# AWS Bedrock - Image Generation

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

<Tabs>
<TabItem value="sdk" label="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}")
```

</TabItem>
<TabItem value="proxy" label="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_secret_access_key: my-key # OPTIONAL - all boto3 auth params supported
      aws_secret_access_id: my-id # 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"]}
}'
```

</TabItem>
</Tabs>

## 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:

<Tabs>
<TabItem value="sdk" label="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}")
```

</TabItem>
<TabItem value="proxy" label="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"
```

</TabItem>
</Tabs>

## Authentication

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

---

Source: [Claudary](https://claudary.paisolsolutions.com/skills/bedrock-image-gen) · https://claudary.paisolsolutions.com