Stability AI

Overview

Property	Details
Description	Stability AI creates open AI models for image, video, audio, and 3D generation. Known for Stable Diffusion.
Provider Route on LiteLLM	`stability/`
Link to Provider Doc	Stability AI API ↗
Supported Operations	`/images/generations`, `/images/edits`

LiteLLM supports Stability AI Image Generation calls via the Stability AI REST API (not via Bedrock).

API Key

# env variable
os.environ['STABILITY_API_KEY'] = "your-api-key"

Get your API key from the Stability AI Platform.

Image Generation

Usage - LiteLLM Python SDK

from litellm import image_generation
import os

os.environ['STABILITY_API_KEY'] = "your-api-key"

# Stability AI image generation call
response = image_generation(
    model="stability/sd3.5-large",
    prompt="A beautiful sunset over a calm ocean",
)
print(response)

Usage - LiteLLM Proxy Server

1. Setup config.yaml

model_list:
  - model_name: sd3
    litellm_params:
      model: stability/sd3.5-large
      api_key: os.environ/STABILITY_API_KEY
    model_info:
      mode: image_generation

general_settings:
  master_key: sk-1234

2. Start the proxy

litellm --config config.yaml

# RUNNING on http://0.0.0.0:4000

3. Test it

curl --location 'http://0.0.0.0:4000/v1/images/generations' \
--header 'Content-Type: application/json' \
--header 'Authorization: Bearer sk-1234' \
--data '{
    "model": "sd3",
    "prompt": "A beautiful sunset over a calm ocean"
}'

Advanced Usage - With Additional Parameters

from litellm import image_generation
import os

os.environ['STABILITY_API_KEY'] = "your-api-key"

response = image_generation(
    model="stability/sd3.5-large",
    prompt="A beautiful sunset over a calm ocean",
    size="1792x1024",  # Maps to aspect_ratio 16:9
    negative_prompt="blurry, low quality",  # Stability-specific
    seed=12345,  # For reproducibility
)
print(response)

Supported Parameters

Stability AI supports the following OpenAI-compatible parameters:

Parameter	Type	Description	Example
`size`	string	Image dimensions (mapped to aspect_ratio)	`"1024x1024"`
`n`	integer	Number of images (note: Stability returns 1 per request)	`1`
`response_format`	string	Format of response (`b64_json` only for Stability)	`"b64_json"`

Size to Aspect Ratio Mapping

The size parameter is automatically mapped to Stability's aspect_ratio:

OpenAI Size	Stability Aspect Ratio
`1024x1024`	`1:1`
`1792x1024`	`16:9`
`1024x1792`	`9:16`
`512x512`	`1:1`
`256x256`	`1:1`

Using Stability-Specific Parameters

You can pass parameters that are specific to Stability AI directly in your request:

from litellm import image_generation
import os

os.environ['STABILITY_API_KEY'] = "your-api-key"

response = image_generation(
    model="stability/sd3.5-large",
    prompt="A beautiful sunset over a calm ocean",
    # Stability-specific parameters
    negative_prompt="blurry, watermark, text",
    aspect_ratio="16:9",  # Use directly instead of size
    seed=42,
    output_format="png",  # png, jpeg, or webp
)
print(response)

Supported Image Generation Models

Model Name	Function Call	Description
sd3	`image_generation(model="stability/sd3", ...)`	Stable Diffusion 3
sd3-large	`image_generation(model="stability/sd3-large", ...)`	SD3 Large
sd3-large-turbo	`image_generation(model="stability/sd3-large-turbo", ...)`	SD3 Large Turbo (faster)
sd3-medium	`image_generation(model="stability/sd3-medium", ...)`	SD3 Medium
sd3.5-large	`image_generation(model="stability/sd3.5-large", ...)`	SD 3.5 Large (recommended)
sd3.5-large-turbo	`image_generation(model="stability/sd3.5-large-turbo", ...)`	SD 3.5 Large Turbo
sd3.5-medium	`image_generation(model="stability/sd3.5-medium", ...)`	SD 3.5 Medium
stable-image-ultra	`image_generation(model="stability/stable-image-ultra", ...)`	Stable Image Ultra
stable-image-core	`image_generation(model="stability/stable-image-core", ...)`	Stable Image Core

For more details on available models and features, see: https://platform.stability.ai/docs/api-reference

Response Format

Stability AI returns images in base64 format. The response is OpenAI-compatible:

{
    "created": 1234567890,
    "data": [
        {
            "b64_json": "iVBORw0KGgo..."  # Base64 encoded image
        }
    ]
}

Image Editing

Stability AI supports various image editing operations including inpainting, upscaling, outpainting, background removal, and more.

Usage - LiteLLM Python SDK

Inpainting (Edit with Mask)

from litellm import image_edit
import os

os.environ['STABILITY_API_KEY'] = "your-api-key"

# Inpainting - edit specific areas using a mask
response = image_edit(
    model="stability/stable-image-inpaint-v1:0",
    image=open("original_image.png", "rb"),
    mask=open("mask_image.png", "rb"), 
    prompt="Add a beautiful sunset in the masked area",
    size="1024x1024",
)
print(response)

Image Upscaling

from litellm import image_edit
import os

os.environ['STABILITY_API_KEY'] = "your-api-key"

# Conservative upscaling - preserves details
response = image_edit(
    model="stability/stable-conservative-upscale-v1:0",
    image=open("low_res_image.png", "rb"),
    prompt="Upscale this image while preserving details",
)

# Creative upscaling - adds creative details
response = image_edit(
    model="stability/stable-creative-upscale-v1:0",
    image=open("low_res_image.png", "rb"),
    prompt="Upscale and enhance with creative details",
    creativity=0.3,  # 0-0.35, higher = more creative
)

# Fast upscaling - quick upscaling
response = image_edit(
    model="stability/stable-fast-upscale-v1:0",
    image=open("low_res_image.png", "rb"),
    prompt="Quickly upscale this image",
)
print(response)

Image Outpainting

from litellm import image_edit
import os

os.environ['STABILITY_API_KEY'] = "your-api-key"

# Extend image beyond its borders
response = image_edit(
    model="stability/stable-outpaint-v1:0",
    image=open("original_image.png", "rb"),
    prompt="Extend this landscape with mountains",
    left=100,   # Pixels to extend on the left
    right=100,  # Pixels to extend on the right
    up=50,      # Pixels to extend on top
    down=50,    # Pixels to extend on bottom
)
print(response)

Background Removal

from litellm import image_edit
import os

os.environ['STABILITY_API_KEY'] = "your-api-key"

# Remove background from image
response = image_edit(
    model="stability/stable-image-remove-background-v1:0",
    image=open("portrait.png", "rb"),
    prompt="Remove the background",
)
print(response)

Search and Replace

from litellm import image_edit
import os

os.environ['STABILITY_API_KEY'] = "your-api-key"

# Search and replace objects in image
response = image_edit(
    model="stability/stable-image-search-replace-v1:0",
    image=open("scene.png", "rb"),
    prompt="A red sports car",
    search_prompt="blue sedan",  # What to replace
)

# Search and recolor
response = image_edit(
    model="stability/stable-image-search-recolor-v1:0",
    image=open("scene.png", "rb"),
    prompt="Make it golden yellow",
    select_prompt="the car",  # What to recolor
)
print(response)

Image Control (Sketch/Structure)

from litellm import image_edit
import os

os.environ['STABILITY_API_KEY'] = "your-api-key"

# Control with sketch
response = image_edit(
    model="stability/stable-image-control-sketch-v1:0",
    image=open("sketch.png", "rb"),
    prompt="Turn this sketch into a realistic photo",
    control_strength=0.7,  # 0-1, higher = more control
)

# Control with structure
response = image_edit(
    model="stability/stable-image-control-structure-v1:0",
    image=open("structure_reference.png", "rb"),
    prompt="Generate image following this structure",
    control_strength=0.7,
)
print(response)

Erase Objects

from litellm import image_edit
import os

os.environ['STABILITY_API_KEY'] = "your-api-key"

# Erase objects from image
response = image_edit(
    model="stability/stable-image-erase-object-v1:0",
    image=open("scene.png", "rb"),
    mask=open("object_mask.png", "rb"),  # Mask the object to erase
    prompt="Remove the object",
)
print(response)

Supported Image Edit Models

Model Name	Function Call	Description
stable-image-inpaint-v1:0	`image_edit(model="stability/stable-image-inpaint-v1:0", ...)`	Inpainting with mask
stable-conservative-upscale-v1:0	`image_edit(model="stability/stable-conservative-upscale-v1:0", ...)`	Conservative upscaling
stable-creative-upscale-v1:0	`image_edit(model="stability/stable-creative-upscale-v1:0", ...)`	Creative upscaling
stable-fast-upscale-v1:0	`image_edit(model="stability/stable-fast-upscale-v1:0", ...)`	Fast upscaling
stable-outpaint-v1:0	`image_edit(model="stability/stable-outpaint-v1:0", ...)`	Extend image borders
stable-image-remove-background-v1:0	`image_edit(model="stability/stable-image-remove-background-v1:0", ...)`	Remove background
stable-image-search-replace-v1:0	`image_edit(model="stability/stable-image-search-replace-v1:0", ...)`	Search and replace objects
stable-image-search-recolor-v1:0	`image_edit(model="stability/stable-image-search-recolor-v1:0", ...)`	Search and recolor
stable-image-control-sketch-v1:0	`image_edit(model="stability/stable-image-control-sketch-v1:0", ...)`	Control with sketch
stable-image-control-structure-v1:0	`image_edit(model="stability/stable-image-control-structure-v1:0", ...)`	Control with structure
stable-image-erase-object-v1:0	`image_edit(model="stability/stable-image-erase-object-v1:0", ...)`	Erase objects
stable-image-style-guide-v1:0	`image_edit(model="stability/stable-image-style-guide-v1:0", ...)`	Apply style guide
stable-style-transfer-v1:0	`image_edit(model="stability/stable-style-transfer-v1:0", ...)`	Transfer style

Usage - LiteLLM Proxy Server

1. Setup config.yaml

model_list:
  - model_name: stability-inpaint
    litellm_params:
      model: stability/stable-image-inpaint-v1:0
      api_key: os.environ/STABILITY_API_KEY
    model_info:
      mode: image_edit

  - model_name: stability-upscale
    litellm_params:
      model: stability/stable-conservative-upscale-v1:0
      api_key: os.environ/STABILITY_API_KEY
    model_info:
      mode: image_edit

general_settings:
  master_key: sk-1234

2. Start the proxy

litellm --config config.yaml

# RUNNING on http://0.0.0.0:4000

3. Test it

curl -X POST "http://0.0.0.0:4000/v1/images/edits" \
  -H "Authorization: Bearer sk-1234" \
  -F "model=stability-inpaint" \
  -F "image=@original_image.png" \
  -F "mask=@mask_image.png" \
  -F "prompt=Add a beautiful garden in the masked area"

AWS Bedrock (Stability)

LiteLLM also supports Stability AI models via AWS Bedrock. This is useful if you're already using AWS infrastructure.

Usage - Bedrock Stability

from litellm import image_edit
import os

# Set AWS credentials
os.environ["AWS_ACCESS_KEY_ID"] = "your-access-key"
os.environ["AWS_SECRET_ACCESS_KEY"] = "your-secret-key"
os.environ["AWS_REGION_NAME"] = "us-east-1"

# Bedrock Stability inpainting
response = image_edit(
    model="bedrock/us.stability.stable-image-inpaint-v1:0",
    image=open("original_image.png", "rb"),
    mask=open("mask_image.png", "rb"),
    prompt="Add flowers in the masked area",
    size="1024x1024",
)
print(response)

Supported Bedrock Stability Models

All Stability AI image edit models are available via Bedrock with the bedrock/ prefix:

Direct API Model	Bedrock Model	Description
stability/stable-image-inpaint-v1:0	bedrock/us.stability.stable-image-inpaint-v1:0	Inpainting
stability/stable-conservative-upscale-v1:0	bedrock/stability.stable-conservative-upscale-v1:0	Conservative upscaling
stability/stable-creative-upscale-v1:0	bedrock/stability.stable-creative-upscale-v1:0	Creative upscaling
stability/stable-fast-upscale-v1:0	bedrock/stability.stable-fast-upscale-v1:0	Fast upscaling
stability/stable-outpaint-v1:0	bedrock/stability.stable-outpaint-v1:0	Outpainting
stability/stable-image-remove-background-v1:0	bedrock/stability.stable-image-remove-background-v1:0	Remove background
stability/stable-image-search-replace-v1:0	bedrock/stability.stable-image-search-replace-v1:0	Search and replace
stability/stable-image-search-recolor-v1:0	bedrock/stability.stable-image-search-recolor-v1:0	Search and recolor
stability/stable-image-control-sketch-v1:0	bedrock/stability.stable-image-control-sketch-v1:0	Control with sketch
stability/stable-image-control-structure-v1:0	bedrock/stability.stable-image-control-structure-v1:0	Control with structure
stability/stable-image-erase-object-v1:0	bedrock/stability.stable-image-erase-object-v1:0	Erase objects

Note: Bedrock model IDs may use us.stability.* or stability.* prefix depending on the region and model.

Comparing Routes

LiteLLM supports Stability AI models via two routes:

Route	Provider	Use Case	Image Generation	Image Editing
`stability/`	Stability AI Direct API	Direct access, all latest models	✅	✅
`bedrock/stability.*`	AWS Bedrock	AWS integration, enterprise features	✅	✅

Use stability/ for direct API access. Use bedrock/stability.* if you're already using AWS Bedrock.

Overview​

API Key​

Image Generation​

Usage - LiteLLM Python SDK​

Usage - LiteLLM Proxy Server​

1. Setup config.yaml​

2. Start the proxy​

3. Test it​

Advanced Usage - With Additional Parameters​

Supported Parameters​

Size to Aspect Ratio Mapping​

Using Stability-Specific Parameters​

Supported Image Generation Models​

Response Format​

Image Editing​

Usage - LiteLLM Python SDK​

Inpainting (Edit with Mask)​

Image Upscaling​

Image Outpainting​

Background Removal​

Search and Replace​

Image Control (Sketch/Structure)​

Erase Objects​

Supported Image Edit Models​

Usage - LiteLLM Proxy Server​

1. Setup config.yaml​

2. Start the proxy​

3. Test it​

AWS Bedrock (Stability)​

Usage - Bedrock Stability​

Supported Bedrock Stability Models​

Comparing Routes​

Overview

API Key

Image Generation

Usage - LiteLLM Python SDK

Usage - LiteLLM Proxy Server

1. Setup config.yaml

2. Start the proxy

3. Test it

Advanced Usage - With Additional Parameters

Supported Parameters

Size to Aspect Ratio Mapping

Using Stability-Specific Parameters

Supported Image Generation Models

Response Format

Image Editing

Usage - LiteLLM Python SDK

Inpainting (Edit with Mask)

Image Upscaling

Image Outpainting

Background Removal

Search and Replace

Image Control (Sketch/Structure)

Erase Objects

Supported Image Edit Models

Usage - LiteLLM Proxy Server

1. Setup config.yaml

2. Start the proxy

3. Test it

AWS Bedrock (Stability)

Usage - Bedrock Stability

Supported Bedrock Stability Models

Comparing Routes