# Stable Diffusion V3 > Stable Diffusion 3 Medium (Text to Image) is a Multimodal Diffusion Transformer (MMDiT) model that improves image quality, typography, prompt understanding, and efficiency. ## Overview - **Endpoint**: `https://fal.run/fal-ai/stable-diffusion-v3-medium` - **Model ID**: `fal-ai/stable-diffusion-v3-medium` - **Category**: text-to-image - **Kind**: inference **Tags**: diffusion, style ## Pricing - **Price**: $0.035 per images For more details, see [fal.ai pricing](https://fal.ai/pricing). ## API Information This model can be used via our HTTP API or more conveniently via our client libraries. See the input and output schema below, as well as the usage examples. ### Input Schema The API accepts the following input parameters: - **`prompt`** (`string`, _required_): The prompt to generate an image from. - Examples: "Digital art, portrait of an anthropomorphic roaring Tiger warrior with full armor, close up in the middle of a battle, behind him there is a banner with the text \"Open Source\"" - **`negative_prompt`** (`string`, _optional_): The negative prompt to generate an image from. Default value: `""` - Default: `""` - **`prompt_expansion`** (`boolean`, _optional_): If set to true, prompt will be upsampled with more details. - Default: `false` - **`image_size`** (`ImageSize | Enum`, _optional_): The size of the generated image. Default value: `square_hd` - Default: `"square_hd"` - One of: ImageSize | Enum - **`num_inference_steps`** (`integer`, _optional_): The number of inference steps to perform. Default value: `28` - Default: `28` - Range: `1` to `50` - **`seed`** (`integer`, _optional_): The same seed and the same prompt given to the same version of Stable Diffusion will output the same image every time. - **`guidance_scale`** (`float`, _optional_): The CFG (Classifier Free Guidance) scale is a measure of how close you want the model to stick to your prompt when looking for a related image to show you. Default value: `5` - Default: `5` - Range: `0` to `20` - **`sync_mode`** (`boolean`, _optional_): If `True`, the media will be returned as a data URI and the output data won't be available in the request history. - Default: `false` - **`num_images`** (`integer`, _optional_): The number of images to generate. Default value: `1` - Default: `1` - Range: `1` to `4` - **`enable_safety_checker`** (`boolean`, _optional_): If set to true, the safety checker will be enabled. Default value: `true` - Default: `true` **Required Parameters Example**: ```json { "prompt": "Digital art, portrait of an anthropomorphic roaring Tiger warrior with full armor, close up in the middle of a battle, behind him there is a banner with the text \"Open Source\"" } ``` **Full Example**: ```json { "prompt": "Digital art, portrait of an anthropomorphic roaring Tiger warrior with full armor, close up in the middle of a battle, behind him there is a banner with the text \"Open Source\"", "image_size": "square_hd", "num_inference_steps": 28, "guidance_scale": 5, "num_images": 1, "enable_safety_checker": true } ``` ### Output Schema The API returns the following output format: - **`images`** (`list`, _required_): The generated image files info. - Array of Image - **`timings`** (`Timings`, _required_) - **`seed`** (`integer`, _required_): Seed of the generated Image. It will be the same value of the one passed in the input or the randomly generated that was used in case none was passed. - **`has_nsfw_concepts`** (`list`, _required_): Whether the generated images contain NSFW concepts. - Array of boolean - **`prompt`** (`string`, _required_): The prompt used for generating the image. - **`num_images`** (`integer`, _required_): The number of images generated. **Example Response**: ```json { "images": [ { "url": "", "content_type": "image/jpeg" } ], "prompt": "" } ``` ## Usage Examples ### cURL ```bash curl --request POST \ --url https://fal.run/fal-ai/stable-diffusion-v3-medium \ --header "Authorization: Key $FAL_KEY" \ --header "Content-Type: application/json" \ --data '{ "prompt": "Digital art, portrait of an anthropomorphic roaring Tiger warrior with full armor, close up in the middle of a battle, behind him there is a banner with the text \"Open Source\"" }' ``` ### Python Ensure you have the Python client installed: ```bash pip install fal-client ``` Then use the API client to make requests: ```python import fal_client def on_queue_update(update): if isinstance(update, fal_client.InProgress): for log in update.logs: print(log["message"]) result = fal_client.subscribe( "fal-ai/stable-diffusion-v3-medium", arguments={ "prompt": "Digital art, portrait of an anthropomorphic roaring Tiger warrior with full armor, close up in the middle of a battle, behind him there is a banner with the text \"Open Source\"" }, with_logs=True, on_queue_update=on_queue_update, ) print(result) ``` ### JavaScript Ensure you have the JavaScript client installed: ```bash npm install --save @fal-ai/client ``` Then use the API client to make requests: ```javascript import { fal } from "@fal-ai/client"; const result = await fal.subscribe("fal-ai/stable-diffusion-v3-medium", { input: { prompt: "Digital art, portrait of an anthropomorphic roaring Tiger warrior with full armor, close up in the middle of a battle, behind him there is a banner with the text \"Open Source\"" }, logs: true, onQueueUpdate: (update) => { if (update.status === "IN_PROGRESS") { update.logs.map((log) => log.message).forEach(console.log); } }, }); console.log(result.data); console.log(result.requestId); ``` ## Additional Resources ### Documentation - [Model Playground](https://fal.ai/models/fal-ai/stable-diffusion-v3-medium) - [API Documentation](https://fal.ai/models/fal-ai/stable-diffusion-v3-medium/api) - [OpenAPI Schema](https://fal.ai/api/openapi/queue/openapi.json?endpoint_id=fal-ai/stable-diffusion-v3-medium) - [GitHub Repository](https://huggingface.co/stabilityai/stable-diffusion-3-medium/blob/main/LICENSE) ### fal.ai Platform - [Platform Documentation](https://docs.fal.ai) - [Python Client](https://docs.fal.ai/clients/python) - [JavaScript Client](https://docs.fal.ai/clients/javascript)