# FLUX.1 [dev] Differential Diffusion > FLUX.1 Differential Diffusion is a rapid endpoint that enables swift, granular control over image transformations through change maps, delivering fast and precise region-specific modifications while maintaining FLUX.1 [dev]'s high-quality output. ## Overview - **Endpoint**: `https://fal.run/fal-ai/flux-differential-diffusion` - **Model ID**: `fal-ai/flux-differential-diffusion` - **Category**: image-to-image - **Kind**: inference **Tags**: transformation ## Pricing - **Price**: $0.05 per megapixels 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: "Tree of life under the sea, ethereal, glittering, lens flares, cinematic lighting, artwork by Anna Dittmann & Carne Griffiths, 8k, unreal engine 5, hightly detailed, intricate detailed." - **`image_url`** (`string`, _required_): URL of image to use as initial image. - Examples: "https://fal.media/files/koala/h6a7KK2Ie_inuGbdartoX.jpeg" - **`change_map_image_url`** (`string`, _required_): URL of change map. - Examples: "https://fal.media/files/zebra/Wh4IYAiAAcVbuZ8M9ZMSn.jpeg" - **`strength`** (`float`, _optional_): The strength to use for image-to-image. 1.0 is completely remakes the image while 0.0 preserves the original. Default value: `0.85` - Default: `0.85` - Range: `0.01` to `1` - **`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 the model 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: `3.5` - Default: `3.5` - 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": "Tree of life under the sea, ethereal, glittering, lens flares, cinematic lighting, artwork by Anna Dittmann & Carne Griffiths, 8k, unreal engine 5, hightly detailed, intricate detailed.", "image_url": "https://fal.media/files/koala/h6a7KK2Ie_inuGbdartoX.jpeg", "change_map_image_url": "https://fal.media/files/zebra/Wh4IYAiAAcVbuZ8M9ZMSn.jpeg" } ``` **Full Example**: ```json { "prompt": "Tree of life under the sea, ethereal, glittering, lens flares, cinematic lighting, artwork by Anna Dittmann & Carne Griffiths, 8k, unreal engine 5, hightly detailed, intricate detailed.", "image_url": "https://fal.media/files/koala/h6a7KK2Ie_inuGbdartoX.jpeg", "change_map_image_url": "https://fal.media/files/zebra/Wh4IYAiAAcVbuZ8M9ZMSn.jpeg", "strength": 0.85, "num_inference_steps": 28, "guidance_scale": 3.5, "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. **Example Response**: ```json { "images": [ { "url": "", "content_type": "image/jpeg" } ], "prompt": "" } ``` ## Usage Examples ### cURL ```bash curl --request POST \ --url https://fal.run/fal-ai/flux-differential-diffusion \ --header "Authorization: Key $FAL_KEY" \ --header "Content-Type: application/json" \ --data '{ "prompt": "Tree of life under the sea, ethereal, glittering, lens flares, cinematic lighting, artwork by Anna Dittmann & Carne Griffiths, 8k, unreal engine 5, hightly detailed, intricate detailed.", "image_url": "https://fal.media/files/koala/h6a7KK2Ie_inuGbdartoX.jpeg", "change_map_image_url": "https://fal.media/files/zebra/Wh4IYAiAAcVbuZ8M9ZMSn.jpeg" }' ``` ### 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/flux-differential-diffusion", arguments={ "prompt": "Tree of life under the sea, ethereal, glittering, lens flares, cinematic lighting, artwork by Anna Dittmann & Carne Griffiths, 8k, unreal engine 5, hightly detailed, intricate detailed.", "image_url": "https://fal.media/files/koala/h6a7KK2Ie_inuGbdartoX.jpeg", "change_map_image_url": "https://fal.media/files/zebra/Wh4IYAiAAcVbuZ8M9ZMSn.jpeg" }, 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/flux-differential-diffusion", { input: { prompt: "Tree of life under the sea, ethereal, glittering, lens flares, cinematic lighting, artwork by Anna Dittmann & Carne Griffiths, 8k, unreal engine 5, hightly detailed, intricate detailed.", image_url: "https://fal.media/files/koala/h6a7KK2Ie_inuGbdartoX.jpeg", change_map_image_url: "https://fal.media/files/zebra/Wh4IYAiAAcVbuZ8M9ZMSn.jpeg" }, 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/flux-differential-diffusion) - [API Documentation](https://fal.ai/models/fal-ai/flux-differential-diffusion/api) - [OpenAPI Schema](https://fal.ai/api/openapi/queue/openapi.json?endpoint_id=fal-ai/flux-differential-diffusion) ### 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)