# FLUX.2 [klein] 4B Base > Text-to-image generation with FLUX.2 [klein] 4B Base from Black Forest Labs. Enhanced realism, crisper text generation, and native editing capabilities. ## Overview - **Endpoint**: `https://fal.run/fal-ai/flux-2/klein/4b/base` - **Model ID**: `fal-ai/flux-2/klein/4b/base` - **Category**: text-to-image - **Kind**: inference ## Pricing - **Price**: $0.009 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: "Japanese zen garden at first light, perfect rake lines in gravel, koi pond with morning mist, temple bell in background, meditation ready" - **`negative_prompt`** (`string`, _optional_): Negative prompt for classifier-free guidance. Describes what to avoid in the image. Default value: `""` - Default: `""` - **`guidance_scale`** (`float`, _optional_): Guidance scale for classifier-free guidance. Default value: `5` - Default: `5` - Range: `0` to `20` - **`seed`** (`integer`, _optional_): The seed to use for the generation. If not provided, a random seed will be used. - **`num_inference_steps`** (`integer`, _optional_): The number of inference steps to perform. Default value: `28` - Default: `28` - Range: `4` to `50` - **`image_size`** (`ImageSize | Enum`, _optional_): The size of the image to generate. Default value: `landscape_4_3` - Default: `"landscape_4_3"` - One of: ImageSize | Enum - **`num_images`** (`integer`, _optional_): The number of images to generate. Default value: `1` - Default: `1` - Range: `1` to `4` - **`acceleration`** (`AccelerationEnum`, _optional_): The acceleration level to use for image generation. Default value: `"regular"` - Default: `"regular"` - Options: `"none"`, `"regular"`, `"high"` - **`sync_mode`** (`boolean`, _optional_): If `True`, the media will be returned as a data URI. Output is not stored when this is True. - Default: `false` - **`enable_safety_checker`** (`boolean`, _optional_): If set to true, the safety checker will be enabled. Default value: `true` - Default: `true` - **`output_format`** (`OutputFormatEnum`, _optional_): The format of the generated image. Default value: `"png"` - Default: `"png"` - Options: `"jpeg"`, `"png"`, `"webp"` **Required Parameters Example**: ```json { "prompt": "Japanese zen garden at first light, perfect rake lines in gravel, koi pond with morning mist, temple bell in background, meditation ready" } ``` **Full Example**: ```json { "prompt": "Japanese zen garden at first light, perfect rake lines in gravel, koi pond with morning mist, temple bell in background, meditation ready", "guidance_scale": 5, "num_inference_steps": 28, "image_size": "landscape_4_3", "num_images": 1, "acceleration": "regular", "enable_safety_checker": true, "output_format": "png" } ``` ### Output Schema The API returns the following output format: - **`images`** (`list`, _required_): The generated images - Array of ImageFile - Examples: [{"url":"https://v3b.fal.media/files/b/0a8a69c2/5IoN78I6tZ8ZH69SB3PhW.png"}] - **`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": "https://v3b.fal.media/files/b/0a8a69c2/5IoN78I6tZ8ZH69SB3PhW.png" } ], "prompt": "" } ``` ## Usage Examples ### cURL ```bash curl --request POST \ --url https://fal.run/fal-ai/flux-2/klein/4b/base \ --header "Authorization: Key $FAL_KEY" \ --header "Content-Type: application/json" \ --data '{ "prompt": "Japanese zen garden at first light, perfect rake lines in gravel, koi pond with morning mist, temple bell in background, meditation ready" }' ``` ### 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-2/klein/4b/base", arguments={ "prompt": "Japanese zen garden at first light, perfect rake lines in gravel, koi pond with morning mist, temple bell in background, meditation ready" }, 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-2/klein/4b/base", { input: { prompt: "Japanese zen garden at first light, perfect rake lines in gravel, koi pond with morning mist, temple bell in background, meditation ready" }, 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-2/klein/4b/base) - [API Documentation](https://fal.ai/models/fal-ai/flux-2/klein/4b/base/api) - [OpenAPI Schema](https://fal.ai/api/openapi/queue/openapi.json?endpoint_id=fal-ai/flux-2/klein/4b/base) ### 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)