Flux Kontext Dev Multi Ultra Fast

FLUX.1 Kontext Multi Ultra Fast [dev] is an optimized, high-performance version of the state-of-the-art image editing model that lets you edit multiple images using text prompts. It maintains the same high quality while delivering significantly faster processing times.

Features

FLUX.1 Kontext Multi Ultra Fast [dev] is an optimized, high-performance version of the state-of-the-art image editing model by Black Forest Labs. It maintains all the powerful features of the original model while delivering significantly faster processing times. You can edit multiple images using text prompts with exceptional speed without compromising on quality.

Key Features

High Performance: Optimized processing pipeline for significantly faster image generation and editing.
Batch Processing: Edit multiple images simultaneously with consistent results.
Context-Aware Editing: Intelligent understanding of image semantics for precise modifications that preserve natural aesthetics.
Lightning Fast: Optimized neural architecture delivers professional results in seconds for real-time workflows.
Precision Control: Granular control over transformations with intuitive parameters and fine-tuning capabilities.
SOTA Quality: State-of-the-art results surpassing existing models across all quality benchmarks.

Use Cases

Style Transfer: Convert multiple photos to different art styles, like watercolor, oil painting and sketches.
Object/Clothing Changes: Modify hairstyles, add accessories, change colors across multiple images.
Text Editing: Replace text in signs, posters, and labels in bulk.
Background Swapping: Change environments while preserving subjects across multiple images.

Authentication

For authentication details, please refer to the Authentication Guide.

API Endpoints

Submit Task & Query Result


# Submit the task
curl --location --request POST "https://api.wavespeed.ai/api/v3/wavespeed-ai/flux-kontext-dev/multi-ultra-fast" \
--header "Content-Type: application/json" \
--header "Authorization: Bearer ${WAVESPEED_API_KEY}" \
--data-raw '{
    "prompt": "A woman wears the dress and the hat, near the sea",
    "images": [
        "https://d2g64w682n9w0w.cloudfront.net/media/images/1750592630644621512_wxGCzvqn.png",
        "https://d2g64w682n9w0w.cloudfront.net/media/images/1750651475543258372_mxurokgd.png",
        "https://d2g64w682n9w0w.cloudfront.net/media/images/1750651331146489846_GS62YUQM.jpg"
    ],
    "size": "1024*1024",
    "num_inference_steps": 28,
    "guidance_scale": 2.5,
    "num_images": 1,
    "seed": -1,
    "enable_base64_output": false,
    "enable_safety_checker": true
}'

# Get the result
curl --location --request GET "https://api.wavespeed.ai/api/v3/predictions/${requestId}/result" \
--header "Authorization: Bearer ${WAVESPEED_API_KEY}"

Parameters

Task Submission Parameters

Request Parameters

Parameter	Type	Required	Default	Range	Description
prompt	string	Yes	A woman wears the dress and the hat, near the sea	-	The prompt to generate an image from.
images	array	No	https://d2g64w682n9w0w.cloudfront.net/media/images/1750592630644621512_wxGCzvqn.pnghttps://d2g64w682n9w0w.cloudfront.net/media/images/1750651475543258372_mxurokgd.pnghttps://d2g64w682n9w0w.cloudfront.net/media/images/1750651331146489846_GS62YUQM.jpg	-	URL of images to use while generating the image.
size	string	No	1024*1024	512 ~ 1536 per dimension	The size of the generated image.
num_inference_steps	integer	No	28	1 ~ 50	The number of inference steps to perform.
guidance_scale	number	No	2.5	1.0 ~ 20.0	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.
num_images	integer	No	1	1 ~ 4	The number of images to generate.
seed	integer	No	-1	-1 ~ 9999999999	The same seed and the same prompt given to the same version of the model will output the same image every time.
enable_base64_output	boolean	No	false	-	If enabled, the output will be encoded into a BASE64 string instead of a URL.
enable_safety_checker	boolean	No	true	-	If set to true, the safety checker will be enabled.

Response Parameters

Parameter	Type	Description
code	integer	HTTP status code (e.g., 200 for success)
message	string	Status message (e.g., “success”)
data.id	string	Unique identifier for the prediction, Task Id
data.model	string	Model ID used for the prediction
data.outputs	array	Array of URLs to the generated content (empty when status is not `completed`)
data.urls	object	Object containing related API endpoints
data.urls.get	string	URL to retrieve the prediction result
data.has_nsfw_contents	array	Array of boolean values indicating NSFW detection for each output
data.status	string	Status of the task: `created`, `processing`, `completed`, or `failed`
data.created_at	string	ISO timestamp of when the request was created (e.g., “2023-04-01T12:34:56.789Z”)
data.error	string	Error message (empty if no error occurred)
data.timings	object	Object containing timing details
data.timings.inference	integer	Inference time in milliseconds

Result Query Parameters

Result Request Parameters

Parameter	Type	Required	Default	Description
id	string	Yes	-	Task ID

Result Response Parameters

Parameter	Type	Description
code	integer	HTTP status code (e.g., 200 for success)
message	string	Status message (e.g., “success”)
data	object	The prediction data object containing all details
data.id	string	Unique identifier for the prediction
data.model	string	Model ID used for the prediction
data.outputs	array	Array of URLs to the generated content (empty when status is not `completed`)
data.urls	object	Object containing related API endpoints
data.urls.get	string	URL to retrieve the prediction result
data.has_nsfw_contents	array	Array of boolean values indicating NSFW detection for each output
data.status	string	Status of the task: `created`, `processing`, `completed`, or `failed`
data.created_at	string	ISO timestamp of when the request was created (e.g., “2023-04-01T12:34:56.789Z”)
data.error	string	Error message (empty if no error occurred)
data.timings	object	Object containing timing details
data.timings.inference	integer	Inference time in milliseconds

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