Flux Redux Pro

Flux Redux Pro

Playground

Try it on WavespeedAI!

FLUX.1 Redux [pro] adapts FLUX.1 to create subtle image variations from a single input for quick refinements and workflow-ready restyling. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

Features

FLUX Redux Pro

FLUX Redux Pro is a powerful image variation and remix model that generates new images inspired by your source image. Upload an image, optionally add a guiding prompt, and the model creates variations that maintain the essence while exploring new possibilities.


Why It Stands Out

  • Image-driven generation: Create variations based on your source image’s style, composition, and content.
  • Optional prompt guidance: Add text prompts to steer the direction of variations.
  • Prompt Enhancer: Built-in AI-powered prompt optimization for better results.
  • Flexible resolution: Customize width and height independently for any aspect ratio.
  • Fine-tuned control: Adjust guidance scale and inference steps for precise results.
  • Reproducibility: Use the seed parameter to recreate exact results.

Parameters

ParameterRequiredDescription
imageYesSource image for variation (upload or public URL).
promptNoOptional text to guide the variation direction.
widthNoOutput width in pixels (up to 1536).
heightNoOutput height in pixels (default: 1024).
seedNoSet for reproducibility (default: 0).
num_inference_stepsNoQuality/speed trade-off (default: 28).
guidance_scaleNoPrompt adherence strength (default: 3.5).

How to Use

  1. Upload your source image — drag and drop a file or paste a public URL.
  2. Add a prompt (optional) — describe how you want to guide the variation. Use the Prompt Enhancer for AI-assisted optimization.
  3. Set dimensions — adjust width and height for your desired output size.
  4. Adjust parameters (optional) — fine-tune guidance scale and inference steps.
  5. Click Run and download your image variation.

Best Use Cases

  • Creative Exploration — Generate multiple variations of a concept to explore possibilities.
  • Design Iteration — Create variations of designs for A/B testing or client options.
  • Art Direction — Explore different interpretations of a visual concept.
  • Content Diversification — Generate multiple unique images from a single source.
  • Style Remixing — Create variations with subtle or dramatic style shifts.

Pricing

OutputPrice
Per image$0.025

Pro Tips for Best Quality

  • Without a prompt, the model generates variations based purely on the source image.
  • Add prompts to guide specific aspects you want to change or emphasize.
  • Use lower guidance scale (2–3) for subtle variations closer to the original.
  • Use higher guidance scale (4–5) for more dramatic departures from the source.
  • Generate multiple variations with different seeds to explore the possibility space.
  • Fix the seed when adjusting other parameters to isolate their effect.

Notes

  • Ensure uploaded image URLs are publicly accessible.
  • Processing time varies based on resolution and current queue load.
  • Please ensure your content complies with usage guidelines.

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-redux-pro" \
--header "Content-Type: application/json" \
--header "Authorization: Bearer ${WAVESPEED_API_KEY}" \
--data-raw '{
    "size": "1024*1024",
    "seed": 0,
    "num_inference_steps": 28,
    "guidance_scale": 3.5
}'

# 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

ParameterTypeRequiredDefaultRangeDescription
imagestringYes-The URL of the image to generate an image from.
promptstringNo-The positive prompt for the generation.
sizestringNo1024*1024256 ~ 1536 per dimensionThe size of the generated media in pixels (width*height).
seedintegerNo--1 ~ 2147483647The random seed to use for the generation.
num_inference_stepsintegerNo281 ~ 50The number of inference steps to perform.
guidance_scalenumberNo3.51.0 ~ 5.0The guidance scale to use for the generation.

Response Parameters

ParameterTypeDescription
codeintegerHTTP status code (e.g., 200 for success)
messagestringStatus message (e.g., “success”)
data.idstringUnique identifier for the prediction, Task Id
data.modelstringModel ID used for the prediction
data.outputsarrayArray of URLs to the generated content (empty when status is not completed)
data.urlsobjectObject containing related API endpoints
data.urls.getstringURL to retrieve the prediction result
data.has_nsfw_contentsarrayArray of boolean values indicating NSFW detection for each output
data.statusstringStatus of the task: created, processing, completed, or failed
data.created_atstringISO timestamp of when the request was created (e.g., “2023-04-01T12:34:56.789Z”)
data.errorstringError message (empty if no error occurred)
data.timingsobjectObject containing timing details
data.timings.inferenceintegerInference time in milliseconds

Result Request Parameters

ParameterTypeRequiredDefaultDescription
idstringYes-Task ID

Result Response Parameters

ParameterTypeDescription
codeintegerHTTP status code (e.g., 200 for success)
messagestringStatus message (e.g., “success”)
dataobjectThe prediction data object containing all details
data.idstringUnique identifier for the prediction, the ID of the prediction to get
data.modelstringModel ID used for the prediction
data.outputsstringArray of URLs to the generated content (empty when status is not completed).
data.urlsobjectObject containing related API endpoints
data.urls.getstringURL to retrieve the prediction result
data.statusstringStatus of the task: created, processing, completed, or failed
data.created_atstringISO timestamp of when the request was created (e.g., “2023-04-01T12:34:56.789Z”)
data.errorstringError message (empty if no error occurred)
data.timingsobjectObject containing timing details
data.timings.inferenceintegerInference time in milliseconds
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