Browse ModelsWavespeed AIFlux 2 Klein 9b Edit LoRA

Flux 2 Klein 9b Edit LoRA

Flux 2 Klein 9b Edit LoRA

Playground

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FLUX.2 [klein] 9B Edit with LoRA support is a high-quality image editing model with 9B parameters, offering precise modifications using natural language instructions and personalized styles via custom LoRA adapters. Ready-to-use REST inference API, best performance, no cold starts, affordable pricing.

Features

FLUX.2 Klein 9B Edit LoRA

FLUX.2 Klein 9B Edit LoRA is a powerful image editing model with full LoRA support. With 9B parameters, it delivers higher quality edits and better prompt understanding. Upload images, describe your edits, and optionally apply custom LoRA adapters for personalized styles.


Why Choose This?

  • Enhanced editing quality 9B parameter model delivers richer detail and better prompt interpretation than the 4B variant.

  • Text-guided editing Describe edits in natural language — transform styles, modify content, apply effects, and more.

  • LoRA support Apply custom LoRA adapters for personalized styles, characters, or visual aesthetics.

  • Multi-image input Upload multiple reference images for context-aware editing.

  • Flexible output sizing Optionally set output size, or leave empty to match input image dimensions.

  • Prompt Enhancer Built-in tool to automatically improve your prompts for better results.


Parameters

ParameterRequiredDescription
promptYesText description of the desired edit
imagesYesSource images to edit (can add multiple)
lorasNoList of LoRA adapters to apply
sizeNoOutput dimensions (empty = same as input image)
seedNoRandom seed for reproducibility (-1 for random)

LoRA Format

Each LoRA in the loras array has:

  • path (required) — URL to the LoRA weights file
  • scale (optional) — Weight multiplier, default 1

How to Use

  1. Write your prompt — describe the edit you want (e.g., “make it a real picture”, “add sunset lighting”).
  2. Upload images — add source images using ”+ Add Item” button.
  3. Add LoRAs (optional) — click ”+ Add Item” to include custom LoRA adapters.
  4. Set size (optional) — specify output dimensions or leave empty to match input.
  5. Set seed — use -1 for random, or specify a number for reproducibility.
  6. Run — submit and download the edited image.

Pricing

ItemCost
Per image$0.021

Simple flat-rate pricing regardless of image size or LoRA count.


Best Use Cases

  • Style Transfer — Transform images with custom LoRA styles.
  • Reality Enhancement — Convert illustrations or renders to photorealistic images.
  • Character Consistency — Apply character LoRAs while editing images.
  • High-Quality Retouching — When 4B quality isn’t enough for professional work.
  • Production Editing — Balanced quality and cost for professional content.

Pro Tips

  • Be specific in your prompt — clearly describe what should change.
  • Use LoRAs to add consistent styles across multiple edits.
  • Leave size empty to preserve original image dimensions.
  • Start with LoRA scale 1.0 and adjust based on results.
  • Use the same seed to compare different prompts or LoRA combinations.

Notes

  • If size is not specified, output matches input image dimensions.
  • 9B model offers better detail than 4B at slightly higher cost.
  • For best results, use high-quality source 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-2-klein-9b/edit-lora" \
--header "Content-Type: application/json" \
--header "Authorization: Bearer ${WAVESPEED_API_KEY}" \
--data-raw '{
    "loras": [],
    "seed": -1,
    "enable_sync_mode": false,
    "enable_base64_output": false
}'

# 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
promptstringYes-The editing instruction.
imagesarrayYes[]1 ~ 3 itemsList of reference image URLs (1-3 images).
lorasarrayNomax 3 itemsList of LoRAs to apply (max 3).
loras[].pathstringYes-Path to the LoRA model
loras[].scalefloatYes-0.0 ~ 4.0Scale of the LoRA model
sizestringNo-256 ~ 1536 per dimension
seedintegerNo-1-1 ~ 2147483647The random seed to use for the generation. -1 means a random seed will be used.
enable_sync_modebooleanNofalse-If set to true, the function will wait for the result to be generated and uploaded before returning the response. It allows you to get the result directly in the response. This property is only available through the API.
enable_base64_outputbooleanNofalse-If enabled, the output will be encoded into a BASE64 string instead of a URL. This property is only available through the API.

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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