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Kwaivgi Kling Image V3 Edit

Kwaivgi Kling Image V3 Edit

Playground

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Kling V3 Edit is an AI model for editing and transforming images via text prompts, enabling precise modifications with natural-language instructions. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

Features

Kling Image V3 Edit

Kling Image V3 Edit is Kuaishou’s image editing model that transforms existing images based on text instructions. Upload a reference image and describe the changes you want — the model applies edits while preserving the original style, structure, and identity. Supports flexible aspect ratios, resolution options, and batch generation.


Why Choose This?

  • Text-guided editing Describe changes in natural language — no manual masking or layer editing required.

  • Style preservation Maintains the original image’s composition, lighting, and aesthetic while applying your edits.

  • Flexible aspect ratios Multiple options including 1:1, 3:4, 4:3, 9:16, 16:9 and more to fit any use case.

  • Resolution control Choose output resolution (1k and above) based on your quality and speed requirements.

  • Batch generation Generate multiple variations in a single request for rapid iteration and comparison.

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


Parameters

ParameterRequiredDescription
promptYesText description of the desired edit
imageYesReference image to edit (URL or upload)
aspect_ratioNoOutput aspect ratio (default: 3:4)
resolutionNoOutput resolution (default: 1k)
num_imagesNoNumber of images to generate (default: 1)
output_formatNoOutput format: png or jpeg (default: png)

How to Use

  1. Upload your image — provide the reference image you want to edit.
  2. Write your prompt — describe the changes you want (e.g., “Change the jacket to red leather”).
  3. Choose aspect ratio — select the output format that fits your use case.
  4. Set resolution — choose 1k for speed or higher for more detail.
  5. Set num_images — generate multiple variations if needed.
  6. Run — submit and download your edited images.

Pricing

ImagesCost
1$0.028
2$0.056
4$0.112
10$0.280

Billing Rules

  • Rate: $0.028 per image
  • Total cost = num_images × $0.028

Best Use Cases

  • Fashion & E-commerce — Change clothing colors, styles, or patterns on product images.
  • Creative Iteration — Explore variations of a concept without starting from scratch.
  • Marketing & Ads — Adapt visuals for different campaigns while maintaining brand consistency.
  • Portrait Editing — Adjust styling, backgrounds, or accessories in portrait photos.
  • Content Repurposing — Transform existing images for new contexts or platforms.

Pro Tips

  • Be specific about what should change and what should stay the same.
  • Use the Prompt Enhancer to refine vague instructions into detailed edit commands.
  • Generate multiple images (num_images > 1) to explore different interpretations of your edit.
  • Higher quality source images yield better editing results.
  • Use png format when you need lossless quality output.

Notes

  • Both prompt and image are required fields.
  • Ensure uploaded image URLs are publicly accessible.
  • Higher resolution may slightly increase processing time.

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/kwaivgi/kling-image-v3/edit" \
--header "Content-Type: application/json" \
--header "Authorization: Bearer ${WAVESPEED_API_KEY}" \
--data-raw '{
    "aspect_ratio": "16:9",
    "resolution": "1k",
    "num_images": 1,
    "output_format": "png"
}'

# 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-Text prompt for image generation.
imagestringYes-Reference image for image-to-image generation.
aspect_ratiostringNo16:916:9, 9:16, 1:1, 4:3, 3:4, 3:2, 2:3, 21:9Aspect ratio of the generated image.
resolutionstringNo1k1k, 2kImage generation resolution.
num_imagesintegerNo11 ~ 9Number of images to generate.
output_formatstringNopngpng, jpeg, webpOutput image format.

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 images.
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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