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Kwaivgi Kling Image O3 Edit

Kwaivgi Kling Image O3 Edit

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Kling O3 Edit is an AI image editing model with 4K resolution and multi-image reference support, enabling high-quality transformations with multiple reference inputs. Ready-to-use REST inference API, best performance, no coldstarts, affordable pricing.

Features

Kling Image O3 Edit

Kling Image O3 Edit is Kuaishou’s next-generation image editing model from the O3 architecture. Upload up to 10 reference images and describe how to combine or transform them — the model generates new images that blend characters, styles, and elements from your references while following your text instructions. Supports flexible aspect ratios, up to 4K resolution, and batch generation.


Why Choose This?

  • O3-generation quality The latest architecture with improved detail, composition, and prompt understanding.

  • Multi-reference support Upload up to 10 reference images to combine characters, objects, or styles in a single output.

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

  • Up to 4K resolution Choose output resolution from 1K to 4K based on your quality requirements.

  • Flexible aspect ratios Auto-detect or manually select from multiple options including 1:1, 3:4, 4:3, 9:16, 16:9.

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


Parameters

ParameterRequiredDescription
promptYesText description of the desired edit or composition
imagesYesReference images (up to 10) for characters, styles, etc.
aspect_ratioNoOutput aspect ratio (default: auto)
resolutionNoOutput resolution: 1k, 2k, or 4k (default: 1k)
num_imagesNoNumber of images to generate (default: 1)
output_formatNoOutput format: png or jpeg (default: png)

How to Use

  1. Upload your images — add up to 10 reference images containing the characters, objects, or styles you want.
  2. Write your prompt — describe how to combine or transform them (e.g., “Have the people in picture 1 and picture 2 take a selfie together.”).
  3. Choose aspect ratio — select auto or a specific format for your use case.
  4. Set resolution — choose 1k/2k for speed or 4k for maximum detail.
  5. Set num_images — generate multiple variations if needed.
  6. Run — submit and download your edited images.

Pricing

ResolutionCost per Image
1K$0.028
2K$0.028
4K$0.056

Billing Rules

  • Base rate: $0.028 per image (1K/2K)
  • 4K rate: $0.056 per image (2× base)
  • Total cost = num_images × per-image rate

Best Use Cases

  • Character Composition — Combine people from different photos into a single scene.
  • Style Fusion — Blend visual styles from multiple reference images.
  • Creative Mashups — Merge characters, objects, or environments from separate sources.
  • Marketing & Ads — Create composite visuals featuring multiple products or people.
  • Social Content — Generate imaginative scenes combining friends, celebrities, or fictional characters.

Pro Tips

  • Reference images with clear subjects and good lighting produce the best results.
  • Use “picture 1”, “picture 2” etc. in your prompt to refer to specific reference images in order.
  • Generate multiple images (num_images > 1) to explore different interpretations.
  • Use 4K resolution for print-quality or large-format outputs.
  • Auto aspect ratio adapts to your reference images — use manual selection for specific platforms.

Notes

  • Both prompt and images are required fields.
  • Maximum 10 reference images per request.
  • 4K resolution costs 2× the base rate.
  • Ensure uploaded image URLs are publicly accessible.

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-o3/edit" \
--header "Content-Type: application/json" \
--header "Authorization: Bearer ${WAVESPEED_API_KEY}" \
--data-raw '{
    "aspect_ratio": "auto",
    "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. Reference images using @Image1, @Image2, etc.
imagesarrayYes[]-Reference images (max 10). Use @Image1, @Image2 in prompt to reference.
aspect_ratiostringNoautoauto, 16:9, 9:16, 1:1, 4:3, 3:4, 3:2, 2:3, 21:9Aspect ratio of the generated image.
resolutionstringNo1k1k, 2k, 4kImage 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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