Kwaivgi Kling Image O3 Edit
Playground
Try it on WavespeedAI!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?
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O3-generation quality The latest architecture with improved detail, composition, and prompt understanding.
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Multi-reference support Upload up to 10 reference images to combine characters, objects, or styles in a single output.
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Text-guided editing Describe changes or compositions in natural language — no manual masking required.
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Up to 4K resolution Choose output resolution from 1K to 4K based on your quality requirements.
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Flexible aspect ratios Auto-detect or manually select from multiple options including 1:1, 3:4, 4:3, 9:16, 16:9.
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Batch generation Generate multiple variations in a single request for rapid iteration.
Parameters
| Parameter | Required | Description |
|---|---|---|
| prompt | Yes | Text description of the desired edit or composition |
| images | Yes | Reference images (up to 10) for characters, styles, etc. |
| aspect_ratio | No | Output aspect ratio (default: auto) |
| resolution | No | Output resolution: 1k, 2k, or 4k (default: 1k) |
| num_images | No | Number of images to generate (default: 1) |
| output_format | No | Output format: png or jpeg (default: png) |
How to Use
- Upload your images — add up to 10 reference images containing the characters, objects, or styles you want.
- 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.”).
- Choose aspect ratio — select auto or a specific format for your use case.
- Set resolution — choose 1k/2k for speed or 4k for maximum detail.
- Set num_images — generate multiple variations if needed.
- Run — submit and download your edited images.
Pricing
| Resolution | Cost 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.
Related Models
- Kling Image O3 Text-to-Image — Generate images from text prompts with O3 quality.
- Kling Image V3 Edit — Previous generation image editing model.
- Kling Video O3 Pro Image-to-Video — Animate edited images into video.
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
| Parameter | Type | Required | Default | Range | Description |
|---|---|---|---|---|---|
| prompt | string | Yes | - | Text prompt for image generation. Reference images using @Image1, @Image2, etc. | |
| images | array | Yes | [] | - | Reference images (max 10). Use @Image1, @Image2 in prompt to reference. |
| aspect_ratio | string | No | auto | auto, 16:9, 9:16, 1:1, 4:3, 3:4, 3:2, 2:3, 21:9 | Aspect ratio of the generated image. |
| resolution | string | No | 1k | 1k, 2k, 4k | Image generation resolution. |
| num_images | integer | No | 1 | 1 ~ 9 | Number of images to generate. |
| output_format | string | No | png | png, jpeg, webp | Output image format. |
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 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, the ID of the prediction to get |
| data.model | string | Model ID used for the prediction |
| data.outputs | string | Array of URLs to the generated images. |
| data.urls | object | Object containing related API endpoints |
| data.urls.get | string | URL to retrieve the prediction result |
| 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 |