Kling V2.1 I2V Master
Kling 2.1 Master: The premium endpoint for Kling 2.1, designed for top-tier image-to-video generation with unparalleled motion fluidity, cinematic visuals, and exceptional prompt precision.
Features
Kling 2.1 is an advanced AI video generation model developed by Kuaishou, designed to deliver high-quality, realistic, and coherent video content from text and image prompts. It targets creators and professionals needing scalable, cinematic-grade video generation with strong motion consistency and rich visual detail.
Kling-v2.1-i2v-master delivers the highest fidelity visuals with film-quality output, complex motion, and detailed style consistency.
Key Features
- Smooth Motion: Algorithmic stabilization for jitter-free long shots.
- High-Fidelity Rendering: Physically accurate skin, fluid, and reflection modeling.
- Prompt Understanding: Context-aware interpretation of actions/styles.
- Camera Control: Cinematic techniques like dolly zoom and motion paths.
Use Cases
- Short-Form Video Production (TikTok, Reels, YouTube Shorts).
- Creative Storyboarding and Previsualization for film and advertising.
- High-Quality Commercials and Promo Videos.
- Artistic and Stylized Video Content for NFTs and experimental projects.
- Game Development Previews and Virtual Environment Visualization.
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-v2.1-i2v-master" \
--header "Content-Type: application/json" \
--header "Authorization: Bearer ${WAVESPEED_API_KEY}" \
--data-raw '{
"prompt": "The scene opens with a small fishing boat caught in the midst of a raging storm. The sky is dark and ominous, filled with swirling clouds and flashes of lightning. The sea is tumultuous, with massive waves crashing against the boat, threatening to capsize it. The boat's deck is slick with rain, and the crew members are struggling to maintain control.",
"negative_prompt": "blur, distort, and low quality",
"image": "https://d2g64w682n9w0w.cloudfront.net/media/images/1749522950129341275_kHvrnkgd.jpeg",
"guidance_scale": 0.5,
"duration": "5"
}'
# Get the result
curl --location --request GET "https://api.wavespeed.ai/api/v3/predictions/${requestId}/result" \
--header "Authorization: Bearer ${WAVESPEED_API_KEY}"
Parameters
Task Submission Parameters
Request Parameters
| Parameter | Type | Required | Default | Range | Description |
|---|---|---|---|---|---|
| prompt | string | Yes | The scene opens with a small fishing boat caught in the midst of a raging storm. The sky is dark and ominous, filled with swirling clouds and flashes of lightning. The sea is tumultuous, with massive waves crashing against the boat, threatening to capsize it. The boat's deck is slick with rain, and the crew members are struggling to maintain control. | - | Text prompt for generation; Positive text prompt; Cannot exceed 2500 characters |
| negative_prompt | string | No | blur, distort, and low quality | - | Negative text prompt; Cannot exceed 2500 characters |
| image | string | No | https://d2g64w682n9w0w.cloudfront.net/media/images/1749522950129341275_kHvrnkgd.jpeg | - | First frame of the video; Supported image formats include.jpg/.jpeg/.png; The image file size cannot exceed 10MB, and the image resolution should not be less than 300*300px |
| guidance_scale | number | No | 0.5 | 0.00 ~ 1.00 | Flexibility in video generation; The higher the value, the lower the model’s degree of flexibility, and the stronger the relevance to the user’s prompt. |
| duration | string | No | 5 | 5, 10 | Generate video duration length seconds. |
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 Query Parameters
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 |
| 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 |