Kling 2.6 Standard Motion Control transfers motion from reference videos to animate still images. Upload a character image and a motion clip (dance, action, gesture), and the model extracts the movement to generate smooth, realistic video. Ready-to-use REST inference API, best performance, no cold starts, affordable pricing.
Idle
$0.21per run·~47 / $10
Transfer motion from any video onto your character with Kling V2.6 Motion Control. Upload a reference image of your subject and a motion video — the model generates your character performing those exact movements. Perfect for dance videos, action sequences, and character animation.
| Parameter | Required | Description |
|---|---|---|
| image | Yes | Reference image of your character/person. |
| video | Yes | Motion reference video to transfer movements from. |
| character_orientation | Yes | Direction character is facing (front, side, back). |
| prompt | No | Additional scene description or style guidance. |
| negative_prompt | No | Elements to avoid in the generated video. |
| keep_original_sound | No | Retain audio from the original motion video. |
Per 3-second billing based on video duration. Minimum 3 seconds, maximum 30 seconds.
| Duration | Calculation | Cost |
|---|---|---|
| 3 seconds (min) | 3 ÷ 3 × $0.21 | $0.21 |
| 6 seconds | 6 ÷ 3 × $0.21 | $0.42 |
| 10 seconds | 10 ÷ 3 × $0.21 | $0.70 |
| 15 seconds | 15 ÷ 3 × $0.21 | $1.05 |
| 30 seconds (max) | 30 ÷ 3 × $0.21 | $2.10 |
| Orientation | When to Use |
|---|---|
| Front | Character facing camera directly |
| Side | Character in profile view |
| Back | Character facing away from camera |
Kling V2.6 Pro Motion Control — Professional-grade motion transfer that maps movements from any reference video onto your character with superior quality and precision.
Wan 2.2 Animate — Transform static images into dynamic videos with AI-powered animation, bringing photos and illustrations to life with natural motion.
Wan 2.2 Fun Control — Creative pose and motion control for image-to-video generation, enabling playful character animations with customizable movements.
Grab a WaveSpeedAI API key, then call POST https://api.wavespeed.ai/api/v3/kwaivgi/kling-v2.6-std/motion-control with your input as JSON. The endpoint returns a prediction id; poll the prediction endpoint until status flips to completed, then read the output URL from data.outputs[0]. Examples for Kling v2.6 Std Motion Control below.
# Submit the prediction
curl -X POST "https://api.wavespeed.ai/api/v3/kwaivgi/kling-v2.6-std/motion-control" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $WAVESPEED_API_KEY" \
-d '{
"image": "https://example.com/your-input.jpg",
"video": "https://example.com/your-input.mp4",
"character_orientation": "video",
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"negative_prompt": "blurry, low quality, distorted",
"keep_original_sound": true
}'
# Response includes a prediction id. Poll for the result:
curl -X GET "https://api.wavespeed.ai/api/v3/predictions/{request_id}/result" \
-H "Authorization: Bearer $WAVESPEED_API_KEY"
# When status is "completed", read the output from data.outputs[0].// npm install wavespeed
const WaveSpeed = require('wavespeed');
const client = new WaveSpeed(); // reads WAVESPEED_API_KEY from env
const result = await client.run("kwaivgi/kling-v2.6-std/motion-control", {
"image": "https://example.com/your-input.jpg",
"video": "https://example.com/your-input.mp4",
"character_orientation": "video",
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"negative_prompt": "blurry, low quality, distorted",
"keep_original_sound": true
});
console.log(result.outputs[0]); // → URL of the generated output# pip install wavespeed
import wavespeed
output = wavespeed.run(
"kwaivgi/kling-v2.6-std/motion-control",
{
"image": "https://example.com/your-input.jpg",
"video": "https://example.com/your-input.mp4",
"character_orientation": "video",
"prompt": "A cinematic shot of a city at sunset, soft golden light",
"negative_prompt": "blurry, low quality, distorted",
"keep_original_sound": true
}
)
print(output["outputs"][0]) # → URL of the generated outputKling v2.6 Std Motion Control is a Kuaishou model for pose / motion driven video, exposed as a REST API on WaveSpeedAI. Kling 2.6 Standard Motion Control transfers motion from reference videos to animate still images. Upload a character image and a motion clip (dance, action, gesture), and the model extracts the movement to generate smooth, realistic video. Ready-to-use REST inference API, best performance, no cold starts, affordable pricing. You can call it programmatically or try it from the playground above.
POST your input parameters to the model's REST endpoint (shown in the API tab of this playground) with your WaveSpeedAI API key in the Authorization header. Submission returns a prediction ID; poll the prediction endpoint until status flips to "completed", then read the output URL from the result. The playground generates a ready-to-paste code sample in Python, JavaScript, or cURL for whatever inputs you've set. Full request/response shape is documented at https://wavespeed.ai/docs/docs-api/kwaivgi/kwaivgi-kling-v2.6-std-motion-control.
Kling v2.6 Std Motion Control starts at $0.21 per run. That figure is the base price — the final charge scales with the parameters you set in the form (output size, length, count, references, or whatever knobs this model exposes), so a higher-quality or larger output costs more than a minimal one. The exact cost for your current input is shown live next to the Generate button before you submit, and the actual per-call charge is recorded on the prediction afterwards.
Key inputs: `prompt`, `image`, `video`, `negative_prompt`, `character_orientation`, `keep_original_sound`. The full JSON schema (types, defaults, allowed values) is rendered above the Generate button and mirrored in the API reference at https://wavespeed.ai/docs/docs-api/kwaivgi/kwaivgi-kling-v2.6-std-motion-control.
Average end-to-end generation time on WaveSpeedAI is around 575 seconds per request — measured across recent runs. Queue time scales with global demand; live status is visible in the prediction record.
Commercial usage rights depend on the model's license, set by its provider (Kuaishou). The license summary appears on the model card above; see WaveSpeedAI's Terms of Service for platform-level conditions.