Motion Transfer
Extracts motion paths from a reference video clip and applies them frame-by-frame to a static subject image, supporting reference videos between 3 and 30 seconds in length.
Kling
Kling 2.6 Pro Motion Control
Kling V2.6 Pro Motion Control is an AI video generation model developed by Kuaishou Technology that animates static character images by extracting and transferring motion from real reference video clips. Rather than generating movement from text descriptions alone, it uses a 3D face and body reconstruction system built on deep learning-based 3D modeling to map human faces and body movements from 2D inputs, then applies those motion paths frame-by-frame to a subject image. The model runs on a Diffusion Transformer Architecture and produces output at 30 frames per second with coherent motion transitions throughout the generated clip. The model accepts reference videos between 3 and 30 seconds in length and supports a wide range of movement types, including dance routines, martial arts, walking cycles, and subtle gestures. It preserves the subject's appearance consistently across all frames without identity drift, and it supports optional text prompts to adjust scene styling, lighting, and atmosphere while keeping the motion transfer intact. Kling V2.6 Pro Motion Control is well suited for social media character animation, brand mascot animation, film pre-production prototyping, digital human content creation, and educational demonstrations.
Unknown
1,000 context
N/A output
Motion Transfer
Source Image Input
Reference Video Input
Prompt-Guided Refinement
Output Orientation Control
Native Audio Support
Model Overview
High-signal model metadata in a structured two-column overview table.
Provider
The entity that provides this model.
Kling
Input Context Window
The number of tokens supported by the input context window.
1,000
tokens
Maximum Output Tokens
The number of tokens that can be generated by the model in a single request.
N/A
tokens
Open Source
Whether the model's code is available for public use.
No
Release Date
When the model was first released.
Unknown
Knowledge Cut-off Date
When the model's knowledge was last updated.
Unknown
API Providers
The providers that offer this model. This is not an exhaustive list.
Kling
Modalities
Types of data this model can process.
Video
Text
Image
What is Kling 2.6 Pro Motion Control
A fuller summary of positioning, capabilities, and source-specific details for Kling 2.6 Pro Motion Control.
Kling V2.6 Pro Motion Control is an AI video generation model developed by Kuaishou Technology that animates static character images by extracting and transferring motion from real reference video clips. Rather than generating movement from text descriptions alone, it uses a 3D face and body reconstruction system built on deep learning-based 3D modeling to map human faces and body movements from 2D inputs, then applies those motion paths frame-by-frame to a subject image. The model runs on a Diffusion Transformer Architecture and produces output at 30 frames per second with coherent motion transitions throughout the generated clip.
The model accepts reference videos between 3 and 30 seconds in length and supports a wide range of movement types, including dance routines, martial arts, walking cycles, and subtle gestures. It preserves the subject's appearance consistently across all frames without identity drift, and it supports optional text prompts to adjust scene styling, lighting, and atmosphere while keeping the motion transfer intact. Kling V2.6 Pro Motion Control is well suited for social media character animation, brand mascot animation, film pre-production prototyping, digital human content creation, and educational demonstrations.
Capabilities
What Kling 2.6 Pro Motion Control supports
Source Image Input
Accepts a static character image via URL as the animation subject, preserving the subject's appearance consistently across all generated frames without identity drift.
Reference Video Input
Takes a reference video URL to supply the motion sequence, supporting diverse movement types including dance, martial arts, walking cycles, and fine hand gestures.
Prompt-Guided Refinement
Accepts a text prompt to adjust scene styling, lighting, and atmosphere while keeping the extracted motion transfer faithful to the reference video.
Output Orientation Control
A select input lets users choose whether the output matches the reference image's framing or the reference video's aspect ratio.
Native Audio Support
A toggle option retains the original audio track from the reference video or produces silent output, controlled via a toggleGroup input.
3D Body Reconstruction
Uses a proprietary 3D face and body reconstruction system to accurately map human faces and full-body movements from 2D inputs, enabling precise rendering of fast and intricate actions.
30 FPS Video Output
Generates video at a native 30 frames per second using a Diffusion Transformer Architecture, maintaining smooth and coherent motion transitions throughout the clip.
Pricing for Kling 2.6 Pro Motion Control
Primary API pricing shown in the same “quick compare” spirit as the reference page.
Input tokens
N/A
Per million tokens
Output tokens
N/A
Per million tokens
API Access & Providers
Places where this model is available, based on the synced detail-page metadata.
Kling
Configuration & Parameters
The configurable options currently documented for this model.
Character Orientation
SelectNegative Prompt
TextDescription of what to exclude from the video.
Supported Request Parameters
Parameters currently listed by OpenRouter or the local catalog for this model.
Resources & Documentation
Official model cards, release notes, docs, and other references synced from the source page.
Community discussion
What people think about Kling 2.6 Pro Motion Control
Kling 2.6 Pro Motion Control discussions are most active in r/klingO1, r/KlingAI_Videos, r/AI_UGC_Marketing. The strongest match in this snapshot has 255 upvotes and 53 comments.
This video was generated using **only two prompts**:
• **Nano Banana Pro** for the image generation
• **Kling 2.6 Pro Motion Control** for animation
1. Go to the [**Kling AI Video Generator**](https://imageat.com/ai-video-generator)
2. Write your full prompt or add reference images
3. Upload the image you want to animate
4. Click **Generate** and get your animated video
# Nano Banana Pro prompt:
""image\_generation\_prompt": { "subject": { "demographics": "Young woman, fair skin, slim build", "hair": { "color": "Silver grey", "style": "High pigtails, straight texture", "details": "Bangs framing the forehead and sides of the face" }, "face\_and\_makeup": { "eyes": "Green/hazel eyes, heavy winged eyeliner, long lashes", "expression": "Sultry gaze, slightly parted lips", "action": "Right index finger touching lower lip or corner of mouth" } }, "attire": { "clothing": "Sleeveless corset-style top with deep scoop neckline and visible hook-and-eye closures, partially visible skirt or shorts", "accessories": "Silver cross pendant necklace on a thin chain" }, "pose": { "type": "High-angle selfie", "body\_position": "Arm extended toward camera, body angled slightly" }, "setting": { "location": "Bedroom interior", "background\_elements": \[ "Large white textured pillows (tufted or knit)", "White sheets", "Dark wall" \], "ambient\_lighting": "Purple LED strip light running horizontally behind the headboard", "atmosphere": "Dimly lit room with colored accent lighting" }, "style\_and\_technical": { "aesthetic": \[ "E-girl", "Y2K grunge", "2000s digital aesthetic" \], "lighting\_technique": "Direct on-camera flash, harsh high-contrast lighting on subject against darker background", "camera\_settings": { "angle": "High-angle wide selfie", "distortion": "Slight wide-angle distortion", "color\_profile": "Full color, natural color rendering with vibrant neon purple accent" }, "aspect\_ratio": "3:4" } } }"
# Kling 2.6 Motion Control Prompt:
"Generate a realistic video using the attached reference image as the identity anchor. Preserve the subject’s overall appearance exactly as shown in the reference image, including face structure, skin tone, hair color and texture, body proportions, and general silhouette. Maintain strong identity consistency across all frames while allowing natural motion, subtle expression changes, and realistic body movement. Do not alter the subject’s physical traits; only introduce smooth, lifelike animation and camera motion. Ensure lighting, realism, and visual fidelity remain consistent with the reference image throughout the video."
The reference image was used strictly as an **identity anchor**. Face structure, skin tone, hair texture, proportions, and overall silhouette were preserved exactly, with no identity drift.
Motion was added naturally:
* Subtle facial expression changes
* Realistic micro-movements
* Smooth, lifelike camera motion
* Consistent lighting and visual fidelity across all frames
No extra prompt chaining, no manual keyframes — just clean prompt discipline.
**Reference image is shared in the comments.**
If you’re experimenting with identity-safe motion or prompt-efficient pipelines, this setup is surprisingly powerful.
Happy to answer questions or share prompt structure details if needed.
Generated using Nano banana pro for the visuals & Kling 2.6 pro motion control to make it move
I made it inside Degaus app
Here's the motion control prompt i used:
Generate a realistic video using the attached reference image as the identity anchor. Preserve the subject’s overall appearance exactly as shown in the reference image, including face structure, skin tone, hair color and texture, body proportions, and general silhouette. Maintain strong identity consistency across all frames while allowing natural motion, subtle expression changes, and realistic body movement. Do not alter the subject’s physical traits; only introduce smooth, lifelike animation and camera motion. Ensure lighting, realism, and visual fidelity remain consistent with the reference image throughout the video.
check my post on X: [https://x.com/Liperoo/status/2011422216257524091](https://x.com/Liperoo/status/2011422216257524091)
This is how I created it
1. Found a reference UGC video
2. Took a screenshot of the first frame and asked nanobanana pro to recreate a different person with the same setup
3. Then used kling 2.6 pro motion control with the reference video and the image from nanobanana pro
4. Viola
btw i used this tool [cursorshorts.com](http://cursorshorts.com)
FAQ
Common questions about Kling 2.6 Pro Motion Control
What inputs does Kling V2.6 Pro Motion Control require?
The model requires a source image URL (the character to animate) and a reference video URL (the motion source). Optional inputs include a text prompt for scene styling, a select input for output orientation, and a toggle for audio handling.
How long can the reference video be?
The model accepts reference videos between 3 and 30 seconds in length. The motion sequence from the full clip is captured and applied to the subject image.
What is the context window for this model?
The model has a context window of 1,000 tokens, as specified in its metadata.
When was this model trained?
According to the metadata, the model's training date is August 2025.
Does the model preserve the identity of the subject across frames?
Yes. The model is designed to keep the subject's appearance consistent across all generated frames, with no identity drift, using its 3D face and body reconstruction system.
What types of motion does the model support?
The model supports a wide range of movement types including dance routines, martial arts, walking cycles, subtle gestures, and complex choreography involving precise hand movements.
More models from Kling
Continue browsing adjacent models from the same provider.