Kling V3 Motion Control
Neural Network
Kling V3 Motion Control by Kling: transfers motion from a reference video to a character image.
Specifications
- Input
- text, images, video
- Output
- video
Video generation
(duration 8 sec., 720p)
Video generation
(duration 8 sec., 1080p)
How it works Kling V3 Motion Control?
Kling V3 Motion Control works not with scene descriptions, but with ready-made motion: you take a reference video, add a character image, and the model transfers the plasticity, gestures, and trajectory to your hero. Compared to the previous Kling generation, character consistency between frames and overall image quality have significantly improved, so the hero remains recognizable from frame to frame. Access in BotHub is open from Russia without a VPN or foreign card: you pay in rubles for actual usage, and unused funds do not expire. Other video, image, and text generators remain nearby in the same window — over 250 models, so you can assemble a video entirely without changing services; for production, there is a unified API, and for companies, a contract, invoice, and admin panel. What to use the model for: animate a character from your illustration, transfer a dance or stunt from a reference to an ad, assemble a series of videos with one hero in different movements, show a client a storyboard in motion, or check an avatar's movement before shooting.Frequently asked questions about Kling V3 Motion Control
You can use generated results for commercial purposes. You own all rights to the content you create. The only restriction: make sure your prompt does not include copyrighted third-party material. You are responsible for respecting the rights to any input data.
This is a video model from kwaivgi with a focus on motion control. It generates video from text descriptions, images, and based on other videos. It is suitable for animating a static frame, assembling a short commercial, animating a character, or setting the desired camera movement trajectory for a scene.
You get a finished video clip as output: it can be downloaded or left in your generation history in your personal account. Resolution, duration, and aspect ratio depend on the selected generation parameters; see the technical specifications in the header of this page for exact values.
A separate reasoning mode is not noted in our data: the model does not show a chain of thought but proceeds directly to the video. The result depends more heavily on your prompt — how detailed the scene, movement character, and camera work are described, or which reference you uploaded.
In our data, function calling and structured JSON are not noted for this model — its task is to generate video. You can access it via the unified OpenAI-compatible BotHub API, and it is convenient to build application logic and structured responses using a text model alongside it.
Yes, according to our data, images and video are accepted as input. You can animate a finished frame or rework an existing clip by controlling the motion in the scene. Text descriptions work both on their own and together with a reference — this sets the desired dynamics more accurately.
The BotHub interface, payment with Russian cards, and support are in Russian, and access to the model works without a VPN or foreign card. There is no information about the model's own prompt language in our data, so describe the scene as detailed as possible and rely more often on the uploaded reference.