Kling V2.6 Motion Control
Neural Network
Kling V2.6 Motion Control is a Kling video model for precise control of character actions and facial expressions via reference images.
Specifications
- Input
- text, images, video
- Output
- video
Video generation
(duration 8 sec., 720p)
Video generation
(duration 8 sec., 1080p)
How it works Kling V2.6 Motion Control?
Kling V2.6 Motion Control is a Kling video model that precisely controls character actions and facial expressions: you provide a reference image, describe the character's movement and emotions, and the model transfers them into a finished video. This level of control is valued in animation, where movement and facial expressions must match the vision. You can work with the model directly in BotHub: access is open from Russia without a VPN or foreign card, payment is in rubles and only for actual usage — tokens and caps do not expire. Need other models? Switch between them in one window, and connect a unified OpenAI-compatible API for your services. Data is protected by AES-GCM encryption and is not saved. For companies, we offer contracts, invoices, EDI, an admin panel, and limits. Scenarios: animate a character from a static image for ads, set precise emotions and gestures for short video characters, create mascot or game character animations from concept art, showcase product movement in presentations, and prepare videos for stories and promos without reshoots.Frequently asked questions about Kling V2.6 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 generation model: it creates a clip from a text description, animates a static image, and transfers motion from a reference video to a character. It is suitable for character animation, dance and sports scenes, and cases where you need to replicate specific movement from an existing clip.
Exact resolution and formats are not specified in our data, so we cannot promise specific figures. The model accepts a text description, image, or video and returns a finished video clip, with quality parameters selected for each request during generation. It is more convenient to check current specifications directly in the interface.
No. This is a generative video model, not a text assistant, so it does not have a reasoning step before answering — this capability is not noted in our data. It immediately builds a clip based on your description or reference, without intermediate explanations or plans.
No, function calling and structured JSON output are not noted for this model in our data. This is a video generation tool: you provide a text description and reference files, and receive a finished video sequence. Such mechanics are more relevant for text models that work with external services.
Yes, in addition to text, the model accepts images and video as input — this is the basis for image-to-video and video-to-video modes, where motion is taken from a reference. There is no mention of audio upload in our data, so we cannot confirm this in advance: this point should be checked in the interface.
According to our data, the model is marked as ENGLISH_ONLY, so it is more reliable to formulate scene and motion descriptions in English, and it is better to translate Russian queries in advance. Access to BotHub remains completely convenient from Russia: no VPN, no foreign card, and payment in rubles.