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What is kimodo?

nv-tlabs/kimodo — explained in plain English

Analysis updated 2026-05-18

2,350PythonAudience · researcherComplexity · 5/5Setup · hard

In one sentence

An NVIDIA AI model that generates realistic 3D human and robot motion animations from text prompts or precise pose constraints.

Mindmap

mindmap
  root((Kimodo))
    What it does
      Text to 3D motion
      Pose-constrained control
      Robot and human skeletons
    Tech stack
      Python
      PyTorch
      Hugging Face models
    Use cases
      Animation authoring
      Robotics simulation
      Motion benchmarking
    Audience
      Researchers
      Animators
      Robotics engineers

Code map

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filefunction / class

What do people build with it?

USE CASE 1

Generate a 3D character animation from a text description like 'walks then sits down'.

USE CASE 2

Control humanoid robot movement using precise pose keyframes.

USE CASE 3

Author animation sequences with an interactive timeline demo.

USE CASE 4

Benchmark different motion generation models against each other.

What is it built with?

PythonPyTorchHugging Face

How does it compare?

nv-tlabs/kimodotencent-hunyuan/hy-motion-1.0ideogram-oss/ideogram4
Stars2,3502,3412,406
LanguagePythonPythonPython
Last pushed2026-06-30
MaintenanceActive
Setup difficultyhardhardmoderate
Complexity5/55/53/5
Audienceresearcherresearcherdesigner

Figures from each repo's GitHub metadata at analysis time.

How do you get it running?

Difficulty · hard Time to first run · 1h+

Requires roughly 17GB of GPU VRAM to run locally.

So what is it?

Kimodo is an AI model from NVIDIA that generates realistic 3D human and robot movement from text descriptions. Given a text prompt like "a person walks forward then sits down," Kimodo produces a corresponding sequence of poses, a motion clip, that can be used in animation, game development, robotics simulation, or research. The model is trained on 700 hours of optical motion capture data, which is the technique of recording actual human movement using reflective markers and cameras. Beyond text prompts, Kimodo can also be controlled by more precise constraints: full-body pose keyframes (exact positions at specific moments in time), end-effector positions (where hands or feet should be at given points), 2D paths, and 2D waypoints. This gives animators and robotics engineers fine-grained control over the output. Several model variants are available, covering different skeleton formats. Some support human motion using the SOMA and SMPL-X body models (standard body representations used in research), and some target humanoid robots using the Unitree G1 robot skeleton. Models are downloaded automatically on first use from Hugging Face (a popular AI model hosting platform). The repository includes a command-line tool for generating motions, an interactive timeline-based demo for authoring animations, a benchmarking suite for comparing motion generation models, and training data annotations. Running the model locally requires approximately 17GB of GPU video memory (VRAM). It is written in Python and released by NVIDIA Research. The full README is longer than what was provided.

Copy-paste prompts

Prompt 1
Set up Kimodo and generate a motion clip from the prompt 'a person walks forward then sits down'.
Prompt 2
Use Kimodo's end-effector constraints to control where a character's hands go.
Prompt 3
Explain what GPU I need to run Kimodo locally.
Prompt 4
Show me how to use Kimodo to animate a Unitree G1 robot skeleton.

Frequently asked questions

What is kimodo?

An NVIDIA AI model that generates realistic 3D human and robot motion animations from text prompts or precise pose constraints.

What language is kimodo written in?

Mainly Python. The stack also includes Python, PyTorch, Hugging Face.

How hard is kimodo to set up?

Setup difficulty is rated hard, with roughly 1h+ to a first successful run.

Who is kimodo for?

Mainly researcher.

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