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Supermimic Vibed
Supermimic Vibed is an unofficial reproduction of SuperMimic for humanoid whole-body control running in Linux containers.
Supermimic Vibed provides an independent, unreviewed implementation of the SuperMimic algorithm for humanoid whole-body control on Isaac Lab and MuJoCo-Warp. It handles 40 LAFAN1 motion clips retargeted to a 29-degree-of-freedom Unitree G1 robot model. The software trains a world model and policy using reinforcement learning techniques, featuring differentiable forward kinematics and return-based reset sampling. It targets researchers and developers working with humanoid robotics simulation on Linux systems with NVIDIA GPUs. The codebase runs inside a Docker container using a kit-less setup with MuJoCo-Warp physics.
Supermimic Vibed at a glance
- Best for: Software engineer, Researcher
- Runs on: Linux, Docker, self-hosted
- Pricing: Free
- Released: October 2026
- Category: AI coding tool
- Website: github.com/zita-ch/supermimic_vibed
Key features
- Trains humanoid whole-body control policies
- Uses MuJoCo-Warp solver and Isaac Lab 3
- Supports 40 LAFAN1 motion clips
- Includes differentiable forward kinematics
- Implements world model and policy training
- Performs offline asset import and conversion
Use it for
- Train a G1 humanoid robot to track motion clips
- Simulate whole-body control tasks using MuJoCo-Warp
- Evaluate humanoid control policies against reference motions
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- Robosimstudio — Rebuilds real robot manipulation tasks by hand or with coding agents.
- VibeCode Pro Max Kit — Stops agents from jumping straight to code without a plan.
- NeMo Molt — It scales fully-async agentic RL to frontier MoE scale with a small PyTorch stack.
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