google-deepmind

    google-deepmind/mujoco_warp

    GPU-optimized version of the MuJoCo physics simulator, designed for NVIDIA hardware.

    backend
    mujoco-warp
    nvidia-warp
    Python
    Apache-2.0
    1.6K stars
    266 forks
    1.6K GitHub watchers
    Updated Oct 31, 2026
    View on GitHub

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    Where it stands

    Rank, growth pace and release cadence relative to everything GStars tracks.

    5 releases in the last 90 days, the latest 8 days ago, with 69 contributors on GitHub.

    Gained 28% more stars in the last 90 days than in the 90 days before.

    Use Cases & Benefits

    • Provides a GPU-optimized version of the MuJoCo physics simulator tailored for NVIDIA hardware acceleration.
    • Delivers enhanced simulation performance by leveraging NVIDIA Warp for efficient GPU computation.
    • Use for accelerating physics simulations in robotics research requiring high-fidelity dynamics on NVIDIA GPUs.
    • Use for integrating GPU-accelerated physics engines into machine learning frameworks for policy training.
    • Use for developing and testing custom Warp kernels to optimize physics computations on supported platforms.

    Should you depend on it?

    License terms, project hygiene and risks, from GitHub metadata and GStars' snapshots.

    License

    Apache 2.0

    Permissive: commercial use, modification and redistribution are allowed with attribution; includes an explicit patent grant from contributors.

    Community files

    • README: present
    • Contributing guide: present

    Watch-outs

    No watch-outs from GStars' checks.

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    From the README

    MJWarp is a GPU-optimized version of the MuJoCo physics simulator, designed for NVIDIA hardware.

    MJWarp uses NVIDIA Warp to circumvent many of the sharp bits in MuJoCo MJX. MJWarp is integrated into both MJX and Newton.

    MJWarp is maintained by Google DeepMind and NVIDIA.

    MuJoCo Warp is currently supported on Windows or Linux on x86-64 architecture (to be expanded to more platforms and architectures soon).

    Windows (native Python only, not MSYS2 or WSL)

    Then install MJWarp in editable mode for local development:

    Should print out something like XX passed in XX.XXs at the end!

    If you plan to write Warp kernels for MJWarp, please use the kernel_analyzer vscode plugin located in contrib/kernel_analyzer. Please see the README.md there for details on how to install it and use it. The same kernel analyzer will be run on any PR you open, so it's important to fix any issues it reports.

    Differentiability via Warp is not currently available.

    Excerpt from the google-deepmind/mujoco_warp README on GitHub (Apache-2.0 license). © its authors.Read the full README on GitHub

    Daily snapshots

    Stars gained per day, and how forks and open issues moved, from GStars' daily snapshots

    Forks

    266+83

    Open issues

    98+46

    Compared with peers in Backend

    Fastest-growing repositories GStars tracks in this cohort for the week of Nov 1, by 7-day star growth

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