mujoco
MuJoCo Physics Simulator
Decision gist · record as of 2026-08-14
Yes, if you need a physics engine for robotics, reinforcement learning, or scientific simulation. The package is actively maintained, has no known vulnerabilities, carries a permissive Apache-2.0 license, and provides prebuilt wheels for common platforms. Medium install friction is typical for compiled bindings. Not necessary if you only need a higher-level scene API—consider wrapper libraries instead.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.10 or later.
- OpenGL rendering requires a display or headless context setup via the egl, glfw, or osmesa subpackages.
- Medium install friction due to compiled wheels for multiple architectures and Python versions (3.10–3.14).
License · maintenance · safety
Apache-2.0 (permissive) — Apache-2.0 permissive license allows commercial and private use with attribution. Pre-built wheels include third-party code (Abseil, cereal, Eigen, Collisions) under compatible licenses (Apache-2.0, BSD, MPL2).
last release 2026-07-28 (17 days) · last repo commit 2026-08-12 · 14,550 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 3,146,959 downloads/mo, #2,729 on PyPI
Alternatives
Verify before relying
pip install mujoco
import mujoco
model = mujoco.MjModel.from_xml_path('model.xml')
data = mujoco.MjData(model)
mujoco.mj_step(model, data)- Whether the package includes pre-built MuJoCo binaries or requires separate installation
- Performance characteristics and simulation accuracy compared to other physics engines
- Specific use-case maturity for robotics vs. general rigid-body simulation
What it is and what it does
MuJoCo is Google DeepMind's physics simulation engine exposed through Python bindings that give direct access to the underlying C API. It provides structs, constants, and enumerations for rigid-body dynamics, collision detection, and constraint solving. The package bundles the MuJoCo library itself, so no separate installation is needed. It depends on numpy, absl-py, etils, glfw, and pyopengl for rendering utilities.
The bindings are designed as a low-level interface rather than a high-level scene authoring API. They include utilities for setting up OpenGL rendering contexts (egl, glfw, osmesa subpackages) and are commonly used in robotics research, reinforcement learning, and physics-based simulation workflows. The package is actively maintained by DeepMind and kept synchronized with MuJoCo's latest developments.
Use it for
- Build reinforcement learning environments with physics-accurate robot simulation and control
- Prototype rigid-body dynamics for robotics applications with direct C API access
- Render physics simulations using OpenGL with built-in context setup utilities
- Conduct biomechanics or mechanical system research requiring precise collision and constraint solving
- Integrate physics simulation into game engines or interactive applications
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you need a physics engine for robotics, reinforcement learning, or scientific simulation.
The package is actively maintained, has no known vulnerabilities, carries a permissive Apache-2.0 license, and provides prebuilt wheels for common platforms. Medium install friction is typical for compiled bindings. Not necessary if you only need a higher-level scene API—consider wrapper libraries instead.
Install
mujoco on PyPI
Before you install
Medium install friction due to compiled wheels for multiple architectures and Python versions (3.10–3.14). Active maintenance with a recent release (17 days old) and strong repository activity (14550 stars). No known vulnerabilities.
Requires Python 3.10 or later. OpenGL rendering requires a display or headless context setup via the egl, glfw, or osmesa subpackages.
License in practice
Apache-2.0 permissive license allows commercial and private use with attribution. Pre-built wheels include third-party code (Abseil, cereal, Eigen, Collisions) under compatible licenses (Apache-2.0, BSD, MPL2).
Quickstart
pip install mujoco
import mujoco
model = mujoco.MjModel.from_xml_path('model.xml')
data = mujoco.MjData(model)
mujoco.mj_step(model, data)Verify before relying
- Whether the package includes pre-built MuJoCo binaries or requires separate installation
- Performance characteristics and simulation accuracy compared to other physics engines
- Specific use-case maturity for robotics vs. general rigid-body simulation
Package facts
| License | Apache-2.0 permissive |
| Python support | Supports the current Python release >=3.10 |
| Install friction | Medium. Platform-specific wheel |
| Runtime dependencies | 5 packagesabsl-pyetilsglfwnumpypyopengl |
| Maintenance | Actively maintained 17 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 3,146,959 / month, #2,729 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 5 - Production/StableIntended Audience :: DevelopersIntended Audience :: Science/ResearchNatural Language :: EnglishProgramming Language :: Python :: 3Programming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.14Topic :: Scientific/Engineering |
Evidence: mujoco-3.11.0-cp310-cp310-macosx_11_0_arm64.whl; mujoco-3.11.0-cp310-cp310-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl; mujoco-3.11.0-cp310-cp310-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl; mujoco-3.11.0-cp310-cp310-win_amd64.whl; mujoco-3.11.0-cp311-cp311-macosx_11_0_arm64.whl; mujoco-3.11.0-cp311-cp311-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl; mujoco-3.11.0-cp311-cp311-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl; mujoco-3.11.0-cp311-cp311-win_amd64.whl; mujoco-3.11.0-cp312-cp312-macosx_11_0_arm64.whl; mujoco-3.11.0-cp312-cp312-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl; mujoco-3.11.0-cp312-cp312-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl; mujoco-3.11.0-cp312-cp312-win_amd64.whl; mujoco-3.11.0-cp313-cp313-macosx_11_0_arm64.whl; mujoco-3.11.0-cp313-cp313-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl; mujoco-3.11.0-cp313-cp313-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl; mujoco-3.11.0-cp313-cp313-win_amd64.whl; mujoco-3.11.0-cp314-cp314-macosx_11_0_arm64.whl; mujoco-3.11.0-cp314-cp314-manylinux_2_27_aarch64.manylinux_2_28_aarch64.whl; mujoco-3.11.0-cp314-cp314-manylinux_2_27_x86_64.manylinux_2_28_x86_64.whl; mujoco-3.11.0-cp314-cp314t-macosx_11_0_arm64.whl
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See also mujoco-mjx · dm-control · mujoco-warp · mjviser · pybullet · pymunk · mink · libpinocchio · newton · Box2D