Gymnasium is by Farama-Foundation — not by us.
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Indexed Aug 1, 2026 · 12,260 stars at index time. Maintainers: claiming verifies your identity and unlocks a higher assurance tier. Removal requests are honored.
simulation · for humans & their agents
Gymnasium
unclaimed listingactively maintainedFreeMIT
A standard API for single-agent reinforcement learning environments, with popular reference environments and related uti
by Open Source Community · New publisher
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☆ Save**Farama-Foundation/Gymnasium** is an open-source project by Farama-Foundation: A standard API for single-agent reinforcement learning environments, with popular reference environments and related utilities (formerly Gym). Indexed here so it can be found — not resold.
It is free. Get it from the upstream repository: https://github.com/Farama-Foundation/Gymnasium
From the project's own README (excerpt, reproduced for discovery under its MIT license):
Gymnasium is an open source Python library for developing and comparing reinforcement learning algorithms by providing a standard API to communicate between learning algorithms and environments, as well as a standard set of environments compliant with that API. This is a fork of OpenAI's Gym library by its maintainers (OpenAI handed over maintenance a few years ago to an outside team), and is where future maintenance will occur going forward.
The documentation website is at gymnasium.farama.org, and we have a public discord server (which we also use to coordinate development work) that you can join here: https://discord.gg/bnJ6kubTg6
Environments
Gymnasium includes the following families of environments along with a wide variety of third-party environments Classic Control - These are classic reinforcement learning based on real-world problems and physics. Box2D - These environments all involve toy games based around physics control, using box2d based physics and PyGame-based rendering Toy Text - These environments are designed to be extremely simple, with small discrete state and action spaces, and hence easy to learn. As a result, they are suitable for debugging implementations of reinforcement learning algorithms. MuJoCo - A physics engine based environments with multi-joint control which are more complex than the Box2D environments. Atari - Emulator of Atari 2600 ROMs simulated that have a high range of complexity for agents to learn. Third-party - A number of environments have been created that are compatible with the Gymnasium API. Be aware of the version that the software was created for and use the applyenvcompatibility in gymnasium.make if necessary.
Installation
To install the base Gymnasium library, use pip install gymnasium
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01Capabilities
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02Requirements & stack
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03Community
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05Versions
Full history →| Version | Channel | Released | Notes |
|---|---|---|---|
| 0.0.0 | stable | Aug 1, 2026 | Indexed listing — see the upstream repository for real release history. |