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The best Stable Baselines3 alternatives

5 tools that do a similar job to Stable Baselines3, 5 of them open source. Each entry says what it does and who it suits, so you can pick the one that fits instead of the most famous.

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Stable Baselines3

A Python library of reliable reinforcement learning algorithms built on PyTorch.

  1. 1

    Tianshou

    Open source · MIT · ★ 11k

    A Python library for building and training reinforcement learning agents using PyTorch.

    Best for: Researchers who want to implement or modify reinforcement learning algorithms in PyTorch; Practitioners training a supported algorithm on their own Gymnasium-style environment

    Full review Stable Baselines3 vs Tianshou
  2. 2

    Gymnasium

    Open source · MIT · ★ 12.8k

    A standard Python interface for reinforcement learning environments, plus reference environments to test algor

    Best for: Researchers comparing reinforcement learning algorithms on the same environments; Students learning reinforcement learning with simple, well-known test problems

    Full review Stable Baselines3 vs Gymnasium
  3. 3

    Weights & Biases

    Open source · MIT · ★ 11.3k

    Python library to track, visualize, and manage machine learning experiments and models.

    Best for: Machine learning engineers who want to compare training runs over time; Researchers tuning hyperparameters across many experiments

    Full review Stable Baselines3 vs Weights & Biases
  4. 4

    ONNX Runtime

    Open source · MIT · ★ 22.2k

    A cross-platform library for running and training machine learning models quickly.

    Best for: Developers who want to deploy a trained model inside an application or service; Teams running the same model across Windows, Linux, macOS, or ARM devices

    Full review
  5. 5

    Petals

    Open source · MIT · ★ 10.7k

    Run big language models by sharing the work across volunteers' GPUs, BitTorrent-style.

    Best for: Developers who want to experiment with large open models like Llama 3.1 or BLOOM without owning the hardware to run them alone; Researchers prompt-tuning large models on their own tasks

    Full review

How we pick: tools in the same category that solve the same problem, projects that name each other as alternatives, and open-source projects that describe themselves as an alternative to Stable Baselines3. We don't take payment for placement.