PufferLib is a fast and sane reinforcement learning library that can train tiny, super-human models in seconds. The included learning algorithm, hyperparameter tuning, and simulation methods are the product of our own research. All our tools are free and open source. Need a high performance environment for your application? We build them professionally and offer training + extended support. Contact jsuarez🐡puffer🐡ai.
The demo below is running live 100% client side in your browser. Hold shift to take control!
Pong
A classic reimagined: Play against our reinforcement learned agent or watch AI vs AI matches. Running at 1M+ steps per second directly in your browser.
BibTeX
Repo / RLC Best Paper 2025 / Original Whitepaper@misc{pufferlib,
title = {{PufferLib}: Fast and Sane Simplifying Reinforcement Learning for Complex Game Environments},
author = {Joseph Suarez},
howpublished = {\url{https://github.com/PufferAI/PufferLib}},
year = {2024},
note = {GitHub repository}
}
@article{suarez2025pufferlib,
title = {{PufferLib} 2.0: {R}einforcement Learning at 1M steps/s},
author = {Suarez, Joseph},
journal = {Reinforcement Learning Journal},
volume = {6},
pages = {1378--1388},
year = {2025}
}
@misc{suarez2024pufferlibmakingreinforcementlearning,
title={PufferLib: Making Reinforcement Learning
Libraries and Environments Play Nice},
author={Joseph Suarez},
year={2024},
eprint={2406.12905},
archivePrefix={arXiv},
primaryClass={cs.LG},
url={https://arxiv.org/abs/2406.12905},
}