REASONING GYM: Reasoning Environments for Reinforcement Learning with
  Verifiable Rewards
We introduce Reasoning Gym (RG), a library of reasoning environments for
reinforcement learning with verifiable rewards. It provides over 100 data
generators and verifiers spanning multiple domains including algebra,
arithmetic, computation, cognition, geometry, graph theory, logic, and various
common games. Its key innovation is the ability to generate virtually infinite
training data with adjustable complexity, unlike most previous reasoning
datasets, which are typically fixed. This procedural generation approach allows
for continuous evaluation across varying difficulty levels. Our experimental
results demonstrate the efficacy of RG in both evaluating and reinforcement
learning of reasoning models.
683e6af92139ea008faa74ba
Zafir Stojanovski
extracted_confirmed
2025-06-03T06:28:46.378Z
65144e46004a986ccc9d21d6
https://cdn-avatars.huggingface.co/v1/production/uploads/65144e46004a986ccc9d21d6/oImRY64V-UeYGdrbd_ozU.jpeg
Zafir Stojanovski
user
zafstojano
683e6af92139ea008faa74bb
Oliver Stanley
claimed_verified
2025-06-03T08:45:56.277Z
6303f5f37b50dd9d0a371b28
https://cdn-avatars.huggingface.co/v1/production/uploads/6303f5f37b50dd9d0a371b28/H25eCzAYVwBtpSpD8tnUV.jpeg
Oliver Stanley
user
OllieStanley
683e6af92139ea008faa74bc
Joe Sharratt
683e6af92139ea008faa74bd
Richard Jones
683e6af92139ea008faa74be
Abdulhakeem Adefioye
claimed_verified
2025-06-04T09:03:05.665Z
676a0fc7bce62ec5a02202ff
/avatars/cd2646ca61853f15373e3e9283c4ec42.svg
Abdulhakeem Adefioye
user
kokolamba
683e6af92139ea008faa74bf
Jean Kaddour
claimed_verified
2025-06-03T09:13:54.739Z
6304061c0547362a22a76a17
https://cdn-avatars.huggingface.co/v1/production/uploads/1661339692442-6304061c0547362a22a76a17.jpeg
Jean Kaddour
user
JeanKaddour
683e6af92139ea008faa74c0
Andreas Köpf
REASONING GYM: Reasoning Environments for Reinforcement Learning with
  Verifiable Rewards
We introduce Reasoning Gym (RG), a library of reasoning environments for
reinforcement learning with verifiable rewards. It provides over 100 data
generators and verifiers spanning multiple domains including algebra,
arithmetic, computation, cognition, geometry, graph theory, logic, and various
common games. Its key innovation is the ability to generate virtually infinite
training data with adjustable complexity, unlike most previous reasoning
datasets, which are typically fixed. This procedural generation approach allows
for continuous evaluation across varying difficulty levels. Our experimental
results demonstrate the efficacy of RG in both evaluating and reinforcement
learning of reasoning models.
Reasoning Gym provides a library of reasoning environments with verifiable rewards and procedural data generation for reinforcement learning, enabling the evaluation and training of reasoning models at varying difficulty levels.
reinforcement learning verifiable rewards data generators verifiers procedural generation reasoning models