open-thought/reasoning-gym

Health v2 · maintenance only

Adoption not part of the score

1494 stars · 128 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

Reasoning Gym is a Python library of procedural dataset generators and algorithmically verifiable reasoning environments for training LLMs with reinforcement learning and verifiable rewards. It offers 100+ tasks across domains like algebra, logic, graph theory, and games, with adjustable complexity and a standard score_answer verification interface.

Use cases

• generate infinite training data for RL with verifiable rewards
• train reasoning models on math and logic tasks
• evaluate LLM reasoning with algorithmic verification
• create procedurally generated puzzle environments for RLHF
• benchmark language models on reasoning tasks

When to choose

• you need scalable, procedurally generated reasoning tasks with automatic answer verification
• you are training or evaluating LLMs with RLVR and want diverse domains
• you want adjustable task difficulty for curriculum-style RL training

When to avoid

• you need static benchmark datasets with fixed test sets
• you are doing general-purpose supervised fine-tuning without verifiable answers
• you need non-Python environments or GPU-accelerated simulation

Facets

library · maturity active

machine-learning reinforcement-learning llm-training data-generation benchmarking reinforcement-learning large-language-models machine-learning python cli gym-environments verifiable-rewards procedural-datasets reasoning-tasks rl-training-data algorithms

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markdown · JSON · MCP: product_card(name="open-thought/reasoning-gym")