openai/prm800k resource

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2150 stars · 129 forks observed · 2026-08-28

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

PRM800K is OpenAI's process supervision dataset containing 800,000 step-level correctness labels for model-generated solutions to MATH dataset problems. It accompanies the paper 'Let's Verify Step by Step' and includes raw labels plus labeler instructions.

Use cases

• train a process reward model for math reasoning
• get step-level correctness labels for LLM solutions
• research process supervision versus outcome supervision
• fine-tune LLMs on human-labeled reasoning steps
• evaluate LLM mathematical problem solving
• study human feedback data collection for RLHF

When to choose

• you need step-level human feedback data for training reward models
• you are researching process supervision for mathematical reasoning
• you want a benchmark dataset for LLM solution correctness

When to avoid

• you need a ready-to-use reward model rather than raw labels
• you need labels for domains other than math problems
• you want actively maintained tooling rather than a static dataset

Facets

dataset · maturity maintenance

machine-learning llm-training data-science large-language-models machine-learning mathematics python cross-platform process-supervision reward-models mathematical-reasoning step-level-labels llm-evaluation human-annotation natural-language-processing

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