OpenAI Evals

OpenAI Evals is a Python framework and public registry for evaluating large language models and LLM-powered systems. It ships with a large catalog of prebuilt evals covering reasoning, factuality, coding, safety, and domain-specific benchmarks, and lets you register your own private evals using YAML plus a small amount of Python. Evals can be basic (exact match, includes, fuzzy match), model-graded (using a stronger model as a judge), or fully custom.

The framework is aimed at ML engineers and applied teams shipping GPT-based products who need reproducible, versioned test suites rather than vibes-based prompt tweaking. It's free and MIT-licensed, but running the evals themselves costs whatever the underlying OpenAI API calls cost, which can add up quickly on large graded suites. It's less polished than commercial eval platforms (Braintrust, Langsmith, Humanloop) but it's the canonical reference implementation and the format many benchmarks are published in.

Integrations include Weights & Biases for run tracking and optional Snowflake logging. Python 3.9+ and Git-LFS are required, and while the registry is OpenAI-flavored, the eval logic itself is portable enough that teams often adapt it to other providers.