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OpenAI Evals vs Promptfoo

If you are wiring up LLM tests, you have probably found both of these. OpenAI Evals is a registry-based framework. You define evals and run them against a model, and the design grew up around OpenAI's own ecosystem. Promptfoo is a config-driven runner that stays model-agnostic. You point one config file at many providers and compare outputs side by side.

DimensionOpenAI EvalsPromptfoo
What it isAn eval framework with a shared eval registryA config-driven, model-agnostic eval runner
LicenseOpen sourceOpen source
You write evals asRegistry entries plus PythonYAML config, with JS/TS when needed
Model coverageOpenAI-centric by designMany providers, built to compare
Feels likeContributing to an eval libraryA CLI you point at prompts and models
CI integrationWorkable, less turnkeyStrong, built to run as a gate
Red-teamingNot the focusYes, a real strength
Best forDeep OpenAI eval work and shared benchmarksCross-model comparison and a fast CI gate
Pick OpenAI Evals if

You build mainly on OpenAI, you want to write evals in Python, or you want to draw on a shared registry of eval templates. OpenAI Evals fits teams who live inside that ecosystem and want their evals close to it.

Pick Promptfoo if

You want to compare several models against the same prompts, or you need an eval gate running in CI this week without committing to one vendor. Promptfoo gets you from a config file to a passing gate fast, and the red-teaming is a real bonus.

The honest take

For most teams starting evals today, I reach for Promptfoo. The config-first workflow and cross-model comparison get you to a real CI gate faster, and staying model-agnostic matters because most teams end up testing more than one model. OpenAI Evals is the better home if your world is OpenAI and you want Python evals plus the shared registry. The common mistake is picking by whose logo is on the box instead of by how the tool actually works. What moves the needle is writing ten honest test cases and wiring them into CI. Either tool does that.

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Comparisons reflect each tool’s general positioning as of 2026 and focus on architecture and fit rather than fast-moving pricing or version details. Check each project’s own docs before you commit.
© 2026 Jason Teixeira · Sage Ideas LLC · All comparisons · Learn