promptfoo vs ragas
LLM application evaluation tools compared
promptfoo and ragas both help teams evaluate LLM applications with repeatable workflows. promptfoo emphasizes prompt and model comparisons plus security testing, while ragas focuses on evaluation metrics, generated test data, and feedback from production data.
promptfoo: Evaluate and Red-Team LLM Apps
Promptfoo is a TypeScript CLI and library for evaluating and red-teaming LLM-based apps. Compare prompts and models, scan for vulnerabilities, and run checks in CI/CD, with evaluations performed locally.
ragas: Evaluate and Improve LLM Applications
Ragas is a Python toolkit for evaluating and improving LLM applications with metrics, generated test data, and feedback from production data. It suits teams building evaluation workflows for retrieval-augmented generation and other LLM-powered systems.
| promptfoo | ragas | |
|---|---|---|
| Language | TypeScript | Python |
| License | MIT | Apache-2.0 |
| Stars | 26.4k | 15.9k |
| Forks | 2.6k | 1.7k |
| Last analyzed | Oct 24, 2026 | Oct 3, 2026 |
Key differences
- promptfoo is a TypeScript CLI and library; ragas is a Python toolkit.
- promptfoo includes red teaming, vulnerability scanning, and CI/CD security checks; ragas centers on metrics, test datasets, and evaluation feedback loops.
- promptfoo supports side-by-side model output comparisons across providers; ragas offers LLM-based and traditional metrics, including custom evaluations.
- promptfoo is MIT licensed; ragas is Apache-2.0 licensed.
- promptfoo describes local evaluations and a web viewer for results; ragas describes integrations with LLM frameworks and observability tools.
- promptfoo reports 25.7k stars and 2.4k forks; ragas reports 15.9k stars and 1.7k forks.
Choose promptfoo if you…
- need prompt and model comparisons alongside LLM application security checks.
- want to run evaluations or red-team checks locally or in CI/CD.
- prefer a TypeScript CLI and library under the MIT license.
Choose ragas if you…
- need evaluation metrics and generated test datasets, particularly for RAG workflows.
- want custom checks or to use production data to guide ongoing improvements.
- prefer a Python toolkit under the Apache-2.0 license.
Compare the numbers side by side, or add more projects
This comparison is generated with AI from the OSRepos analyses of both projects. Always check each project's repository and documentation before choosing.