DeepEval vs Ragas
A side-by-side look at scores, pricing and features — with RECATOOLS' ASEAN-aware verdict for each.
DeepEval
Pytest-style unit testing for LLM outputs, 50+ metrics, Apache 2.0
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Ragas
Widely adopted open-source framework for evaluating RAG pipelines with...
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| RECATOOLS Score | 8 / 10 | 7.5 / 10 |
| Capability | — | |
| Value for money | — | |
| Ease of use | — | |
| ASEAN readiness | — | |
| API quality | — | |
| Pricing | Open Source | Freemium |
| Free tier | — | Open-source library (Apache-2.0) is free; you pay only for evaluator model calls. |
| Paid from | — | Paid hosted platform (app.ragas.io) for dashboards and team features. |
| Has API | ✓ | ✓ |
| Open source | ✓ | ✓ |
| Free to use | ✓ | ✓ |
| Users | — | 15K+ GitHub stars |
| Founded | — | 2023 |
| Maker | — | Exploding Gradients |
| Verdict | DeepEval's whole pitch is that evaluating an LLM shouldn't require learning a new tool — if your team already writes pytest, you already know how to write a DeepEval test. That framing, plus Apache 2.0 licensing with no... |
What this is for: Measuring the quality of RAG pipelines with faithfulness, relevancy, and context metrics, plus synthetic test-set generation. Who this is for: Developers and ML teams who need to quantify and regressio... |
| Full review → | Full review → |
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Comparisons cover up to 4 tools. Scores are RECATOOLS editorial assessments; verify current pricing on each vendor's site.