Key features
Core capabilities each platform advertises.
Data not available
- RAG-specific evaluation framework
- Component-wise metrics for RAG
- Synthetic test data generation
- LLM-as-judge evaluators
- Open-source Python library
Updated March 10, 2026
DeepEval is an open-source LLM evaluation framework built for unit testing AI outputs. It provides 14+ evaluation metrics including hallucination detection, answer relevancy, and contextual recall. Integrates with pytest, supports custom metrics, and works with any LLM provider for automated quality assurance in CI/CD pipelines.
Ragas is an open-source evaluation framework specifically designed for RAG (Retrieval-Augmented Generation) pipelines. It provides metrics for context precision, context recall, faithfulness, and answer relevancy, helping teams measure and improve the quality of their RAG systems. Ragas has become the standard evaluation toolkit for teams building production RAG applications.
Core capabilities each platform advertises.
What each tool does well, and the limitations to keep in mind.
Pros
Cons
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Choose DeepEval if you wantChoose if you want
Choose Ragas if you wantChoose if you want
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