DeepEval vs LangSmith

Pick two tools from the same category to compare side-by-side.

	DeepEval Open-source LLM evaluation framework with pytest-style testing and 50+ research-backed metrics, maintained by Confident AI.	LangSmith Eval, tracing, and prompt management from the LangChain team.
Category	eval	eval
Vendor type	hybrid	commercial
Pricing	freemium	freemium
Strengths	+ 50+ research-backed metrics covering RAG, agents, and safety dimensions + Pytest-style API designed for unit testing LLM apps in CI/CD + Local-first execution; cloud platform is optional + Includes synthetic test data generation and red-teaming capabilities	+ End-to-end coverage (trace, eval, prompt) + Native LangChain/LangGraph integration
Tradeoffs	− LLM-as-judge metrics consume judge-model tokens and can vary between runs − Documentation and feature set steer users toward the commercial Confident AI platform	− Most natural for LangChain-stack teams
Used in stacks	0	2