LangSmith vs Ragas

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

	LangSmith Eval, tracing, and prompt management from the LangChain team.	Ragas Open-source Python framework for evaluating RAG pipelines with model-based, largely reference-free metrics.
Category	eval	eval
Vendor type	commercial	open source
Pricing	freemium	free
Strengths	+ End-to-end coverage (trace, eval, prompt) + Native LangChain/LangGraph integration	+ Reference-free metrics reduce the need for human-labeled ground truth + Research-grounded RAG metrics: faithfulness, relevancy, context precision/recall + Synthetic test set generation for bootstrapping evaluation datasets + Integrations with LangChain, LlamaIndex, and tracing platforms
Tradeoffs	− Most natural for LangChain-stack teams	− LLM-judged scores can be inconsistent across runs and judge models, and add token cost − Scoped primarily to RAG; weaker coverage for agentic or general LLM app evaluation − Absolute metric values are hard to interpret without a baseline
Used in stacks	2	0