Both products connect traces, evaluation, and prompts. Choose by the experiment workflow and deployment model your team can sustain, then test them with the same difficult cases.
Teams shortlisting Langfuse and LangSmith
Langfuse
Start here when an open-source AI engineering platform and its self-hosting model are central to the decision.
LangSmith
Start here when its tracing and evaluation workflow fits your development process and existing ecosystem.
Also consider Lunary
Include Lunary if customer conversation review and shared prompt investigation are important shortlist criteria.
At a glance
| Question | Langfuse | LangSmith |
|---|---|---|
| Evaluation workflow | Datasets, scores, and experiments | Datasets, evaluators, and experiments |
| Prompt work | Versioned prompts and retrieval | Prompt engineering and testing |
| Deployment decision | Open-source self-hosting plus edition choices | Hosted and commercial self-hosting options |
| Archive options | Filtered UI and blob-storage exports | SDK queries and eligible bulk exports |
Evaluate a change with known regressions
Build a small test set containing common successes, previous failures, and important edge cases. Run the baseline and candidate in each product's evaluation workflow. Ask reviewers to identify which cases improved, which regressed, and whether an aggregate score conceals an unacceptable failure. This reveals more than checking whether both products offer evaluations.
Test your stack, not a brand association
LangSmith documents framework-independent tracing; it is not limited to LangChain applications. Langfuse supports application tracing and a broad instrumentation ecosystem. Run the same nested workflow in both. Check propagation across asynchronous operations, error handling, streaming, and the attributes needed to relate a trace to the correct user session and release.
Self-hosting is an operational decision
Langfuse documents an open-source self-hosting path. LangSmith also documents self-hosting, with its own commercial requirements and deployment options. Compare the actual edition and architecture, not a yes-or-no cell. Include an upgrade and restore exercise in a serious infrastructure evaluation.
Test the data exit before committing
Langfuse documents UI and blob-storage exports. LangSmith offers SDK queries and bulk export, with plan and signup-date eligibility affecting the latter. Export the same bounded time range and inspect whether you have child operations, scores, and usable payloads. Archive completeness is separate from recreating native experiments in another platform.
Put an unfamiliar reviewer in front of the result
After the first engineer configures the trial, ask a different teammate to review an experiment without a walkthrough. They should identify the baseline, candidate, evaluation criteria, and one important regression. Then ask them to locate the execution evidence behind that regression. Observe which parts are self-explanatory and which depend on tribal knowledge. This test separates a workflow that one enthusiastic implementer can demonstrate from a process the wider team can use repeatedly.
Common questions
Is this a neutral third-party review?
No. Lunary publishes this documentation-based comparison. The selection advice is editorial, and no comparative performance benchmark is claimed.
Which is better for LangChain?
Test your precise integration and workflow. A shared ecosystem can help, but instrumentation completeness, evaluation usability, and operational fit should decide the purchase.
Sources & methodology
Lunary publishes this guide. We compare documented workflows and explain where each approach fits; this is not an independent benchmark or a hands-on product rating. Features, limits, and commercial terms can change. Check the linked vendor documentation before deciding.