Langfuse vs LangSmith (2026)
Open-source and framework-agnostic against LangChain-native. A head-to-head between two strong observability platforms — and where each one stops making sense.
Langfuse and LangSmith get compared constantly because they overlap on the surface — both do tracing, evals, and prompt management — but they're built on different bets. Langfuse bets on open source and framework independence. LangSmith bets on being the native observability layer for LangChain. Which bet fits you depends almost entirely on two things: whether you must self-host, and whether your stack is LangChain.
At a glance
| Langfuse | LangSmith | |
|---|---|---|
| Best for | Self-hosting / OSS shops, framework-agnostic stacks | Teams all-in on LangChain / LangGraph |
| License | Open source (MIT) | Closed source |
| Self-hosting | First-class (Helm, docker-compose) | Enterprise tier only |
| Tracing setup | OTel-native; works across frameworks | Zero-config for LangChain; manual otherwise |
| Framework coupling | None — provider SDKs, OTel, LangChain all supported | Strong gravity toward LangChain |
| Entry price | Free self-hosted; cloud from $29/mo | Free (5k traces/mo, 1 user), Plus $39/user/mo |
| Pricing model | Usage-based, self-host is free | Per-trace, per-user |
Where Langfuse wins
- Openness and control. MIT-licensed and self-hostable, with a SOC 2-compliant cloud tier if you don't want to run it. If data can't leave your infrastructure, LangSmith's self-hosting sits behind the Enterprise tier while Langfuse hands it to you on day one.
- Framework independence. OpenTelemetry-native tracing plus first-class integrations for provider SDKs and LangChain alike. Nothing pulls you toward a particular framework, which matters if your stack is provider-SDK-direct or mixed.
- Tracing depth. Debugging multi-step agent runs feels closer to a real APM than most competitors, with clean session grouping.
- Cost at scale. Self-hosted is free; the cloud tier is reasonable. Per-trace, per-user pricing tends to climb faster as you grow.
Where LangSmith wins
- LangChain integration. If your app is LangChain or LangGraph, one environment variable gets you a fully populated trace view — every chain, tool call, and decision step, no instrumentation code. Built by the framework team, and it shows. Langfuse supports LangChain well, but it can't match native.
- Time to first trace. For a LangChain shop, LangSmith is the fastest
pip install-to-populated-dashboard path in the category. - Prompt Hub. Store, version, and load prompts directly into LangChain code, tied to the primitives you're already using.
The honest read
Neither of these is a bad choice — they're the two most common defaults for good reason. The mistake is picking on brand rather than fit. If your entire stack lives in LangChain and you want zero-config tracing today, LangSmith's native integration is worth the framework coupling. If you're framework-agnostic, need to self-host, or care about open source, Langfuse is the more flexible foundation and ages better as your stack evolves.
How to choose
- Entire stack is LangChain / LangGraph? LangSmith.
- Need self-hosting, OSS, or framework independence? Langfuse.
- Mixed or provider-SDK-direct stack? Langfuse — the OTel-native approach won't fight you.
One caveat worth naming about both: their eval workflows are solid but trail the all-in-one specialists on CI-gated, dataset-driven release gates. If evals wired into your release process — not just tracing — are the real goal, weigh how far each will take you before you commit.