LangSmith vs Sentry
Both are observability & tracing tools. Here is how they actually differ on price, billing model and deployment.
LangSmith
LangChain's proprietary observability and eval platform. Turnkey and deeply integrated with LangChain and LangGraph - but closed-source, and the trace bill explodes at production scale.
Sentry
Excellent error tracking that keeps appearing in LLM observability roundups where it does not belong. Its AI product, Seer, is a code-debugging agent billed per contributor - not an LLM tracing or evaluation platform.
| LangSmith | Sentry | |
|---|---|---|
| Category | Observability & Tracing | Observability & Tracing |
| Our rating | 3/5 | 2/5 |
| Starting price | $39/seat/mo | $26/mo |
| Billing meter | seat | event |
| Free plan | Yes | Yes |
| Free self-hosting | No or paid tier only | No or paid tier only |
| Best for | Teams already all-in on LangChain and LangGraph who want the tightest-integrated observability and don't mind the bill | Error tracking and front-end debugging, which it does superbly. It is not the right tool for observing or evaluating LLM applications, and should be paired with one rather than substituted for one. |
Our verdict on LangSmith
The most turnkey observability platform if you already live in LangChain and LangGraph - the tracing is zero-config and the eval tooling is genuinely good. But it's closed source, self-hosting is Enterprise-only, and the trace bill is roughly 25x Langfuse at scale. It's great until you scale or want out, and you can't self-host your way around either problem.
Full LangSmith review →Our verdict on Sentry
We are including Sentry because it keeps appearing in LLM observability comparisons, and the most useful thing we can tell you is that it does not belong in them. Sentry is an outstanding error tracking and performance monitoring product. What it is not is an LLM observability platform. It does not do prompt and completion capture, token accounting, per-model cost attribution or output-quality evaluation in the way this category means those terms. The confusion comes from Seer, Sentry's AI product, which roundups see and file as AI observability. Seer is a code debugging agent - it looks at your errors and proposes fixes - billed at $40 per active contributor per month, where an active contributor is anyone opening two or more pull requests to a Seer-enabled repository in a billing cycle. That is a developer productivity tool, not agent observability. Run Sentry for your application errors, absolutely. Run something else for your LLM calls.
Full Sentry review →Frequently Asked Questions
What is the main difference between LangSmith and Sentry?
LangSmith: Teams already all-in on LangChain and LangGraph who want the tightest-integrated observability and don't mind the bill Sentry: Error tracking and front-end debugging, which it does superbly. It is not the right tool for observing or evaluating LLM applications, and should be paired with one rather than substituted for one. Both sit in Observability & Tracing, so the decision usually comes down to billing model and deployment rather than raw capability.
Which is cheaper, LangSmith or Sentry?
It depends entirely on your workload shape, because they meter differently - LangSmith bills on seat and Sentry bills on event. Published starting prices are $39/seat/mo and $26/mo respectively, but those numbers are not comparable until you apply them to the same traffic. Use our cost calculator to model both against your own request volume and span count.
Can I self-host LangSmith or Sentry?
LangSmith: No or paid tier only. Sentry: No or paid tier only. Free self-hosting means no licence fee, not no cost - you still own the infrastructure, upgrades and on-call.