Braintrust vs LangSmith
Two hosted eval platform options for LLM observability & evals. When each fits, what it costs, who moves from one to the other, and what makers who chose it say.
Which fits you
Choose Braintrust if- Your main question is whether a prompt or model change made outputs better or worse
Use it whenYour main question is "did this change make outputs better or worse".
Trade-offClosed source, and the paid tier is priced for teams rather than hobby projects.
Choose LangSmith if- Your app is built on LangChain or LangGraph
Use it whenYou already use the LangChain stack.
Trade-offPaid per seat beyond the free tier; self-hosting is enterprise-only.
At a glance
| Braintrust | LangSmith | |
|---|---|---|
| Used by | 5 makers' products · 10 open-source projects | 11 makers' products · 49 open-source projects |
| Cost at default usagetraces 100k traces | — | $475/mo Developer |
| Downloads | 1.4M/wk+117% vs npm | 6.1M/wk−4% vs npm |
| Pricing | Free tier with monthly usage credits; paid tier with usage overage; custom Enterprise, including self-hosted. · paid from $249/mo | Free tier with a monthly trace limit; paid per-seat plan with usage overage; custom Enterprise, including self-hosted. · paid from $39/seat/mo |
| Free tier | Yes | Yes |
| Open source | No | No |
| Incidents, 90 daysfrom its status page | 9 (8 major) | 0 |
What makers say
Makers on using it for LLM observability & evals, from Product Hunt and Starter Story interviews, each linked to the source. Products with a page of their own and fuller notes first.
On BraintrustNo maker quote about Braintrust for LLM observability & evals yet.
On LangSmithLangSmith’s real-time analytics and versioning keep our AI agents rock-solid -- so everything just works better.
You can't build AI agents without monitoring. Metadata filtering is strong.
I deployed the manage Pig agent on LangGraph and it's been smooth sailing!
Loved and watch-outs
Themes that recur in makers' words and Hacker News comments, each linked to what it summarises.
BraintrustLangSmith- It keeps pulling users toward the LangChain platform, and LangChain docs push LangSmith, which feels like lock-in. HNHN 2HN 3HN 4
- Traces show which agent failed but not why, so root-cause analysis stays manual. HNHN 2HN 3HN 4
- Viewing your own traces requires a cloud account, with no local-first option. HNHN 2
Who uses each
Braintrust5 makers' productsLangSmith11 makers' products
lmChatGPTtfy
Watchman AI
Meet-TingWhat makers pair each with
With Braintrust
BrewHey Noah
inbox-zero
Arcade
Blacksmith
Directuseveholmesgpt
Linear
Mastraonyx-foss
PostHogand 2 moreinbox-zeroDirectuseveMastraonyx-fossPostHogArcadeBlacksmithMastraPostHogBrewHey Noahinbox-zeroBlacksmithMastraBlacksmithLinearPostHog
Supabaseinbox-zeroDirectusPostHogWith LangSmith
Astrid
Pig
Traycer AIAstrid
NeuralAgentTraycer AINeuralAgentTraycer AI
GitLawTraycer AIGitLaw
IntrycTraycer AINeither quite right?
See the whole LLM observability & evals decision →
LangfuseOpen-source platformTracing, prompt management and evals in one tool you can run on your own server for free.vs Braintrust →vs LangSmith →
Arize PhoenixOpen-source platformOpenTelemetry-based tracing and evals you can start locally in a notebook, then self-host or move to its cloud.vs LangSmith →
HeliconeProxy loggingGetting request logs, costs and latency by changing one base URL, with no SDK instrumentation.vs Braintrust →vs LangSmith →