Braintrust vs LangSmith
Detailed side-by-side comparison to help you choose the right tool
Braintrust
🔴DeveloperAI evaluation
AI evals, prompt iteration and observability platform
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Starting Price
FreeLangSmith
🔴DeveloperAI Observability
LangSmith is LangChain’s LLM observability and evaluation platform for tracing, testing, monitoring, and improving AI agents.
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FreeFeature Comparison
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💡 Our Take
Choose Braintrust if you're model-agnostic and want to compare OpenAI, Anthropic, Google, and 20+ providers in one dashboard, plus access the Loop agent for automated prompt generation. Choose LangSmith if your stack is built on LangChain — the integration is tighter and tracing is more idiomatic within that ecosystem. Braintrust wins on optimization automation and provider flexibility; LangSmith wins on LangChain-native workflows.
Braintrust - Pros & Cons
Pros
- ✓Strong fit for production AI teams because traces, datasets and experiments live in one workflow
- ✓Starter is $0/month with 1 GB processed data, 10k scores and 14-day retention
- ✓Pro is $249/month with 5 GB processed data, 50k scores, 30-day retention and priority support
- ✓Framework agnostic with Python, TypeScript, Go, Ruby and C# SDKs
Cons
- ✗The value shows up after you have real traffic or evaluation datasets; it may be overkill for prototypes
- ✗Data and score overages require attention on high-volume products
- ✗Enterprise deployment choices need procurement and security review
LangSmith - Pros & Cons
Pros
- ✓Very strong fit for teams already building with LangChain or LangGraph because tracing, evals, prompts, and deployments sit in the same ecosystem.
- ✓The free Developer plan is useful for early projects because it includes up to 5k base traces per month rather than only a demo sandbox.
- ✓Supports both debugging workflows and production monitoring, so teams can use one system from prototype through release.
- ✓Enterprise deployment options include hybrid/self-hosted patterns for teams that cannot send sensitive traces to a hosted SaaS environment.
- ✓SDK coverage across Python, TypeScript, Go, and Java makes it workable outside a single framework choice.
Cons
- ✗The best experience is developer-oriented; product managers and analysts will usually need engineering help to instrument traces and evaluations well.
- ✗Costs can become usage-modeling work because seats, traces, Fleet runs, sandboxes, and model-provider charges are separate considerations.
- ✗It is naturally biased toward the LangChain ecosystem, which may be a drawback if your stack is built around a different observability standard.
- ✗The official /langsmith/pricing URL returned a 404 during this run, so pricing was verified from the alternate LangChain pricing page and should be rechecked before purchase.
- ✗Self-hosting, custom SSO/RBAC, and formal support SLA are Enterprise items rather than default features on the $39 Plus plan.
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