Promptfoo vs Braintrust vs LangSmith: Choosing an LLM Eval Tool
Use Promptfoo for prompt-level CI integration with simple eval needs (open-source, free, easy to integrate). Use Braintrust for production trace analysis and dataset curation at scale (paid, polished UX, strong dataset workflows). Use LangSmith for LangChain / LangGraph agent observability (paid, deep graph-aware tracing, native LangChain ecosystem integration). Most BearPlex engagements use multiple tools: Promptfoo in CI for prompt regression testing, Braintrust or LangSmith for production observability and dataset management. The right combination depends on your stack and team preferences.
Side-by-side comparison
| Dimension | Promptfoo | Braintrust |
|---|---|---|
| Pricing | Free (open source) | Free tier + paid |
| CI integration | Excellent | Good |
| Production trace analysis | Limited | Excellent |
| Dataset curation | Basic | Strong |
| UX polish | Engineering-focused | Polished, team-friendly |
| LangChain integration | Generic | Generic |
| Vendor lock-in | Low (open source) | Medium (data in their platform) |
| Maturity | Established (2023+) | Newer (2024+) |
| Best for | CI prompt regression, simple eval | Production-scale eval, dataset workflows |
Promptfoo
Open-source prompt-level eval and CI integration. Simple, fast, free.
Promptfoo is an open-source prompt evaluation framework focused on CI integration. Run prompt evaluations as part of your test suite; catch regressions before they ship; A/B test prompts and models. Excellent for prompt-level evaluation in development and CI. Less polished UX than paid alternatives for production trace analysis. Strong choice for teams wanting eval rigor without vendor lock-in or for early-stage AI products where simple eval is sufficient.
Pros
- Open source (MIT) and free
- Easy CI integration
- Multiple model providers supported (OpenAI, Anthropic, etc.)
- Configurable scoring (LLM-as-judge, deterministic, custom)
- Active development and community
Cons
- Less polished UX than paid alternatives
- Limited production trace analysis features
- Dataset management is basic
- Less suited for very-large-scale production observability
Best for
- → CI integration for prompt regression testing
- → Early-stage AI products where simple eval is sufficient
- → Teams wanting open-source eval without vendor lock-in
Worst for
- → Production trace analysis at scale
- → Sophisticated dataset curation and management
- → Teams that need deep observability beyond eval
Free (open source).
Hours from install to first eval running.
Braintrust
Polished production eval and dataset platform. Paid, strong UX.
Braintrust is a paid LLM evaluation platform with strong dataset curation, production trace analysis, and team collaboration features. Excellent UX for organizing eval datasets, viewing production traces, comparing model versions. Used at production scale by teams that have outgrown open-source eval tools. Strong choice for teams wanting professional-grade eval infrastructure.
Pros
- Polished UX for production eval
- Strong dataset curation and management
- Production trace analysis at scale
- Team collaboration features
- A/B testing and prompt versioning
- Provider-agnostic (works with any LLM)
Cons
- Paid (free tier limited)
- Vendor lock-in for the eval data and workflows
- Newer than Promptfoo / LangSmith: less established
- Less deep integration with specific frameworks (vs LangSmith with LangChain)
Best for
- → Production-scale LLM eval and dataset management
- → Teams that need polished UX for non-engineering team members
- → Sophisticated dataset curation workflows
Worst for
- → Early-stage projects without budget for paid tools
- → Teams committed to LangChain / LangGraph (LangSmith better)
Free tier limited; paid tiers from ~$50/month.
Days for production-ready eval setup.
Decision scenarios
Add prompt regression testing to CI for a Series B SaaS AI features
Promptfoo. Open-source, easy CI integration, free. Sufficient for prompt-level regression testing.
Production-scale LLM eval with multiple AI features and dataset curation needs
Braintrust. Polished UX for production trace analysis, dataset curation, team collaboration. Worth the paid investment at this scale.
Customer-facing AI product with LangChain / LangGraph throughout
LangSmith for graph-aware tracing of LangChain/LangGraph systems; Promptfoo or Braintrust for prompt-level eval. Common combination.
Early-stage AI startup without budget for paid tools
Promptfoo. Free open-source eval is sufficient for early-stage. Migrate to paid tools when production scale justifies investment.
Production AI with non-engineering team members curating datasets
Braintrust's polished UX makes dataset curation by non-engineers practical. Promptfoo is too engineering-focused for this use case.
Common questions
Yes: common pattern. Promptfoo in CI for prompt regression testing; Braintrust or LangSmith for production trace analysis. Different tools for different purposes; no need to consolidate to one.
For production AI features, yes. Eval tools are infrastructure; the alternative (no eval, ship and pray) is how AI features regress silently. We treat eval infrastructure as a first-class deliverable on every production engagement.
Inspect is Anthropic's open-source eval framework, particularly strong for safety-relevant evaluation and rigorous statistical methodology. Less production-scale focus than Braintrust / LangSmith but rigorous for high-stakes evals. We use Inspect for safety-critical eval work.
Usually no. Promptfoo, Braintrust, and LangSmith cover the patterns most production AI needs. Build custom only when your specific eval needs aren't covered by existing tools.
Eval infrastructure is part of standard production engagement scope. We set up Promptfoo in CI, Braintrust or LangSmith for production observability, golden datasets, and the eval rituals (regression review, dataset evolution) that keep eval useful over time.
Promptfoo: free. LangSmith: free 5K traces/month, $39/seat/month Plus. Braintrust: similar paid pricing. For production AI, eval tooling is a small fraction of total AI cost; not optimizing here.
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Get a recommendation tailored to your situation
BearPlex builds production AI systems using both approaches. We'll tell you which fits your case in a 30-minute scoping call.