Langfuse vs Braintrust
Detailed side-by-side comparison to help you choose the right tool
Langfuse
🔴DeveloperOpen-source LLM observability
open-source LLM observability, tracing, prompt and eval platform
Was this helpful?
Starting Price
FreeBraintrust
🔴DeveloperAI evaluation
AI evals, prompt iteration and observability platform
Was this helpful?
Starting Price
FreeFeature Comparison
Scroll horizontally to compare details.
💡 Our Take
Choose Braintrust if you need automated prompt optimization through the Loop agent and have budget for $25/seat/month — the automation pays for itself within 2-3 months for active teams. Choose Langfuse if you're budget-conscious, want full data sovereignty through self-hosting, or only need observability without automated improvement. Langfuse is the better pick for solo developers and open-source-first teams; Braintrust wins for production teams iterating on prompts weekly.
Langfuse - Pros & Cons
Pros
- ✓Open-source and self-hostable, which is valuable for teams that do not want observability locked fully in a SaaS.
- ✓Clear fit for prompt lifecycle management: versioning, fetching, traces, datasets, and evals in one workflow.
- ✓MCP support is useful for coding agents that need to inspect or update observability assets safely.
- ✓Cloud pricing starts low enough for serious prototypes while still offering enterprise controls.
Cons
- ✗Unit-based pricing requires teams to understand how traces and observations translate into monthly spend.
- ✗Self-hosting reduces vendor lock-in but adds ClickHouse/database operations and upgrade responsibility.
- ✗Not a full application monitoring suite; you still need product analytics and infrastructure observability.
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
Not sure which to pick?
🎯 Take our quiz →🔒 Security & Compliance Comparison
Scroll horizontally to compare details.
Price Drop Alerts
Get notified when AI tools lower their prices
Get weekly AI agent tool insights
Comparisons, new tool launches, and expert recommendations delivered to your inbox.