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Comparison

Logfire vs Langfuse

Both monitor LLM applications, but differ on scope and architecture. Langfuse is LLM-specific while Logfire gives you complete visibility across your entire stack—AI and infrastructure in one place. When your AI agent fails, see both the LLM trace AND the database error that caused it.

Feature comparison

Quick comparison

Logfire and Langfuse compared feature by feature
Feature Logfire Langfuse
Observability scope Full-stack: AI, databases, APIs, and infrastructure in one trace LLM-specific observability
LLM Tracing Yes Yes
Token/Cost Tracking Yes Yes
Prompt Playground Yes Yes
Human annotations & queues Annotations on production runs + annotation queues Annotations on production runs + annotation queues
Full-Stack Observability Yes No
Database/API Tracing Yes No
Query Interface SQL (PostgreSQL) Custom UI / API
MCP server SQL queries over production telemetry from your editor or AI agent Query observations, metrics, scores, datasets, and annotation queues
OpenTelemetry Native; fully portable instrumentation Export only
Self-Hosting Enterprise Open Source
Free Tier 10M logs, spans, and metrics Limited (each trace, span, eval score counts separately)
Python SDK First-class (Pydantic team) Good
JavaScript SDK Full SDK Good
Any OTel Language Yes No
Cost savings

Pricing comparison

Monthly list price for equivalent workloads in Langfuse and Logfire
Workload Langfuse Logfire Savings
1 user, 5M spans/mo ~$451 $0 (free tier) 100%
5 users, 50M spans/mo ~$3,451 ~$129 ~27x
20 users, 500M spans/mo ~$36,801 ~$1,229 ~30x

Logfire Team or Growth plans (base + $2/million spans). Langfuse Core Plan ($29/mo base + $8/100k units); units count every trace, observation, and evaluation score separately.

Key differences

Why teams choose Logfire

Full-stack, not AI-only

Your AI doesn't run in isolation. When an agent fails, is it the LLM, the database, or the API it called? Logfire shows you everything in one trace. Langfuse only sees the LLM part.

OpenTelemetry native

Logfire is built on OpenTelemetry, the industry standard. Any framework with OTel instrumentation works automatically, with no special integration needed. Vercel AI SDK, LangChain, FastAPI all just work. No vendor lock-in.

SQL query interface

Query your observability data with standard PostgreSQL SQL. Use familiar tools, no proprietary query language to learn. AI assistants write excellent SQL, making complex analysis easy.

Decision guide

Which should you choose?

Choose Logfire if

  • You want AI monitoring AND application monitoring in one tool
  • You have services in multiple languages that need unified tracing
  • You prefer SQL-based querying (AI assistants write excellent SQL)
  • You're building with Pydantic/FastAPI
  • You want exceptional Python integrations

Choose Langfuse if

  • You only need LLM-specific monitoring
  • You need open-source self-hosting (Logfire self-hosting is enterprise)
  • You want built-in dataset management and eval workflows
FAQ

Common questions

What is the main difference between Logfire and Langfuse?

Logfire provides full-stack observability covering your entire application (AI, databases, APIs), while Langfuse focuses specifically on LLM tracing. When your AI agent fails, Logfire shows you both the LLM trace AND the database error or API timeout that caused it.

Is Logfire more expensive than Langfuse?

Logfire offers a free tier of 10M logs, spans, and metrics a month, then $2 per million records. Langfuse uses per-event pricing plus usage-based costs. The best choice depends on your specific usage patterns and whether you need full-stack observability or LLM-only monitoring.

Can I use Logfire with LangChain?

Yes. Logfire provides auto-instrumentation for LangChain, LlamaIndex, OpenAI, Anthropic, and many other AI frameworks. You can visualize complex chains and retrieval flows automatically.

Can I migrate from Langfuse to Logfire?

Yes. Both platforms are OpenTelemetry-compatible, so instrumentation concepts transfer easily. Logfire's Pydantic AI integration is a drop-in replacement. You can run both during a transition period.

Does Logfire support open-source self-hosting?

Logfire's SDK is open source. The platform is available as cloud-hosted or self-hosted (enterprise). If open-source self-hosting is a hard requirement, Langfuse may be a better fit.

Ready to switch from Langfuse?

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