--- title: 'Logfire vs Langfuse: Full-Stack AI Observability Comparison' description: Compare Logfire and Langfuse for AI observability. See features, pricing, and why teams choose Logfire for complete application visibility. canonical: https://pydantic.dev/logfire/vs-langfuse last-reviewed: 2026-07-13 --- > Markdown version of [Logfire vs Langfuse](https://pydantic.dev/logfire/vs-langfuse) — the canonical HTML page. > > Site index: [/llms.txt](https://pydantic.dev/llms.txt) --- # 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. [Try Logfire free](https://logfire.pydantic.dev/) ## Quick comparison | Feature | Logfire | Langfuse | | ------------------------ | ---------------------------------------------------------------- | -------------------------------------------------------- | | Observability scope | Full-stack: AI, databases, APIs, and infrastructure in one trace | LLM-specific observability | | LLM Tracing | ✓ | ✓ | | Token/Cost Tracking | ✓ | ✓ | | Prompt Playground | ✓ | ✓ | | Full-Stack Observability | ✓ | ✗ | | Database/API Tracing | ✓ | ✗ | | Query Interface | SQL (PostgreSQL) | Custom UI / API | | MCP server | Query production traces and spans from your editor or AI agent | Prompt management only | | OpenTelemetry | Native; fully portable instrumentation | Export only | | Self-Hosting | Enterprise | Open Source | | Free Tier | 10M spans | Limited (each trace, span, eval score counts separately) | | Python SDK | First-class (Pydantic team) | Good | | JavaScript SDK | Full SDK | Good | | Any OTel Language | ✓ | ✗ | ## Pricing comparison | 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. ## Why teams choose Logfire ### Full-Stack vs 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—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. ## 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 **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 with 10M spans/month and then charges $2/million spans. 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? Get started with 10 million free spans per month. No credit card required. Start free: https://logfire.pydantic.dev/ — [View pricing](https://pydantic.dev/pricing) --- See also: [Logfire alternatives](https://pydantic.dev/logfire/alternatives) ([markdown](https://pydantic.dev/logfire/alternatives.md)), [Pydantic Logfire](https://pydantic.dev/logfire) ([markdown](https://pydantic.dev/logfire.md)), and [pricing](https://pydantic.dev/pricing.md).