Langfuse vs Opik

Side-by-side comparison of two AI agent tools

Short answer

  • Langfuse is growing faster: +1,812 GitHub stars in the last 30 days vs +607 for Opik.
  • Pick Langfuse for: open-source LLM engineering platform for observability, evaluation, prompt and dataset management. Pick Opik for: debug, evaluate, and monitor your LLM applications, RAG systems, and agentic workflows with comprehensive.

From GitHub data refreshed daily.

Langfuseopen-source

Open-source LLM engineering platform for observability, evaluation, prompt and dataset management

Opikopen-source

Debug, evaluate, and monitor your LLM applications, RAG systems, and agentic workflows with comprehensive tracing, automated evaluations, and production-ready dashboards.

Metrics

LangfuseOpik
Stars35.3k22.3k
Star velocity /mo1.8k606.8253968253969
Commits (90d)2.0k1.0k
Releases (6m)1010
Overall score0.90672926166320360.8528137883272678

Pros

  • +Open source with MIT license allowing full customization and transparency, plus active community support
  • +Comprehensive feature set combining observability, prompt management, evaluations, and datasets in one platform
  • +Extensive integrations with major LLM frameworks and tools including OpenTelemetry, LangChain, and OpenAI SDK
  • +提供端到端的 AI 应用可观测性,包括详细的链路追踪和性能监控,帮助开发者快速定位问题
  • +支持自动化评估和优化,能够自动改进提示词和工具配置,降低手动调优的工作量
  • +完全开源且拥有活跃社区支持,提供灵活的部署选项和定制化能力

Cons

  • -May require significant setup and configuration for self-hosted deployments
  • -Could be overwhelming for simple use cases that only need basic LLM monitoring
  • -Self-hosting requires technical expertise and infrastructure resources
  • -作为相对较新的工具,可能在某些企业级功能和集成方面还需要进一步完善
  • -学习曲线可能较陡,需要开发者具备一定的 AI 应用开发和监控经验

Use Cases

  • •Production LLM application monitoring to track performance, costs, and identify issues in real-time
  • •Prompt engineering and management for teams collaborating on optimizing model prompts and tracking versions
  • •LLM evaluation and testing to measure model performance across different datasets and use cases
  • •RAG 聊天机器人的性能监控和优化,追踪检索质量和回答准确性
  • •代码助手应用的链路分析,监控代码生成质量和响应时间
  • •复杂智能体工作流的调试和评估,跟踪多步骤推理过程的执行效果

FAQ

Which is more popular, Langfuse or Opik?
Langfuse has more GitHub stars (35,301 vs 22,334).
Which is more actively developed, Langfuse or Opik?
Langfuse had more commits in the last 90 days (2,007 vs 1,044).
Should I use Langfuse or Opik?
Compare their capabilities, limitations and "best for" notes above. Both are open source, so trying each on a small task is the fastest way to decide.