Langfuse vs Phoenix
Overview
Langfuse is an open-source LLM observability platform that provides tracing, analytics, prompt management, and evaluation for AI applications. It captures detailed traces of LLM calls, supports custom scoring, and integrates with LangChain, LlamaIndex, Vercel AI SDK, and raw API calls. Langfuse can be self-hosted for data privacy or used as a managed cloud service. Its open-source model and generous free tier make it popular with startups and developers.
Phoenix is an open-source LLM observability and evaluation platform from Arize AI. It supports OpenTelemetry-based tracing across LLM and agent applications, with built-in evaluators, dataset management, and prompt playgrounds. Phoenix can be self-hosted with Docker or run via the Arize-hosted cloud version.
Key features
Core capabilities each platform advertises.
- Open-source LLM observability
- Detailed trace and span tracking
- Prompt management
- Evaluation scoring
- Self-hosted and cloud options
- OpenTelemetry-based LLM and agent tracing
- Built-in evaluators for hallucination and relevance
- Dataset and experiment management
- Prompt playgrounds and versioning
- Self-hosted Docker deployment or Arize cloud
Strengths and tradeoffs
What each tool does well, and the limitations to keep in mind.
Pros
- Fully open-source with MIT license and free for commercial use with no usage limits
- Acquired by ClickHouse in January 2026, providing strong backing and future investment
- Active development with strong community support and comprehensive documentation
- Transparent pricing model based on units rather than complex metric calculations
- Deep integrations with major frameworks like LangChain, OpenAI, and LlamaIndex
Cons
- Recent acquisition by ClickHouse may lead to platform changes and strategic shifts
- Smaller team of 7 employees may impact support capacity
- Enterprise pricing at $3,450-$5,700/month can be expensive for mid-sized teams
Pros
- Open-source with active development by Arize
- OpenTelemetry-native (no proprietary trace format lock-in)
- Strong evaluator library out of the box
- Both self-hosted and managed cloud options available
- Upgrade path to full Arize enterprise platform
Cons
- Smaller community than Langfuse for open-source-first teams
- Cloud version's enterprise pricing is contact-sales only
- UI and feature set tilt toward ML engineers more than application developers
Langfuse or Phoenix — which should you choose?
Choose Langfuse if you wantChoose if you want
- Self-hosted LLM monitoring
- Open-source tracing for AI applications
- Prompt versioning and management
- Cost tracking across providers
- Community-driven observability
Choose Phoenix if you wantChoose if you want
- OpenTelemetry-native LLM observability
- Hallucination detection for RAG
- Experiment tracking and golden-set evaluation
- Prompt iteration and comparison
- Self-hosted tracing for compliance-sensitive teams
Compare Langfuse and Phoenix on your own traffic
Respan lets you trace LLM and agent calls across any model or framework, A/B test prompts on production traffic, and route requests across 500+ models through one gateway.