Langfuse vs 
Phoenix
Langfuse vs Phoenix compared for 2026 — features, license, ease of use, performance and which one to choose. See what your LLM app actually did vs Trace, evaluate and debug LLM apps.
Updated regularly · curated by OpenSourceAI.tech
Langfuse vs Phoenix at a glance
| Spec | Langfuse | Phoenix |
|---|---|---|
| Category | LLM / RAG framework | LLM / RAG framework |
| Type | LLM observability | LLM observability |
| License | MIT | Elastic-2.0 |
| Runs locally | Yes | Yes |
| Primary language | TypeScript | Python |
| Ease of use | Intermediate | Intermediate |
| Best for | debugging and monitoring LLM apps in production | finding why a RAG pipeline fails |
| GitHub stars | 31.3k | 10.6k |
How Langfuse and Phoenix score
| Criterion | Langfuse | Phoenix |
|---|---|---|
| Popularity | 4.0 | 3.0 |
| Maintenance | 5.0 | 5.0 |
| Ease of use | 3.5 | 3.5 |
| Privacy | 5.0 | 5.0 |
| License freedom | 5.0 | 3.5 |
Scores are computed automatically from public signals — GitHub stars (popularity), recent commit activity (maintenance), license type (freedom), local-first design (privacy) and onboarding complexity (ease of use). Indicative, not a verdict.
What each one is
Langfuse
Langfuse traces every LLM call, tool use and cost in your application, with prompt management and evaluation built in — self-hostable.
- Full tracing of chains and agents
- Cost and latency tracking
- Self-hosted, MIT licensed
Phoenix
Phoenix from Arize traces LLM applications, surfaces failure clusters and runs evaluations, all runnable locally in a notebook or as a server.
- Runs locally, even in a notebook
- Clusters failures to find patterns
- Built-in LLM evaluators
Key differences
Langfuse is lLM observability, while Phoenix is lLM observability. Their licenses differ (MIT vs Elastic-2.0), which matters if you ship a commercial product. In short, Langfuse fits debugging and monitoring LLM apps in production, and Phoenix fits finding why a RAG pipeline fails.
Which should you choose?
Choose Langfuse for debugging and monitoring LLM apps in production. Choose Phoenix for finding why a RAG pipeline fails.
There is rarely one winner — many setups use both. The right pick depends on your hardware, your team's skills, and whether you value simplicity or control.
Frequently asked questions
Is Langfuse or Phoenix easier to use?
Both sit at a similar level (Intermediate). Your choice should come down to fit rather than difficulty.
Are Langfuse and Phoenix free?
Langfuse is free and open source (MIT), and Phoenix is free and open source (Elastic-2.0). Neither charges for the core software.
Can I run Langfuse and Phoenix locally?
Langfuse: yes · Phoenix: yes. Both can be used without sending your data to a third-party cloud where their setup allows.
Langfuse vs Phoenix — which should I pick in 2026?
Choose Langfuse for debugging and monitoring LLM apps in production. Choose Phoenix for finding why a RAG pipeline fails.
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