AI Tool Comparison
Langflow vs Langfuse
A side-by-side breakdown to help you pick the right tool for your workflow.
Langflow
Wire up AI agents and RAG pipelines on a visual canvas, then export the finished flow as a working API or MCP server. Free and self-hosted since DataStax's cloud tier closed.
Langfuse
Trace and score LLM application runs so teams can debug agent behavior and track cost per user or session.
Bottom Line
Last reviewed: August 2026
Langflow and Langfuse both sit in Developer Tools, but they're built around different use cases within it. Langflow runs on a fully free plan while Langfuse runs on a freemium model, which alone may settle it if budget or a free tier is a hard requirement. Langfuse carries the higher rating (4.7 vs 4.5), but a gap that size rarely overrides a real workflow fit on its own.
Choose Langflow if…
Best for developers who want to build agent or RAG flows visually instead of writing orchestration code by hand, and its edge is finished flows export directly as a REST API or MCP server, ready to drop into another application. Genuinely free and open-source, self-hosting is now the only option since the hosted cloud tier shut down.
Choose Langfuse if…
Best for engineering teams who need production visibility into LLM application behavior that standard monitoring tools miss, and its edge is one of the strongest open-source LLM observability platforms, working with any provider rather than locking you in. A genuinely capable eval and monitoring layer, setup requires real SDK integration into your codebase.
| Attribute | Langflow | Langfuse |
|---|---|---|
| Category | Developer Tools | Developer Tools |
| Pricing | free | freemium |
| Pricing Detail | Free and MIT licensed, self-hosted only (DataStax's hosted cloud shut down April 2026) | Free (50K units) / $29/mo Core / $199/mo Pro |
| Rating |
Key Features
Langflow
- Drag-and-drop visual canvas
- Export flows as an API or MCP server
- Built-in RAG and vector store components
- Desktop app plus Docker/pip self-hosting
Langfuse
- Full LLM call tracing
- Prompt version management
- User session tracking
- Cost and latency analytics
- Evaluation datasets
- Self-hostable
Pros
Langflow
- •Fully free since the hosted cloud tier was discontinued
- •MIT licensed with an active, large contributor base
- •Exports directly to a usable API or MCP server
Langfuse
- •One of the best open-source options in LLM observability
- •Works with any LLM provider
- •Eval framework helps catch quality regressions early
Cons
Langflow
- No first-party managed hosting anymore, self-hosting is the only option
- Production usage still costs LLM API tokens and infrastructure
Langfuse
- Setup requires SDK integration in your codebase
- Dashboard can feel complex for simple use cases