A side-by-side of two observability for building AI agents — live GitHub data, languages, and what each is best at.
Short answer: Langfuse leads Langfuse vs Helicone by community traction (★ 35k vs ★ 6.2k). Pick Langfuse for LLM tracing; pick Helicone for cost tracking.
✓ Live data verified
| Langfuse | Helicone | |
|---|---|---|
| GitHub stars | ★ 35k | ★ 6.2k |
| Language | TypeScript | TypeScript |
| Category | Observability | Observability |
| Best for | LLM tracing | cost tracking |
| Repository | langfuse/langfuse | Helicone/helicone |
Langfuse and Helicone are both credible choices. By community traction, Langfuse leads (★ 35k). Pick Langfuse for LLM tracing; pick Helicone for cost tracking.
Both are credible observability. By community traction Langfuse leads (★ 35k). Pick Langfuse for LLM tracing; pick Helicone for cost tracking.
Langfuse is Open-source LLM engineering platform — tracing, evals, prompt management, and metrics for agent apps.. Helicone is Open-source observability for LLM apps via a proxy — logging, caching, and cost tracking with one header..
Langfuse has more — ★ 35k vs ★ 6.2k (live counts).
Often yes — many teams combine observability. Check each tool's docs for interop; they solve overlapping but not identical problems.
Langfuse is primarily TypeScript; Helicone is primarily TypeScript.
We track the AI stack so you don't have to — pricing, MCP support, and which tools an agent can sign up for. Free.