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 Helicone vs Langfuse by community traction (★ 33k vs ★ 6.0k). Pick Helicone for cost tracking; pick Langfuse for LLM tracing.
✓ Live data verified
| Helicone | Langfuse | |
|---|---|---|
| GitHub stars | ★ 6.0k | ★ 33k |
| Language | TypeScript | TypeScript |
| Category | Observability | Observability |
| Best for | cost tracking | LLM tracing |
| Repository | Helicone/helicone | langfuse/langfuse |
Helicone and Langfuse are both credible choices. By community traction, Langfuse leads (★ 33k). Pick Helicone for cost tracking; pick Langfuse for LLM tracing.
Both are credible observability. By community traction Langfuse leads (★ 33k). Pick Helicone for cost tracking; pick Langfuse for LLM tracing.
Helicone is Open-source observability for LLM apps via a proxy — logging, caching, and cost tracking with one header.. Langfuse is Open-source LLM engineering platform — tracing, evals, prompt management, and metrics for agent apps..
Langfuse has more — ★ 33k vs ★ 6.0k (live counts).
Often yes — many teams combine observability. Check each tool's docs for interop; they solve overlapping but not identical problems.
Helicone is primarily TypeScript; Langfuse 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.