A side-by-side of two observability for building AI agents — live GitHub data, languages, and what each is best at.
Short answer: Phoenix leads Helicone vs Phoenix by community traction (★ 11k vs ★ 6.1k). Pick Helicone for cost tracking; pick Phoenix for OTel tracing.
✓ Live data verified
| Helicone | Phoenix | |
|---|---|---|
| GitHub stars | ★ 6.1k | ★ 11k |
| Language | TypeScript | Jupyter Notebook |
| Category | Observability | Observability |
| Best for | cost tracking | OTel tracing |
| Repository | Helicone/helicone | Arize-ai/phoenix |
Helicone and Phoenix are both credible choices. By community traction, Phoenix leads (★ 11k). Pick Helicone for cost tracking; pick Phoenix for OTel tracing.
Both are credible observability. By community traction Phoenix leads (★ 11k). Pick Helicone for cost tracking; pick Phoenix for OTel tracing.
Helicone is Open-source observability for LLM apps via a proxy — logging, caching, and cost tracking with one header.. Phoenix is Arize's open-source observability for LLM apps — OpenTelemetry-based tracing and evaluation..
Phoenix has more — ★ 11k vs ★ 6.1k (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; Phoenix is primarily Jupyter Notebook.
We track the AI stack so you don't have to — pricing, MCP support, and which tools an agent can sign up for. Free.