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 Phoenix vs Helicone by community traction (★ 11k vs ★ 6.1k). Pick Phoenix for OTel tracing; pick Helicone for cost tracking.
✓ Live data verified
| Phoenix | Helicone | |
|---|---|---|
| GitHub stars | ★ 11k | ★ 6.1k |
| Language | Jupyter Notebook | TypeScript |
| Category | Observability | Observability |
| Best for | OTel tracing | cost tracking |
| Repository | Arize-ai/phoenix | Helicone/helicone |
Phoenix and Helicone are both credible choices. By community traction, Phoenix leads (★ 11k). Pick Phoenix for OTel tracing; pick Helicone for cost tracking.
Both are credible observability. By community traction Phoenix leads (★ 11k). Pick Phoenix for OTel tracing; pick Helicone for cost tracking.
Phoenix is Arize's open-source observability for LLM apps — OpenTelemetry-based tracing and evaluation.. Helicone is Open-source observability for LLM apps via a proxy — logging, caching, and cost tracking with one header..
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.
Phoenix is primarily Jupyter Notebook; 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.