Helicone vs Arize Phoenix
Detailed side-by-side comparison to help you choose the right tool
Helicone
🔴DeveloperLLM Observability
Open-source LLM observability, gateway, and cost analytics platform — proxy your OpenAI, Anthropic, or Bedrock calls through Helicone and get traces, caching, retries, rate limiting, and cost tracking in one line of code.
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FreeArize Phoenix
🔴DeveloperAI Observability
Arize Phoenix is an open-source AI observability and evaluation platform for tracing, testing, and improving LLM applications and agents.
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FreeFeature Comparison
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💡 Our Take
Choose Helicone for hosted SaaS observability with a free tier and proxy-based integration that works in 5 minutes. Choose Arize Phoenix if you want a fully open-source, OpenTelemetry-native tracing solution with strong RAG and embedding analysis features. Phoenix wins for ML practitioners doing deep retrieval debugging; Helicone wins for engineers needing cost dashboards out of the box.
Helicone - Pros & Cons
Pros
- ✓5-minute proxy integration captures full traces, cost, and latency across 20+ providers
- ✓Real AI gateway features (caching, retries, fallback, key vault) replace a custom proxy
- ✓MIT-licensed and self-hostable on Postgres + ClickHouse — passes regulated procurement
Cons
- ✗Proxy mode adds a network hop unless self-hosted in your own region
- ✗Prompt experiment UX is less mature than dedicated eval platforms like Braintrust
- ✗Self-hosting requires running ClickHouse, which is an extra ops surface
Arize Phoenix - Pros & Cons
Pros
- ✓Open-source Phoenix can run locally or on controlled infrastructure without a software license fee.
- ✓OpenTelemetry tracing reduces instrumentation lock-in.
- ✓Datasets, experiments, evaluations, and Prompt IDE connect evidence to changes.
- ✓AX Free and Pro include unlimited users and evaluations at published prices.
Cons
- ✗Self-hosting shifts upgrades, storage, access control, backups, and availability to the user's team.
- ✗Agent runs can generate many spans, consuming 25,000 or 50,000 allowances quickly.
- ✗Managed retention of 15 or 30 days may be short for audits or long incident cycles.
- ✗Fetched pages did not explicitly document native MCP support.
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