LiteLLM vs Helicone
Detailed side-by-side comparison to help you choose the right tool
LiteLLM
🔴DeveloperAI Gateway
LiteLLM is a self-hosted AI gateway that presents one OpenAI-compatible API across more than 100 model providers. The homepage separately claims access to over 1,800 models. Platform teams can issue virtual keys, organize users and teams, enforce budgets and rate limits, route requests, configure fallbacks and retries, log requests, export Prometheus metrics, and place models, agents, and MCP servers behind one access layer. Comparable options include [OpenRouter](/tools/openrouter), [Portkey AI
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Starting Price
FreeHelicone
🔴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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FreeFeature Comparison
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LiteLLM - Pros & Cons
Pros
- ✓Open-source edition has no license charge for production self-hosting
- ✓One interface reduces application coupling to individual providers
- ✓Centralizes model and MCP access, cost controls, and logs
- ✓Supports private and air-gapped deployments
Cons
- ✗The customer must operate a critical production gateway
- ✗Enterprise pricing is custom and requires an annual agreement
- ✗Upstream model usage and infrastructure remain separate costs
- ✗Provider-specific behavior can leak through the normalized API
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
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