LiteLLM
Call 100+ LLMs with the same OpenAI code you already have. LiteLLM handles the translation, tracks costs, runs fallbacks, and proxies for your whole team.
LiteLLM — the verdict: Developers who want to switch between GPT-4o, Claude, and Gemini without rewriting integration code LiteLLM's value is concrete: switching from GPT-4o to Claude to Gemini is a one-line config change rather than a rewrite of your integration code, because it translates every provider's API into a single OpenAI-compatible interface. Pricing: Open source / Free (Enterprise proxy available). Last reviewed: August 2026.
Best For
Developers who want to switch between GPT-4o, Claude, and Gemini without rewriting integration code
Standout Feature
A one-line config change swaps providers, with built-in cost tracking and fallback routing across 100+ models
Verdict
The simplest way to avoid vendor lock-in, self-hosting the proxy is real operational overhead for a small team.
Alternatives
Overview
LiteLLM translates calls to 100+ LLMs into a single OpenAI-compatible interface — switching from GPT-4o to Claude to Gemini is a one-line config change. Run it as a local library, a self-hosted proxy gateway for your whole team, or call the Python SDK directly. Built-in cost tracking, usage logs, rate-limit handling, fallback routing, and per-user budget controls make it practical for production-scale deployments.
Our Take
LiteLLM's value is concrete: switching from GPT-4o to Claude to Gemini is a one-line config change rather than a rewrite of your integration code, because it translates every provider's API into a single OpenAI-compatible interface. Built-in cost tracking and fallback routing across 100-plus models round out the core feature set. Run it as a local library or a self-hosted proxy gateway for your whole team. The proxy option is where the operational overhead lands: self-hosting adds real infrastructure responsibility for a small team. SSO and audit logs require the paid enterprise tier. For developers who want provider flexibility without rewriting their stack, this is the simplest path.
Key Features
- OpenAI-compatible interface for 100+ LLM providers
- Proxy server mode with centralized API key management
- Per-model and per-user cost tracking with budget limits
- Automatic fallback and load balancing across providers
- Streaming response support across all providers
- Integrations with Langfuse, Helicone, and other observability tools
- • Zero vendor lock-in — swap any provider with one config line
- • Largest provider coverage of any LLM abstraction layer
- • Fully open source with a large and active community
- • Self-hosting the proxy adds operational overhead for teams
- • SSO and audit log features require the paid enterprise tier
- • Occasional lag keeping up with very new model API releases
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