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LiteLLM

Free plan

A self-hosted open-source LLM gateway

An open-source Python SDK and self-hostable AI gateway (proxy) that calls 100+ LLM providers in OpenAI-compatible format. It handles cost tracking, load balancing, fallbacks, guardrails, and virtual key provisioning all in one place.

Open sourceAPI availableCommercial use OK
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Edge

vs. similar tools: Its strength is the MIT-licensed core you can self-host, running virtual keys, budgets, and cost tracking without ever sending data outside your environment.

Pricing

PlanMonthly priceLimits
Open Source$0/moMIT 라이선스 코어, 셀프 호스팅 시 무료
Enterprise--

AI Score

Computed by AI from public info and internal criteria (not a measured benchmark)

88

Overall score

Category average +4
Model coverageKorean supportValue for moneyEase of useEcosystem / Integration

Not a measured benchmark — this is a score computed by AI based on information published on the web and internal evaluation criteria.

Popularity

Buzz and recognition within the same category (not a quality score)

44

Relative score within category

  • Domain authority4.2 / 10
  • Hacker News buzz2,635 pts
  • GitHub stars★ 48,838

A buzz metric computed by normalizing public signals — GitHub stars, Hacker News mentions, domain authority, and more — per category. Popularity is a different axis from quality and can disadvantage new or niche tools, so we use it only as a supplementary indicator. Collected: 2026-05-31.

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By AI score

  • 91
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  • 90
    OpenRouter

    Its strength is passing through provider pricing as-is while offering automatic fallback and model routing from a single key.

  • 89
    LangGraph

    Its advantage is graph-based state persistence that enables pause-and-resume, rollback, and audit trails, making it strong for production agents.

  • 87
    Ollama

    Its strength is pulling open models with a single command and running them as a local API server, enabling offline inference with no data leaving your machine.

  • 86
    Pinecone

    Its strength is a serverless model where you pay only for storage and read/write usage with no capacity to reserve, making it well suited to variable workloads.

Compare LiteLLM

LiteLLM vs ComposioLiteLLM vs Hugging FaceLiteLLM vs LangfuseLiteLLM vs LangGraphLiteLLM vs Ollama

Last updated: 2026-05-30

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