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litellm vs OmniRoute

Open-source AI gateway: call 100+ LLM providers in OpenAI format via a Python SDK or self-hosted proxy — with cost tracking, virtual keys, guardrails, load balancing and logging. — versus — Free MIT AI gateway for coding CLIs: one endpoint over 352 providers (150+ free tiers) and 1,200+ models with quota-aware auto-fallback, RTK+Caveman token compression, MCP/A2A and a desktop app.

The curated verdict

LiteLLM is the general-purpose OpenAI-format gateway for applications; OmniRoute is built for coding CLIs and free tiers specifically — quota tracking and fallback are the product, not a feature.

litellmOmniRoute
Stars58k62k
Forks11k8.6k
LanguagePythonTypeScript
LicenseNOASSERTIONMIT
Last activity2 days agotoday
Topicsgatewaygateway, coding
Curated connections206

litellm — the curator's take

The default answer to "one API for every LLM." Reach for it when app code or an agent fleet must hit many providers without per-SDK glue, or when a team needs a central proxy with spend caps, virtual keys and logging. The SDK is a thin drop-in; the proxy is the real value (dashboard, budgets, rate limits). NOT an inference engine — it routes to backends like vLLM/Ollama, doesn't run models. Overkill if you only ever call one provider. Guardrails/evals exist but are lighter than dedicated tools.

OmniRoute — the curator's take

The maximalist gateway for people who refuse to pay per token: it catalogues 444 free-tier entries, computes an honest monthly budget (~1.47B tokens, re-audited fortnightly, regional-ID quotas shown separately), and schedules Claude Code, Codex, Cursor, OpenCode, Cline or Copilot traffic across them with quota-aware fallback so a limit never stops you. 61k stars and 550 contributors are real. NOT for a production application: 352 providers means 352 terms of service and 352 latency profiles, and the value is breadth, not guarantees. For a small, predictable stack use a purpose-built gateway; use OmniRoute to keep coding when your subscription runs dry.