a3m-router vs freellmapi

Self-hosted LLM request routers compared

a3m-router and freellmapi are self-hosted TypeScript gateways that route LLM requests through a shared API. a3m-router emphasizes routing strategies, ensembles, and provider failover, while freellmapi focuses on combining free provider tiers and custom endpoints with quota and key management.

a3m-routerfreellmapi
LanguageTypeScriptTypeScript
LicenseMITMIT
Stars1730.3k
Forks54.2k
Last analyzedOct 23, 2026Oct 3, 2026

Key differences

  • a3m-router offers heuristic and ML-based routing, while freellmapi routes using model selection, quota tracking, key rotation, and fallback.
  • a3m-router describes semantic caching and optional parallel ensembles; freellmapi highlights a dashboard, usage analytics, and client and MCP helpers.
  • a3m-router lists support for 80+ providers with runtime availability checks, while freellmapi combines configured free-tier providers with custom OpenAI-compatible endpoints.
  • freellmapi supports additional Anthropic, Gemini, and optional Ollama-compatible interfaces, while a3m-router describes an OpenAI-compatible chat completions endpoint.
  • freellmapi is positioned for personal experimentation and explicitly not for production; a3m-router is aimed at teams operating routing infrastructure themselves and advises validating capabilities before production use.
  • Both projects are TypeScript and MIT-licensed; freellmapi describes local, Docker, and desktop installation options, while a3m-router provides CLI commands for serving and route and provider checks.

Choose a3m-router if you…

  • need heuristic or ML-based routing, provider failover, or semantic caching.
  • want optional parallel ensembles to compare and combine provider responses.
  • plan to operate a self-hosted routing gateway for a team.
Read the a3m-router analysis →

Choose freellmapi if you…

  • want to combine free provider tiers and custom OpenAI-compatible endpoints behind one API.
  • need quota tracking, key rotation, a dashboard, or compatible client and agent helpers.
  • are experimenting with models or prototyping workflows rather than running production inference.
Read the freellmapi analysis →

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This comparison is generated with AI from the OSRepos analyses of both projects. Always check each project's repository and documentation before choosing.