a3m-router vs TurboLLM
Self-hosted LLM routing and local inference compared
a3m-router routes OpenAI-compatible requests across external models and providers, while TurboLLM runs language models locally and provides browser and API access. The main distinction is routing requests among provider models versus managing local inference engines and hardware tuning.
a3m-router: Route LLM Requests Across Models
A3M Router is a TypeScript, self-hosted LLM gateway built around Jev System One single-pass routing. It directs OpenAI-compatible requests to models and providers based on the task, with failover and optional parallel ensembles.
TurboLLM: Run Local Language Models With GPU Tuning
TurboLLM runs local language models through a browser interface and OpenAI- or Anthropic-compatible APIs. It suits developers who want hardware-aware tuning and a choice of inference engines, including community forks.
| a3m-router | TurboLLM | |
|---|---|---|
| Language | TypeScript | TypeScript |
| License | MIT | — |
| Stars | 17 | 278 |
| Forks | 5 | 40 |
| Last analyzed | Oct 23, 2026 | Oct 3, 2026 |
Key differences
- a3m-router is a TypeScript gateway for heuristic or Jev System One routing; TurboLLM is a TypeScript runtime and web app for local models.
- a3m-router advertises support for more than 80 providers, with availability checked at runtime; TurboLLM supports llama-server-compatible engines, including selected MLX and vLLM types.
- a3m-router offers provider failover, semantic caching, conversation memory, and optional parallel ensembles; TurboLLM focuses on model downloads, engine selection, and hardware-aware benchmarking and tuning.
- a3m-router provides an OpenAI-compatible chat completions API; TurboLLM provides OpenAI- and Anthropic-compatible APIs, including Claude Code integration support.
- a3m-router is MIT-licensed and can run with Node.js or Docker; TurboLLM requires Node.js and a terminal command, and its FSL-1.1 license includes a future Apache-2.0 grant.
- a3m-router is a young project with 17 stars and 5 forks; TurboLLM has 278 stars and 40 forks.
Choose a3m-router if you…
- need a self-hosted gateway that routes OpenAI-compatible requests across providers.
- want failover or parallel provider ensembles for mixed workloads.
- prefer an MIT-licensed project and can run a local routing service.
Choose TurboLLM if you…
- want to run models on your own hardware through a browser interface or compatible API.
- need to try supported inference engines and tune settings for available hardware.
- want to connect Claude Code or other compatible tools to local models.
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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.