Every free model. One endpoint.

The major AI labs all offer free capacity. Separately, each allowance is small and comes with its own SDK, model names, quota rules and failure modes. Together, they are a serious amount of compute—if something can keep track of all the moving pieces.

FreeLLMAPI makes that fragmentation disappear behind the interface developers already know. An existing OpenAI client only changes two values: its base URL and API key.

const client = new OpenAI({
  baseURL: 'http://localhost:3001/v1',
  apiKey: 'freellmapi-…'
})

await client.chat.completions.create({
  model: 'auto',
  messages
})

A routing layer scores models against capability, speed, reliability and remaining quota. When a provider rate-limits, times out or fails, the key cools down and the same request moves to the next viable route—without the calling app learning a new integration.

• Smart routingPriority, balanced, smartest, fastest, reliable or a custom weighting.
• Quota-aware falloverTracks RPM, RPD, TPM and TPD per model and key before a request is sent.
• One compatibility layerChat, responses, embeddings, images, audio, tools, structured output and MCP.
• Local-first by designProvider keys stay in the user’s own SQLite database, encrypted with AES-256-GCM.

React·TypeScript·Express·SQLite·Docker·Electron

The dashboard makes the router legible. Add and health-check provider keys, inspect the budget across the whole pool, drag the fallback order, test a prompt, then trace request volume and latency back to the provider that served it.

It runs as a Docker service or a native desktop app on macOS and Windows. The UI ships in six languages, while a signed live catalog keeps model launches, quota changes and provider quirks current without a reinstall.