LMRouter: Open-Source AI API Router for Multi-Provider Model Access

The explosion of AI language model providers has created a paradoxical situation for developers. On one hand, the diversity is extraordinary — OpenAI, Anthropic, Google, DeepSeek, Mistral, Groq, and dozens more are pushing the state of the art forward every month. On the other hand, each provider has its own API format, authentication mechanism, pricing model, and rate limits. Managing multiple provider integrations in a single application means writing and maintaining adapters for each one, handling failover logic, and tracking costs across disparate billing systems.

LMRouter solves this problem by providing a single, unified API gateway for all major language model providers. Built in TypeScript and released under the MIT license, LMRouter acts as a lightweight proxy that sits between your application and the various AI provider APIs. You configure your own API keys once, and LMRouter presents a single OpenAI-compatible endpoint that routes requests to the appropriate provider based on the model name.

The critical distinction between LMRouter and managed services like OpenRouter is BYOK — Bring Your Own Key. LMRouter does not charge for API access or add margins to provider pricing. You configure your own keys, pay providers directly, and LMRouter handles the routing, failover, and cost tracking. For teams that need control over their AI infrastructure without the overhead of building custom integration code, LMRouter is an elegant solution.

What Providers Does LMRouter Support?

LMRouter supports a rapidly growing list of AI providers, covering all major frontier model families:

How Does LMRouter Work?

LMRouter’s architecture is straightforward. It runs as a local or cloud-hosted HTTP server that accepts requests in OpenAI’s chat completions format and routes them to the appropriate provider based on the requested model:

flowchart LR
    A[Your Application] --> B{LMRouter API Gateway}
    B --> C[OpenAI Key]
    B --> D[Anthropic Key]
    B --> E[Google Key]
    B --> F[DeepSeek Key]
    B --> G[10+ Providers...]
    
    H[Config File<br/>API Keys + Routing Rules] --> B

The routing logic is model-name based. When LMRouter receives a request for gpt-4o, it routes to OpenAI. A request for claude-sonnet-4 goes to Anthropic. The system handles the format translation transparently — converting between OpenAI’s chat format and each provider’s native API format.

What Are the Key Features?

Beyond basic routing, LMRouter provides a set of features that make it suitable for production use:

How Does LMRouter Compare to Alternatives?

How to Deploy LMRouter

LMRouter offers multiple deployment options to suit different environments:

# Docker (recommended for production)
docker run -d \
  -p 8080:8080 \
  -v ./config.yaml:/app/config.yaml \
  ghcr.io/lmrouter/lmrouter:latest

# Node.js (for development)
git clone https://github.com/LMRouter/lmrouter.git
cd lmrouter
npm install
npm run dev

Configuration is done through a config.yaml file where you specify your API keys, rate limits, and routing rules:

What Can You Build with LMRouter?

LMRouter enables several architectural patterns that would otherwise require significant custom infrastructure:

• Multi-provider AI applications: Build applications that can switch between providers based on cost, latency, or capability requirements
• Cost-optimized routing: Route simple queries to cheaper models and complex reasoning tasks to frontier models
• High-availability AI systems: Configure provider failover so your application stays online even when one provider has an outage
• Team AI gateways: Deploy a shared gateway with centralized cost tracking and rate limiting for team use
• Development and testing: Use different providers for staging and production without changing application code

Frequently Asked Questions

What is LMRouter?

LMRouter is an open-source AI API router that provides a single, unified API endpoint and key for accessing language models across 10+ providers. It supports text, image, audio, and video modalities through a consistent API interface and is designed as a self-hosted alternative to managed router services.

What providers does LMRouter support?

LMRouter supports 10+ AI providers including OpenAI, Anthropic, Google, Groq, DeepSeek, Mistral, Cohere, Together AI, Fireworks AI, and custom OpenAI-compatible endpoints. The provider list is actively expanding through community contributions.

What is BYOK and how does it work?

BYOK (Bring Your Own Key) is a core design principle of LMRouter. Users configure their own API keys for each provider, and LMRouter does not charge for API usage — it only routes requests to the providers whose keys you have configured. This means you pay provider prices directly with no markup.

How can LMRouter be deployed?

LMRouter offers multiple deployment options: as a Docker container (recommended), directly via Node.js, or through cloud deployment platforms. It includes configuration for rate limiting, cost tracking, and provider failover.

What is LMRouter’s license?

LMRouter is released under the MIT license, making it free to use, modify, and distribute for both personal and commercial projects. The entire source code is available on GitHub.

Further Reading

• LMRouter GitHub Repository — Source code, Docker images, and configuration examples
• OpenRouter — Managed alternative for comparison
• OpenAI API Reference — The API format LMRouter emulates for compatibility
• Docker Compose Documentation — Deployment guide for Docker-based LMRouter installations