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vLLM Semantic Router

Make Your Mixture-of-Models Programmable.

Documentation | Playground | Blog | Publications | Hugging Face


About

vLLM Semantic Router is a programmable routing layer for building Mixture-of-Models systems across heterogeneous LLM infrastructure. It evaluates request signals, user preferences, and application policies to select—or compose—the right model path for each request.

Use it to improve quality, cost, latency, privacy, and safety without hard-coding routing logic into applications.

Dimension Fragmented today With vLLM SR
Models Models specialize in different work. Compose personalized model paths.
Compute GPUs, accelerators, edge, and cloud coexist. Route across heterogeneous compute.
Location Inference spans edge, private, and cloud. Keep data within its boundaries.
Preference "Best" changes by user and workload. Make every preference executable.

Explore how it works →

Getting Started

Install

curl -fsSL https://vllm-sr.ai/install.sh | bash

For platform notes, detailed setup options, and troubleshooting, see the Installation Guide.

Online playground credentials
  • Username: love@vllm-sr.ai
  • Password: vllm-sr

Latest News

Earlier announcements

More announcements are available on the Blog and Publications pages.

Community

For questions, feedback, or to contribute, please join the #semantic-router channel in vLLM Slack.

Community Meetings

We host community meetings on the first and third Tuesday of each month to sync with contributors across different time zones:

Contributing

If you want to contribute, start with CONTRIBUTING.md.

For repository-native development workflow and validation commands, use AGENTS.md as the entrypoint and tools/agent/docs/README.md as the canonical index.

Citation

If you find Semantic Router helpful in your research or projects, please consider citing it:

@misc{semanticrouter2025,
  title={vLLM Semantic Router},
  author={vLLM Semantic Router Team},
  year={2025},
  howpublished={\url{https://github.com/vllm-project/semantic-router}},
}

Sponsors

We are grateful to our sponsors who support us:


AMD provides us with GPU resources and ROCm™ software for training and researching frontier router models, enhancing E2E testing, and building the online models playground.