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vLLM Semantic Router

An intelligent Mixture-of-Models router that directs requests to the most suitable models to improve inference accuracy and efficiency.

Introduction

vLLM Semantic Router is a high-performance routing framework that uses semantic understanding to dispatch requests to the best-suited model or service, improving accuracy while optimizing cost and latency.

Key features

  • Semantic classification-based model selection (BERT classifier / Mixture-of-Models).
  • Similarity caching to reduce redundant computation and latency.
  • Enterprise-grade security: PII detection and prompt guard.

Use cases

  • Request routing and model orchestration in multi-model deployments.
  • Inference platforms balancing latency, cost, and accuracy.
  • Integrating routing as part of an AI gateway or microservice stack.

Technical details

  • Multi-language implementation (Go core with Python benchmarks and Rust bindings).
  • Integrations with vLLM and Hugging Face Candle backends, with Grafana dashboards and deployment scripts.
  • Comprehensive docs, examples and benchmarks (bench & examples).

Comments

vLLM Semantic Router
Resource Info
Author vLLM Semantic Router Team
Added Date 2025-09-30
Open Source Since 2025-08-26
Tags
Open Source LLM Router AI Gateway Inference