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vLLM Semantic Router: An open, programmable decision layer for models and compute (6.2k stars) What it does All text below is quoted directly from the project README. >An open, programmable decision layer for models and compute. >Intelligence beyond any one model. >Give your agent harness one API for many models. vLLM Semantic Router selects or combines models for each call, guided by your policy. >Your harness keeps the agent loop, tools, and task state. The Router chooses among configured backends across local, private, and cloud compute. With vLLM SR: - Models: Different models excel at different tasks. Select or combine models. - Compute: Hardware varies in speed and capacity. Choose among configured backends. - Location: Edge, private, and cloud. Keep calls within approved locations. - Preference: Priorities change by task. Set quality, latency, and cost priorities. >Point your harness at the Router's inference endpoint. Use a public model ID such as vllm-sr/auto. >For questions, feedback, or to contribute, please join the #semantic-router channel in vLLM Slack. Repository vllm-project/semantic-router Repository stats |Metric|Value| |:-|:-| |Stars|6,151| |Forks|1.0k| |Last release|v0.4.0 (2026-09-27)| |Languages|Go 51.4%, Python 30.4%, TypeScript 11.9%| |Contributors|261| |AI contributor accounts (Claude / Codex / Cursor / Copilot)|claude (51 commits), cursoragent (41), Copilot (30)| |AI co-authored commits|Claude: 52, Cursor: 41, Copilot: 31| Main contributor |Field|Value| |:-|:-| |Name|Xunzhuo| |GitHub|@Xunzhuo| |Commits to this repo|697 (top contributor)| |Bio|Intelligent Routing @vllm-project | Open Source & AI @AMD| |X / Twitter|@XunzhuoLiu| |Followers|1.4k|