vLLM(@vllm_project):Great work from the vLLM Semantic Router, KR Labs, and @AMD teams on Vela 3.0! Routing decisions and span extraction in one call, with six open models from 0.3B to 27B. More flexibility in what the router can detect and how small it can run.

vLLM

@vllm_project

A high-throughput and memory-efficient inference and serving engine for LLMs. Join to discuss together with the community!

Joined March 2024

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vLLM@vllm_project

2026.10.28 13:11

Great work from the vLLM Semantic Router, KR Labs, and @AMD teams on Vela 3.0! Routing decisions and span extraction in one call, with six open models from 0.3B to 27B. More flexibility in what the router can detect and how small it can run.

Xunzhuo@XunzhuoLiu

2026.10.28 12:53

Introducing Vela 3.0 📡 Name it. Vela finds it. Six open models (0.3B–27B): decisions + the spans you name. One call. ⚡ 380M: #1# Decision Index ≤500M 🎯 Beats GPT-5-mini at zero-shot classification 🔍 18 ms per span question 🤗 #Jev# #Decison#