vLLM Semantic Router beats frontier models by making multiple models collaborate inside one API call

Micro-Agent: Beat Frontier Models with Collaboration Inside Model API

vLLM's Micro-Agent makes multiple models collaborate behind a single API endpoint. Users call one model name as usual; the router decides whether to try a cheaper model first, run several in parallel and aggregate, or let models review each other. The core idea is turning one API call into a bounded micro-collaboration with budget, topology, and failure policy. The post describes five looper patterns—Confidence, Ratings, ReMoM, Fusion, and Workflows—and claims they beat individual frontier models on benchmarks, though it does not name the benchmarks or provide scores.

Why it matters: vLLM upgrades semantic routing into a model-collaboration engine with five concrete patterns and budget controls — highly relevant for inference engineers. Held back from 80+ because it's a blog post, not a shipped product, and performance numbers aren't fully disclosed in the...