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Overview
We believe Mixture-of-Models is the next-generation model architecture for heterogeneous LLM inference. vLLM Semantic Router makes it executable.
News
Mixture-of-Models for Heterogeneous LLM Inference
We believe Mixture-of-Models is the next-generation model architecture for heterogeneous LLM inference. vLLM Semantic Router makes it executable.
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Report
Eight MI300X GPUs, Six Open Models, Five Routing Objectives
The first AMD Developer Cloud deployment guide showed how to put vLLM Semantic Router in front of a balance-oriented ROCm backend. The maintained multi-objective recipe takes the next step: clients choose the optimization objective they want, while the ro
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Report
Beyond a Single Model: Building Mixture-of-Models Systems with vLLM Semantic Router
Most AI applications are built around a single model endpoint. But as models, devices, and deployment constraints diversify, no single model is the best fit for every request or environment. The practical question is how multiple specialized models can be
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Adding Cursor-Style Auto Model Selection to OpenCode with vLLM Semantic Router
The Feature Everyone Wants and Almost Nobody Has Cursor's Auto mode is deceptively simple: the developer types, and the IDE chooses whether a prompt deserves a frontier model or something faster and cheaper. It is easy to stop noticing - until moving to a
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Micro-Agent: Beat Frontier Models with Collaboration inside Model API
Everyone is watching for the next frontier model. The more interesting layer may be the one in front of it. Routers are becoming the control plane for AI inference. Their first role was practical: route the right request to the right model. That already m
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