Anatomy of the vLLM Engine
Anatomy of the vLLM Engine vLLM is the most widely deployed open-source engine for serving large language models, and its core ideas have been quietly copied by nearly every serving framework that came after it. This article walks through the engine from the inside out: the prefill/decode execution model and its latency metrics, the paged KV cache (PagedAttention), the unified scheduler of the current V1 engine, preemption and prefix caching, and the Prometheus metrics vLLM exposes for production monitoring. It closes with the boundaries against neighboring systems — FlashAttention, SGLang, and disaggregated prefill — and an honest reproduction guide for a single TITAN RTX.