Featured Inside vLLM: Anatomy of a High-Throughput LLM Inference System Sep 5, 2025 · 41 min read In this post, I'll gradually introduce all of the core system components and advanced features that make up a modern high-throughput LLM inference system. In particular I'll be doing a breakdown...

Inside vLLM: Anatomy of a High-Throughput LLM Inference System Note: Originally posted on Aleksa Gordic's website. From paged attention, continuous batching, prefix caching, specdec, etc. to multi-GPU, multi-node dynamic serving at scale In this post, I'll gradually introduce all of the core system components and advanced features that make up a modern high-throughput LLM inference system. In particular I'll be doing a breakdown of how vLLM [1] works. This post is the first in a series. It starts broad and then layers in detail (following an inverse-pyramid approach) so you can form an accurate high-level mental model of the complete system without drowning in minutiae. Later posts will dive into specific subsystems. This post is structured into five parts: - LLM engine & engine core: fundamentals of vLLM (scheduling, paged attention, continuous batching, etc.) - Advanced features: chunked prefill, prefix…