深入 vLLM：高吞吐 LLM 推理系统的完整剖面
Aleksa Gordic 从一次离线 generate 调用出发，逐层拆解 vLLM V1 的 engine core、调度器、PagedAttention、continuous batching、chunked prefill、prefix caching、guided/speculative decoding、P/D 解耦、多 GPU/多节点服务，以及 TTFT、ITL、吞吐和 roofline 评测。
Inside vLLM: Anatomy of a High-Throughput LLM Inference System
Aleksa Gordic traces vLLM V1 from a single offline generate call through the engine core, scheduler, PagedAttention, continuous batching, chunked prefill, prefix caching, guided/speculative decoding, disaggregated prefill/decode, multi-GPU and multi-node serving, and latency-throughput benchmarking.
https://vllm.ai/blog/2025-09-05-anatomy-of-vllm
vllm.ai
Inside vLLM: Anatomy of a High-Throughput LLM Inference System
How vLLM's inference engine works, covering PagedAttention, continuous batching, prefix caching, speculative decoding, multi-GPU serving, scheduling, and benchm
August 24, 2026 10 1
