Model Serving & Inference · Established · Advanced
vLLM PagedAttention v2
Also known as: vLLM v2 Engine
An upgraded high-throughput inference engine featuring enhanced multi-GPU KV cache allocation and low-latency chunked prefill.
What vLLM PagedAttention v2 is
vLLM PagedAttention v2 is an advanced serving architecture designed for enterprise LLM endpoints requiring ultra-high concurrency.
How it works
Utilizes virtual memory block management to eliminate VRAM fragmentation and dynamically interleave prefill and decode execution passes.
Why it matters
Dramatically lowers inference hosting costs while improving TTFT (Time To First Token) and token throughput.
Common uses
- →High-concurrency LLM APIs
- →Enterprise RAG model serving
- →Multi-GPU inference server
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