vLLM capabilities and measurement

vLLM capabilities and measurement An architecture diagram generated by Archify. PagedAttention · Block-level KV cache management · vLLM Core Technologies PagedAttention Block-level KV cache management Continuous Batching · vLLM Core Technologies Continuous Batching Prefix Caching · --enable-prefix-caching · vLLM Core Technologies Prefix Caching --enable-prefix-caching Chunked Prefill · --enable-chunked-prefill · vLLM Core Technologies Chunked Prefill --enable-chunked-prefill KV fragmentation · separate weights / KV / workspace · Validate by measurement KV fragmentation separate weights / KV / workspace Throughput and queues · concurrency / token budgets · Validate by measurement Throughput and queues concurrency / token budgets Reusable prefixes · measure conditional TTFT · Validate by measurement Reusable prefixes measure conditional TTFT Prefill / decode scheduling · long-context memory budget · Validate by measurement Prefill / decode scheduling long-context memory budget block allocation workload dependent KV reuse conditions scheduler budget vLLM Core Technologies Validate by measurement Legend vLLM Core Technologies Measure per workload

No fixed speedup guarantee

  • • gpu-memory-utilization is not a KV-only fraction.
  • • Prefix KV caching differs from full-response caching.
  • • Pin image, model and drivers; measure latency and throughput.