Taking vLLM Apart: A Practical Guide to Disaggregated Serving

In 30 Sekunden

Was passiert ist

vLLM v0.30.0 adds disaggregated serving, splitting LLM inference into separate prefill, decode, and CPU-only tokenization stages to reduce latency and improve throughput.

Warum es zählt

Use this when inter-token latency p99 misses your SLO under load, or when long prompts at high concurrency cause stalls in a single-process setup.

Achtung

KV cache transfer speed between prefill and decode is critical; slow transfers can make time-to-first-token worse than collocated serving, and you now operate multiple services instead of one.