Tag:llm-serving

All the articles with the tag "llm-serving".

• Evaluating Narwhal: Adaptive Prefill/Decode Allocation Under Rapidly Changing Workloads

  Updated:29 Sep, 2026

  On Kimi-K3 with six TP8 engines, Narwhal delivered 76.18% of chat/document requests within the latency SLO, against 56.76% for Dynamo Planner and 51.66% for Ray Serve LLM. The main trade-off was an 11-second p95 TTFT tail on mixed traffic.

• The Price of Anarchy in Disaggregated Inference

  17 Jun, 2026

  I split NVIDIA Dynamo's prefill and decode into three competing games and measured the Price of Anarchy on a 3-node B200 cluster. While the GPUs had headroom, no router tuning moved the needle; the moment they saturated, one parameter was the gap between a 1-second tail and a 28-second one. So I built a 270-line controller that watches for that moment and flips the switch, without touching Dynamo's core.