vllm-loop model-improvement progress tracker junk-tokens
models / / #20
▲ MADE POSITIVE PROGRESS

c1 optimization - TP8xPP1 wins at every depth

Single-stream TP8xPP1 (zero pipeline hops): 98.1/95.0/92.6/88.4 tok/s @8/512/4k/32k vs TP4xPP2 89.4/84.2/87.6/54.1 - decisive at 32k. Accuracy gates pass (needle 4/4, coding 5/5). Tradeoff: 512k aggregate 113 vs 130. TP8xPP1 becomes the served config for c1-first.

When (PT)2026-09-11 13:34 PT
ServingTP8xPP1, DSpark k=5, fp8_ds_mla, 1M ctx
Enginelocal/vllm-dsv41:sm80 @ dsv41-feat@e47aa780
KV

Benchmarks

MetricValueΔ vs previousUnitContextNote
c1_decode_32k_tok_s (c1_decode_32k_tok_s) 88.4 tok/s first point tok/s TP8xPP1 @32k prompt (TP4xPP2 was 54.1)
c1_decode_tok_s (c1_decode_tok_s) 98.1 tok/s -6.6% tok/s TP8xPP1, 8-tok prompt (best of 3)

What was found

  • Under load the GPUs draw ~100 W of 250 W at 1470 MHz - c1 is memory/latency-bound, not power-bound
  • DSpark acceptance 93.6% on predictable content (len 4.68) vs ~35-45% on open prose

raw JSON: /api/reports/20