Gahow Wang
c8ec73c548
High-concurrency test (512 input, 64 output, rates 4-32 req/s): Rate=8: plain TTFT p90=94ms, mooncake_both=102ms → +9% tax Rate=16: plain TTFT p90=144ms, mooncake_both=156ms → +8% tax Rate=32: both saturated at ~6.1s → no distinguishable difference Low-concurrency back-to-back retest (4096 input, 256 output): mooncake_both_v2 vs plain_v2: tax is ≈0% (within noise) because scheduler's 1.4ms/step is hidden behind model forward. Decomposition of trace-replay's +45%: +7-9% from build_connector_meta per-step cost (this microbench) +20-30% from multi-instance coupling amplification (not measurable here) remainder from large-cache O(|cache|) scaling (Phase B follow-up) Also: bench_loop.py now emits mean/p50/p90/p99 for all three metrics.