Comment on: Experiment: Fused Q·Centroid compressed attention for turbo3 decode

## Final experiment results — dequant-level optimization ceiling reached ### Complete M2 Pro scoreboard (8K decode, q8_0 = 21.9 tok/s): | # | Approach | tok/s | vs q8_0 | vs Main | Const addrs | |---|----------|-------|---------|---------|-------------| | — | No-op ceiling | 24.5 | 1.119x | — | 0 | | **1** | **4-mag LUT + per-elem norm** | **15.1** | **0.689x** | **+38%** | **4** | | 2 | Batched extract (8-LUT) | 13.7 | 0.626x | +25% | 8 | | 3 | Deferred norm (4-mag) | 12.9 | 0.589x | +18% | 4 | | 4 | 2-pair half2 LUT | 12.0 | 0.548x | +10% | 2 | | 5 | Select chain (zero LUT) | 11.9 | 0.544x | +9% | 0 | | 6 | Bit-arithmetic | 11.6 | 0.530x | +6% | 0 | | — | Main (8-entry LUT) | 10.95 | 0.500x | baseline | 8 | | 7 | Non-vec forced (nl=2) | 10.2 | 0.466x | -7% | 8 | ### Key insight: 4 constant addresses is the sweet spot on M2 Pro - **0 addresses** (select chain, bit-arith): ALU cost exceeds constant cache savings - **2 addresses** (half2 pairs): ternary overhead exceeds savings from ...