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Wan2.2-T2V-A14B β€” QK-INT8 Γ— PV-FP8 attention ablation (B200, 2026-07-21)

End-to-end video quality of low-bit attention kernels, measured against an FA4-CuTe bf16 ground truth. 32 MovieGenVideoBench prompts, seed 42, 1280Γ—720, 81 frames, UniPC 40 steps, shift 12, CFG 4.

Shared quantization recipe (all configs): QK INT8 β€” Q per-token scale, K per-128-token scale; PV FP8 β€” V per-channel scale. Softmax row-sum computed on tensor cores (l-MMA); exact exp = FA4-style EX2 + polynomial mix; split-P = 64.

Results (mean over 32 videos vs FA4 bf16 GT)

Config PSNR ↑ SSIM ↑ LPIPS ↓
Sage2 baseline β€” no QK transform, K per-channel smooth, V per-channel smooth 20.43 0.7402 0.2008
Ours (exact exp) β€” + QK Hadamard, V balanced-kmeans reorder + per-128-block smooth 21.24 0.7609 0.1757
Ours + 50% linmant exp approx (hybrid50) 19.97 0.7204 0.2136
Ours + 100% linmant exp approx 19.59 0.7049 0.2250

Paired per-video statistics (n = 32):

  • Ours (exact) vs Sage2: +0.803 dB PSNR (SEM 0.444, wins 20/32, β‰ˆ1.8Οƒ)
  • linmant vs exact: βˆ’1.647 dB (SEM 0.463); hybrid50 vs exact: βˆ’1.264 dB (SEM 0.428)

Note: the 40-step diffusion chaos floor gives a per-video Οƒ of ~2.3–2.9 dB, so per-prompt deltas swing widely in both directions even when the mean improves β€” the three sample prompts below were chosen to show exactly that spread.

Sample videos (videos/)

Naming: <prompt>__<config>.mp4, configs = gt_fa4 (reference), sage2, ours_exact, ours_hybrid50, ours_linmant. PSNR vs GT per video:

Prompt sage2 ours_exact ours_hybrid50 ours_linmant novsmooth_linmant
A_documentary-style_00250 (best case, ours +6.1 dB) 20.81 26.91 24.59 24.89 23.76
A_macro_shot_in_real_00692 (median, ours +0.4 dB) 16.38 16.82 18.59 18.56 15.32
A_steampunk-inspired_00733 (worst case, ours βˆ’5.1 dB) 24.51 19.39 18.75 18.94 β€”

novsmooth_linmant is a stress probe: V-smooth fully OFF (per-channel FP8 V only) + 100% linmant exp approx. No structural collapse β€” videos stay coherent; the cost of removing V-smooth under linmant is content-dependent (βˆ’1.1 dB on 00250, βˆ’3.2 dB on 00692).

Hardware: NVIDIA B200 (sm100), CuTe-DSL kernels (tcgen05). Generated with the fp8-attention max-approx kernel branch; balanced-kmeans V reorder reuses the permutation across denoise steps inside an adaptive window.

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