A verified Large-preset win — and the historical curve around it
A frozen ABBA run on an Apple M5 Pro measured 10.67× WebGPU-over-WASM speedup on Large, with 4.72% maximum paired final-loss drift and zero runtime errors. That point is verified for this machine and configuration. The older Small, Medium, and XL values remain historical.
evals/verified-wins/webgpu-paired-result-v1.json.
Chrome 151 identified apple · metal-3, rejected software and
fallback adapters, and ran WASM → WebGPU → WebGPU → WASM on identical inputs.
The retained 2.6×–12.1× multi-preset curve is still historical evidence only.
The hypothesis encoded by the curve
Every training step costs fixed_overhead + math(model_size). Larger matmuls should amortize GPU dispatch overhead better. The historical curve is consistent with that mechanism, but the mechanism does not verify the retained numbers.
The shipped default WebGPU path uses blocked4 matmul, vec4 loads, subgroup-cooperative reductions, and Flash Attention 2 forward and backward. Use the playground's live benchmark for exploration; use a paired JSON receipt before publishing a performance result.