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# `[2026-08-25]` Fused MoE kernel path — DEFERRED, tracked at park `fused-moe-kernel-path-for-gemma-4-moe-training` (id 47).
**Fused MoE kernel path — DEFERRED, tracked at park `fused-moe-kernel-path-for-gemma-4-moe-training` (id 47).** Operator: "note the fused MoE kernel for round two… if we nail it soon, the math has us wanting to restart the run anyway." Training MFU is **8.6%** (27.1 of a benchmarked 313.8 TFLOPS) because `transformers` runs the Gemma-4 experts in a Python loop — 128 experts × 30 layers, ~11,500 iterations per step under gradient checkpointing. ⚠ **The same fused 3-D expert layout that made bitsandbytes skip 88.5% of the model is exactly what a grouped GEMM wants** — the format is good for storage and for fused kernels, and hostile only to naive iteration. Two fixes: `group_by_length` (−29.9% compute, free, but breaks the seeded order manifest and re-opens a batch-composition call brokkr already made) and a grouped-GEMM/compiled MoE forward (the remaining ~10×). **Not applied to the live run** — restarting mid-flight to change batch ordering was judged a bad trade at step ~50 of 1,312.