The generic scale pass in llama-model.cpp loads the per-expert
NVFP4 scale2 tensors (ffn_{up,gate,down}_exps_s) and the per-tensor
MXFP8 scales for the dense FFN and the shared expert, but
minimax-m3.cpp never forwarded any of them to the graph.
build_moe_ffn() defaults these to nullptr, so build_lora_mm_id()
skipped its w_s branch entirely and the routed-expert weights came
out global_scale times too large, swamping the residual (reported
G ~= 15123 for M3.1 Flash) and producing token soup.
Forward all scale tensors at the three call sites, matching the
pattern used by flint and the other NVFP4-capable MoE models.
Co-authored-by: origin-labs-ai <origin-labs-ai@users.noreply.github.com>
