GLM-5.2-NVFP4's NextN (MTP) layer-78 routed experts are fp4, but deepseek_nextn unconditionally
dropped modelopt_fp4 for NextN (a DeepSeek-R1-FP4 assumption: its MTP is unquantized). Two fixes
(opus-designed, full back-compat matrix):
A) Drop fp4 for NextN only when the MoE runner can't consume it. Keep fp4 for flashinfer
trtllm/trtllm_routed/cutedsl/cutlass (extends wxiwnd's helper to include our trtllm runner).
R1-FP4/V3-FP4 (non-flashinfer-fp4 or unquantized MTP) still drop → bf16, no regression.
B) The NextN hf_to_sglang_mapper was hardcoded `model.layers.61 -> model.decoder` (R1's MTP idx).
For GLM (MTP=layer 78) this never remapped the layer-78 self_attn/indexer exclude patterns to
the internal model.decoder prefix → NextN attention wrongly quantized fp4 → crash. Worse, keeping
the hardcoded 61 would mis-remap GLM's *real* layer 61. Fix: empty the class mapper and inject
`model.layers.{num_hidden_layers} -> model.decoder` per-config in loader.py (gated on
num_nextn_predict_layers; dataclasses.replace, no class mutation), generalizing to any MTP index.
Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>
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