Root-caused the NVFP4 gibberish to a quant-namespace bug: quant_nvfp4.py loaded
via AutoModelForCausalLM -> text-only Qwen3_5ForCausalLM -> flat model.layers.* keys,
but vLLM 0.24 serves only Qwen3_5ForConditionalGeneration (whose weight mapper needs
model.language_model.*). Fixed by loading as AutoModelForImageTextToText; NVFP4 now
serves coherent (validated greedy on ana-ml2 GPU0).
Base NVFP4 (compressed-tensors) measured ~53 tok/s (~= GGUF at batch-1, no single-stream
win) and its MTP is 0% acceptance (vLLM's Qwen3_5MTP drafter loads the bf16 mtp head only
off a modelopt main-model checkpoint). Added quant_modelopt.py (nvidia-modelopt PTQ,
matches AEON's NVFP4 W4A4 g16 + lm_head/linear_attn/visual exclusions) as the path to
working native MTP; graft + splice + serve otherwise unchanged.
vh
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