Model Description Qwen3.5 397B A17B NVFP4 is an NVFP4 quantized version of Qwen/Qwen3.5 397B A17B, a 397B parameter Mixture of Experts vision language model with 17B active parameters, 512 experts per layer (10 active), and hybrid attention (softmax + linear/DeltaNet). The original BF16 weights were quantized to NVFP4 (4 bit with blockwise FP8 scales per 16 elements) using NVIDIA Model Optimizer v0.37.0. What's quantized Only the routed MoE expert MLP layers (gate, up, and down projections) are quantized to NVFP4. The following are left unquantized in BF16: Shared expert MLPs (process every token, unlike routed experts. thanks to Festr for pointing this out) Attention layers (softmax attention and DeltaNet linear attention) Vision encoder (ViT) Router / gate weights MTP (multi token prediction) draft model Embeddings, layer norms, lm head Since the expert weights constitute the vast majority of the 397B parameters, this still yields significant memory savings (~233 GB on disk). Calibration methodology Calibration uses natural top k routing rather than forcing all experts to activate, so each expert's quantization scales reflect the token distributions it actually sees during infere…
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