NVIDIA's quantized release of Nemotron 3.5 Super VL (2026-10-23, NVFP4 with quantization-aware distillation from the BF16 model): a 120B-total / 12B-active vision-language MoE. The architecture interleaves Mamba-2 and Transformer attention layers in a hybrid MoE, with a C-RADIO vision encoder and a vision-language connector; context runs up to **1,000,000 tokens**, and native Multi-Token Prediction (MTP) enables speculative decoding (official LiLiCorr drafter, seven speculative tokens per step). Reasoning level is switchable between off / on (medium) / on through the chat template; deployment targets are 1x DGX Spark (GB10), 1x RTX PRO 6000, 1x H200, 2x H100 or 1x GB200, running on vLLM (official nightly image with --speculative_config.method dflash, mamba-backend flashinfer, video-pruning-rate 0.5). The NVFP4 weights measure **75.0GB** in total across 88 safetensors shards. Benchmarks (NVFP4 / BF16): GPQA-Diamond 89.90 / 89.52, Terminal-Bench 2.1 62.78 / 60.67, SWE-bench Verified 71.07 / 71.10, SWE-bench Pro 51.30 / 51.78, tau2-bench retail 69.30 / 69.24, tau2-bench airline 75.75 / 76.50, Video-MME v2 32.54 / 32.85, OSWorld-Verified 52.3 / 51.14, AA-Omniscience index 5.3 / 4.03, GDPval-AA v2 1206 / 1211. License is OpenMDW-1.1 (commercial use permitted). **Cataloged with zero on-site runs**: under the site's conservative padded VRAM accounting a 120B-class NVFP4 model needs roughly 180GB+, so 96GB-class cards do not get a fit verdict.
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