Nemotron 3.5 Super VL
Nemotron 3.5 Super VL, which NVIDIA shipped on October 15, 2026, is an open 120B-parameter vision-language model that activates 12B parameters per token, released alongside Nemotron 3.5 Bolt for local machines.
Model: Nemotron 3.5 Super VL (
nvidia/NVIDIA-Nemotron-3.5-Super-VL-120B-A12B-BF16)Maker: NVIDIA
Ship date: October 15, 2026
Pricing: Free (open weights)
Context: 1M tokens
Where you can use it:
Hugging Face weights, plus NVIDIA NIM
OpenRouter, ModelScope and one DGX Spark
When to reach for it:
Agents that read charts, PDFs and web pages
Fast, self-hosted agents you can post-train
Skip it for top coding accuracy
How it compares:
Beats Qwen3.5-122B-A10B on most text evals
Trails Qwen3.8-Flash-Next on most evals
What makes it different:
Hybrid Mamba-Transformer MoE with vision
Open weights, data and training recipes
Early reactions: On launch day, one Hacker News commenter said NVIDIA's own benchmarks put it well behind Qwen3.8-Flash-Next on nearly everything but speed, while another singled out its LiLiCorr speculative decoding and Mamba layers.
Read more: NVIDIA Nemotron 3.5 Super VL Powers Specialized Agents with Multimodal Reasoning, Open From Data Center to Desktop: NVIDIA Expands Nemotron Family With Highest Efficiency Super VL and Bolt Models, Hugging Face model card, Nemotron 3.5 Super and Lightning technical report
The benchmarks
Scores are the BF16 checkpoint against six open models NVIDIA picked, all run in NVIDIA's own NeMo Gym harnesses with each model card's recommended sampling (NVIDIA doesn't name the reasoning mode for this table), SWE-bench rows in the OpenCode harness, and Hermes Bench from NVIDIA's launch blog against Nemotron 3 Ultra only.
NVIDIA's numbers
SWE-bench Pro (harder real-repo fixes): 51.78%. +2.12 over Nemotron 3 Ultra (49.66%), −8.59 under Qwen3.8-Flash-Next (60.37%), −7.92 under GLM-5.3-Flash (59.70%).
SWE-bench Verified (real GitHub fixes): 71.10%. −0.77 under Qwen3.5-122B-A10B (71.87%), −2.83 under Nemotron 3 Ultra (73.93%), −8.00 under GLM-5.3-Flash (79.10%).
GPQA Diamond (PhD-level science): 89.52%. +2.78 over Qwen3.5-122B-A10B (86.74%), +2.53 over Nemotron 3 Ultra (86.99%), −3.16 under Qwen3.8-Flash-Next (92.68%).
Humanity's Last Exam (no tools) (text-only expert questions): 31.79%. +7.55 over Qwen3.5-122B-A10B (24.24%), +2.55 over Nemotron 3 Ultra (29.24%), −7.78 under Qwen3.8-Flash-Next (39.57%).
CharXiv Reasoning (scientific chart questions): 80.82%. −2.65 under Qwen3.5-122B-A10B (83.47%), −1.11 under GLM-5.3-Flash (81.93%), +3.05 over Inkling Small (77.77%).
IFBench (new instruction constraints): 70.86%. +3.30 over Qwen3.5-122B-A10B (67.56%), −12.08 under Nemotron 3 Ultra (82.94%), +13.19 over GLM-5.3-Flash (57.67%).
τ²-bench Telecom (customer-support tool use): 73.19%. −13.98 under Qwen3.5-122B-A10B (87.17%), −9.81 under Nemotron 3 Ultra (83.00%), −25.27 under GLM-5.3-Flash (98.46%).
Hermes Bench (Hermes agent harness tasks): 63.44%. +7.11 over Nemotron 3 Ultra (56.33%).
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