// ZDNET — INTELLIGENZA ARTIFICIALE
Nvidia’s new Nemotron 3.5 Super VL is another step forward for US open-weight AI
Nvidia's new models join a wave of open-weight releases from US labs on the heels of the Hugging Face hack.
China-based AI labs have had the upper hand on competitive open-weight AI models over the last few years, but a recent surge in Western-made open models is challenging that.
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Nvidia’s new model, the open-weight Nemotron 3.5 Super VL, aims to be the latest data point in that surge. The 120-billion-parameter model, available today, targets the industry’s increasing focus on agentic work by delivering “the fastest task completion and highest accuracy for specialized, always-on agents,” according to Nvidia.
“As the fastest open agentic model in its class — 5x faster than the next best — it helps enterprise agents complete high-volume tasks faster across workflows that span days or weeks,” Nvidia said in the release. That’s based on Artificial Analysis’ benchmark testing of the model against its similarly sized competitors; InclusionAI’s Ling 3.0 Flash and DeepSeek’s V4.1 Flash came in second and third, respectively, but with significant distance between them and Super VL.
Nvidia also said Super VL achieves top-tier accuracy for specialized agents with post-training. The company cited how far post-training a base version of the model could take its capabilities — in one case, a 44% gain in medical insurance claims, which put the model far above Claude Opus 5. While that means the base model didn’t top proprietary frontier models on its own, it does give enterprises the chance to tailor the model to their needs and see highly specific gains.
As Nvidia pointed out in the release, the advantage open models have over proprietary models is that businesses can post-train them on their own data and run them on their own infrastructure, offering greater personalization and security.
Super VL is flanked by two new edge models as well: Nemotron 3.5 Bolt 74B-A9B 24GB and Nemotron 3.5 Bolt E4B 4GB (no, Nvidia didn’t waste any time on naming here). Edge AI refers to models that can operate locally and off-grid. Nvidia said the former Bolt is built for local agentic use, while the latter Bolt is for “fast, conversational agents.”
Both models “deliver the highest intelligence per gigabyte of memory” relative to Nvidia’s other models, the company said. While the 24GB model, geared toward local agents, achieves the best split of capability and speed per gigabyte, the 4GB model “delivers the best intelligence per gigabyte for its intended use cases,” which Nvidia named as voice and device agents and “interactive characters,” among others.
While it’s unclear whether Nvidia’s new model will raise the bar for open-weight or proprietary models in practice, Artificial Analysis’ findings demonstrate efficiency gains for now.