Nvidia on Thursday launched new open-weight models designed for always-on agents and edge computing. The Nvidia open models lineup now spans two very different ends of the market: a large system built for enterprise agents and a pair of lightweight models meant to run locally on new AI PCs.
The headline release is the Nemotron 3.5 Super VL, a large 120-billion-parameter model geared for agents used by the enterprise. While it uses fewer parameters than the Nemotron 3 Ultra model, Nvidia says it can deliver similar accuracy in instruction-following and tool-use tasks.
At the other end of the spectrum, the company also launched two lightweight Bolt models. These are intended to run locally on the new AI PCs (running the Nvidia RTX Spark chip) and workstations running the DGX Spark. Such PCs, aimed at consumers, programmers, and enterprise knowledge workers, are being released right now into the market through partners like Microsoft and Dell.
Why Nvidia Is Pushing Open Weights
“Any organization that wants to run agents on Nvidia infrastructure now has an open, optimized model for their tier without having to choose between capability and deployability,” Nvidia’s vice president of Open Models and Software, Kari Briski, wrote in the blog post announcing these models.
That quote captures the pitch behind the Nvidia open models strategy. Enterprises increasingly want to run their own models in their own data centers, and Nvidia is positioning its releases as the way to do that without giving up performance.
Nvidia claims that the Super VL completes tasks faster than competing models from Anthropic and OpenAI (Opus 5, GPT 6.1 Sol, Luna, Astra) when post-trained on specific agentic tasks. These tasks include document intelligence, financial accounting, scientific experimentation, medical insurance claims, and security attack resilience.
While such claims are standard whenever a major tech company announces a new model, Nvidia has backed it up with a list of heavy-hitter companies that it says are using Super VL. These include Skydance, EY, Ramp, Crowdstrike, Perplexity, and Salesforce.
Part of a Much Larger Family
These aren’t the first open-weight models that Nvidia has released that compete with the proprietary frontier labs — companies that are both its customers and its investments. The GPU giant has an entire family of Nemotron models that do everything from multimodal artificial intelligence to reasoning, coding, math, and enterprise automation.
However, those fast-growing proprietary AI labs are now looking to many other chips and AI system makers beyond Nvidia to power their needs, like AWS’s Trainium and Cerebras, as well as building their own home-grown chips.
So Nvidia is leaning hard into the trend of enterprise companies wanting to run their own open models in their own data centers. “Unlike closed frontier models, organizations can post-train Super VL on their own data, deploy it on their own infrastructure and own what they build,” Briski wrote.
Agents That Stay on the Device
With the announcement of the smaller, local PC models, Nvidia is also trying to push forward the nascent trend of consumer AI assistants. While it seems a new AI assistant is introduced every day by startups and Big Tech alike, privacy-weary consumers may not want to invite such agents so deeply into their lives, giving them access to info about their families, health, finances, and so on.
So, while Nvidia hopes to create a new market for itself selling PCs powered by its chips by creating machines that run the models and agents locally, PC users “can delegate everyday projects … without sending those workloads to the cloud,” Briski wrote.
How the Three Models Compare
Of the two Bolt models, Nemotron 3.5 Bolt 74B-A9B 24GB is a 74-billion parameter model designed for local agentic tasks. It is intended to balance speed with reasoning to handle multistep reasoning, tool calling, and web browsing. The smallest Bolt E4B is aimed at conversational agents.
| Model | Parameters | Intended Use | Availability |
|---|---|---|---|
| Nemotron 3.5 Super VL | 120 billion | Enterprise agents | Available now |
| Nemotron 3.5 Bolt 74B-A9B 24GB | 74 billion | Local agentic tasks | Available now |
| Nemotron 3.5 Bolt E4B | Smallest Bolt model | Conversational agents | Later this month |
Super VL and Bolt 74B-A9B are available now, with Bolt E4B coming later this month, Nvidia says.
What the Nvidia Open Models Mean for Buyers
For enterprises, the appeal is control. Teams can post-train Super VL on their own data and deploy it on their own infrastructure, rather than depending entirely on a closed frontier system. That matters for regulated industries handling sensitive documents, claims, and financial records.
For consumers and knowledge workers, the Bolt models promise capable local agents without cloud dependence. Running agents on the device keeps personal and work data closer to home, which is exactly the trade-off privacy-conscious users are looking for.
The broader takeaway is that the Nvidia open models push now covers every tier of deployment. Whether an organization needs a 120-billion-parameter workhorse in its data center or a compact assistant on a laptop, Nvidia is arguing it has an optimized option that doesn’t force a choice between capability and deployability.
