Nvidia Becomes a Major Model Maker With Nemotron 3
Summary
Nvidia has launched Nemotron 3, a family of high-performance open models (Nano: 30B, Super: 100B, Ultra: 500B) and accompanying training data and tools designed for developers to download, modify and run on their own hardware. The company is releasing its training data, new libraries for reinforcement learning and a hybrid latent mixture-of-experts architecture aimed at building agentic systems that can act on computers and the web. Nvidia positions this as a commitment to open innovation while hedging against AI companies that might favour their own chips over Nvidia silicon.
The move addresses a gap in up-to-date open models (where Chinese firms have been strong) and includes resources for customisation and fine-tuning — making Nemotron 3 useful both for experimentation and for building specialised agents, though the largest models require substantial hardware.
Key Points
- Nemotron 3 is an open-model release from Nvidia with three sizes: Nano (30B), Super (100B) and Ultra (500B).
- Nvidia is publishing training data and developer tools to make the models easier to customise and fine-tune.
- The models use a new hybrid latent mixture-of-experts architecture targeted at agentic behaviours and action-taking on the web and computers.
- Libraries for reinforcement learning are included to help train agents with simulated rewards and punishments.
- Releasing open models is a strategic hedge: as competitors like OpenAI, Google and Anthropic develop their own silicon, Nvidia needs to keep software ecosystems tied to its hardware and maintain influence over AI development.
- Chinese companies currently lead in frequently updated open models; Nvidia’s move aims to make Western open models more competitive for engineers and startups.
- The largest Nemotron models (500B) are computationally expensive and will typically need racks of hardware to run.
Why should I read this?
Short version: if you care about who shapes the tools that will run tomorrow’s AI, this matters. Nvidia just went from being the world’s GPU shopkeeper to publishing serious open models — training data, tools and all — which changes the game for developers, startups and cloud providers. It’s the kind of strategic play that could steer where people build and run models for years. Read it if you want to know where the centre of gravity in AI tooling is shifting.
Author (Punchy)
Will Knight lays out a clear, no-nonsense view: Nvidia isn’t just safeguarding its chip business — it’s trying to set the rules of open-source AI. This is not fluff: the launch comes with real assets (data, code, architecture) that make Nemotron 3 usable, not just promotional noise. If you work with models, this announcement is worth digging into.
Context and Relevance
Why this is important: the AI industry is polarising between closed, vertically integrated stacks (model + silicon + cloud) and open ecosystems that favour experimentation. Nvidia’s release bolsters the open side while protecting its silicon business as rivals develop their own chips. For engineers, researchers and businesses that rely on flexible models and customisation, Nemotron 3 reduces dependence on closed APIs and offers a Western alternative to Chinese open models.
How it relates to trends: the announcement sits at the intersection of geopolitics, supply-chain risk and platform strategy — US export decisions, Chinese efforts to favour domestic silicon, and competition among AI platform providers all make Nvidia’s move strategically significant.
Source
Source: https://www.wired.com/story/nvidia-becomes-major-model-maker-nemotron-3/