NVIDIA is giving away the most powerful AI for free: a strategy that generates billions
On June 4, 2026, NVIDIA released its largest artificial intelligence model, Nemotron 3 Ultra, to the public. The model weights, training data, and methodologies were published under a free license. This is not just charity, but a calculated move that allows the giant to earn more than its competitors do with paid access.
Unlike closed systems such as ChatGPT or Claude, Nemotron 3 Ultra can be downloaded, fine-tuned on your own data, and run on your own infrastructure. The bet here is not on maximum intelligence, but on openness, efficiency, and complete control over the model.
An Architecture That Breaks Stereotypes
Nemotron 3 Ultra is not just a scaled-up transformer. It is based on a hybrid architecture combining three approaches: Mamba-2 layers, Attention layers, and Latent Mixture of Experts (Latent MoE). Mamba-2 processes long texts quickly and efficiently—costs grow linearly, not exponentially. Attention layers, in turn, accurately retain large volumes of text in memory. Latent MoE compresses data before passing it to experts, allowing each to work narrowly and precisely without requiring unnecessary computations.
The model has approximately 550 billion parameters, but only about 55 billion are activated for processing each token. This allows it to think like a huge system while behaving, in terms of cost, like a much more compact one. With a context window of 1 million tokens and a speed exceeding 300 tokens per second, Nemotron 3 Ultra provides five to six times greater throughput and roughly 30% lower task costs compared to its counterparts.
NVIDIA's Strategy: The Ecosystem as the Main Asset
The main value of the release is not the model itself, but the ecosystem that NVIDIA is building around its hardware. The logic is simple: whoever runs Nemotron almost certainly does so on NVIDIA graphics cards, fine-tunes it using its software tools, and deploys it on its own software. Openness here is not charity, but a way to bring developers back to purchasing the company's hardware.
NVIDIA can afford this thanks to its incomparable financial capabilities. With a market capitalization exceeding $5 trillion, training Nemotron 3 Ultra, which likely cost hundreds of millions of dollars, is almost a negligible expense for the company. Graphics card sales more than cover the research, so NVIDIA can give the model away for free and still earn more than closed competitors do with paid access.
The political context adds extra weight to the release. An open American model can be inspected, modified, and run on your own servers—this makes it attractive for countries building independent national AI, from Europe to Southeast Asia. No one can remotely disable such a model, and this is especially valuable in light of recent restrictions surrounding closed models.
Where the Model Falls Short and What's Next
Despite all its advantages, Nemotron 3 Ultra is not the smartest model on the market. In the independent Artificial Analysis Intelligence Index ranking, it scored 48 points—the best result among open US models, but globally it lags behind leaders like Kimi K2.6 (54 points) and DeepSeek. Open models, according to analysts, trail closed ones by three to seven months.
But this gap matters less and less if the open model is simply sufficient for real-world tasks. A bank deploying Nemotron 3 Ultra to process loans on its own servers doesn't need flagship-level intelligence—it needs a model that can be fine-tuned on closed data, kept within its own secure perimeter, and not hand over confidential information to outsiders.
NVIDIA's bet on efficiency rather than test records may prove more farsighted. With mass AI adoption, the cost of running a model comes to the forefront, and one that is almost as smart but five times cheaper wins in real-world operation. Analysts expect the open ecosystem to only strengthen: NVIDIA has the resources, motivation, and distribution channels to release increasingly powerful open models faster than any other company.
Expert Opinion: NVIDIA's strategy is a classic example of "razor and blades," but on the scale of the entire AI market. By giving away the "razor" (the model) for free, the company ensures endless demand for the "blades" (its graphics cards and software). In the long term, this could lead to open models becoming the de facto standard for the corporate sector, leaving closed flagships only the niche of the most complex and expensive tasks.