NVIDIA is giving away the most powerful AI for free: a brilliant move that brings in billions
On June 4, 2026, NVIDIA released its largest model to date, Nemotron 3 Ultra, to the public. Under a free license, the weights, training data, and training methodologies were published. This is not charity, but a well-thought-out business strategy that allows the company to earn more than closed competitors like OpenAI or Anthropic.
Architecture: A Hybrid That Changes the Game
Nemotron 3 Ultra is not just an "upscaled transformer." It is based on a unique hybrid architecture combining three approaches: Mamba-2 layers, classic attention, and Latent Mixture of Experts (Latent MoE).
Mamba-2 layers process long texts quickly and efficiently: their costs grow linearly, not exponentially like the standard attention mechanism. Attention layers, in turn, accurately retain large volumes of context in memory. And Latent MoE compresses data before passing it to experts, forcing each to work narrowly and precisely, without 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 giant system while behaving like a much more compact one in terms of cost. With a context window of 1 million tokens and a speed exceeding 300 tokens per second, this provides 5-6 times greater throughput and roughly 30% lower task costs.
Strategy: Not a Model, but an Ecosystem
The main value of Nemotron 3 Ultra lies not in the model itself, but in the ecosystem 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 software.
With a market capitalization exceeding $5 trillion, training Nemotron 3 Ultra, which likely cost hundreds of millions of dollars, is a nearly 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 charging for access.
The political context adds further weight to the release. An open American model can be inspected, modified, and run on one's own servers—making it attractive for countries building independent national AI, from Europe to Southeast Asia. Such a model cannot be remotely disabled, which is especially valuable in light of recent restrictions surrounding closed models.
Limitations and Prospects
Despite all its advantages, Nemotron 3 Ultra is not the smartest model on the market. In the independent Artificial Analysis Intelligence Index, it scored 48 points—the best result among open US models, but trailing leaders like Kimi K2.6 (54 points) and DeepSeek. Open models, according to analysts, lag behind closed ones by three to seven months.
However, this lag matters less and less if an 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 proprietary data, kept within its secure perimeter, and not share confidential information with outsiders.
Expert opinion: NVIDIA's bet on efficiency rather than test records may prove more far-sighted than it seems. 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 deployment. The open ecosystem will only strengthen: NVIDIA has the resources, motivation, and distribution channels to release increasingly powerful open models faster than any other company.