Free AI from NVIDIA: How Nemotron 3 Ultra Turns Openness into a Goldmine
On June 4, 2026, NVIDIA released its most powerful model to date, Nemotron 3 Ultra, to the public. This is not just another release; it is a strategic move that upends the conventional business model of the artificial intelligence industry. Instead of selling access to a "superbrain," as competitors do, NVIDIA is handing out shovels and teaching people how to dig—but the gold ultimately ends up in its pocket.
Unlike closed giants like ChatGPT or Claude, Nemotron 3 Ultra is an open-weight model. You can download it, fine-tune it on your own data, and run it on your own infrastructure. The bet here is not on maximum intelligence, but on openness, efficiency, and control. This changes the rules of the game, especially for businesses that are not willing to entrust confidential data to third parties.
Architecture of the Future: A Hybrid That Works
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 layers process long texts quickly and efficiently: their costs grow linearly with length, rather than exponentially like the standard attention mechanism. Attention layers, in turn, accurately retain large volumes of text in memory. And Latent MoE compresses data before passing it to "specialists," allowing each of them to work narrowly and precisely without requiring additional computation.
The result is impressive: with a total of approximately 550 billion parameters, only about 55 billion are activated for processing each token. The model thinks like a huge system, but behaves like a much more compact one in terms of cost. A context window of 1 million tokens and a speed of over 300 tokens per second provide five to six times greater throughput and roughly 30% lower task costs compared to analogs.
NVIDIA's Strategy: Give Away Software, Sell Hardware
The main value of the release, in my assessment, lies not in the model itself, but in the ecosystem that NVIDIA is building around its hardware. The logic is simple: whoever runs Nemotron is almost certainly doing so on NVIDIA graphics cards, fine-tuning it with its software tools, and deploying it on its software. Openness here is not charity, but a way to lead developers back to purchasing the company's equipment.
NVIDIA can afford this because its financial capabilities are incomparable to the costs of the model itself. 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 away the model for free and still earn more than closed competitors charge for paid 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—this has made it attractive for countries building independent national AI, from Europe to Southeast Asia. Such a model cannot be remotely disabled, and this is especially valuable in light of recent restrictions surrounding closed models.
Weaknesses and Prospects
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 trails leaders like Kimi K2.6 (54 points) and DeepSeek. Open models, according to analysts, lag behind closed ones by three to seven months.
But this lag, in my opinion, 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 confidential data, kept within its own secure perimeter, and not hand over sensitive 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.
My conclusion: In the cryptocurrency and blockchain project market, where data confidentiality and decentralization are paramount, the emergence of powerful open AI models is a tectonic shift. Nemotron 3 Ultra paves the way for creating truly decentralized AI agents operating on their own nodes, without concern for censorship or data leaks. For DeFi protocols, for example, this means the ability to embed complex analytical models directly into smart contracts, without relying on centralized APIs. The market has not yet realized this, but the potential is colossal.