NVIDIA is giving away powerful AI for free — and making more money than its competitors from it
On June 4, 2026, NVIDIA released its flagship model, Nemotron 3 Ultra, the largest open AI model in the Nemotron 3 line, to the public. The release includes model weights, training data, and training methods distributed under a free license. This is not just another model—it is a strategic move that turns the rules of the AI market upside down.
Unlike closed systems like 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 full control over the model. This changes the approach to AI adoption in the corporate sector.
Architecture: A Hybrid That Works More Efficiently
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 cost-effectively: costs grow linearly with length, rather than exploding as in conventional attention mechanisms. 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 unnecessary computations.
The model has approximately 550 billion parameters in total, but only about 55 billion are used to process each token. This allows it to think like a massive system while behaving cost-wise like a much more compact one. Combined with a context window of 1 million tokens and a speed of over 300 tokens per second, this results in five to six times greater throughput and roughly 30% lower task costs compared to analogs.
NVIDIA's Strategy: The Ecosystem as the Main Asset
The main value of the release, according to analysts, 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. Openness here is not charity, but a way to bring developers back to purchasing the company's hardware.
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 research, so NVIDIA can give the model away 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 to 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 around 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 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 gap, 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 closed data, kept within its own secure perimeter, and not share confidential information with outsiders.
NVIDIA's bet on efficiency rather than test records may prove more farsighted. In mass AI adoption, the cost of running the 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: This release is not just a technological breakthrough, but a brilliant business move. NVIDIA is turning AI development from an arms race into a hardware subscription market. The free model is bait that ensures demand for graphics cards for years to come, and in the long term, this strategy could prove far more profitable than selling access to the smartest model.