NVIDIA is giving away a powerful AI for free — and making more money from it than competitors do from paid models
On June 4, 2026, NVIDIA released Nemotron 3 Ultra, the largest open-source AI model in the Nemotron 3 line. Weights, training data, and training methodologies were released to the public under a permissive license. The model is designed for long-running autonomous agents and complex reasoning.
Unlike closed flagships 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 control over the model.
Model Architecture: Three in One
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: 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. Latent MoE compresses data before passing it to the experts, allowing each expert to work narrowly and precisely without requiring additional computation.
The model has approximately 550 billion parameters in total, but only about 55 billion are activated for processing each token. This allows it to think like a massive system while behaving like a much more compact one in terms of cost. Combined with a 1 million token context window and a speed of over 300 tokens per second, this results in five to six times greater throughput and roughly 30% lower task costs.
NVIDIA's Strategy: Betting on the Ecosystem
The main value of the release, according to industry analysts, lies not in the model itself, but in the ecosystem NVIDIA is building around its hardware. The logic is simple: whoever runs Nemotron is almost certainly doing so on NVIDIA GPUs, fine-tuning it with NVIDIA's software tools, and deploying it on NVIDIA's software. Openness here is not charity, but a way to guide developers back to purchasing the company's hardware.
NVIDIA can afford this because its financial resources 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. GPU sales more than cover the 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—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.
Where the Model Falls Short and What's Next
Despite its strengths, 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 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 for loan processing 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 expose confidential information to outsiders.
My analysis: NVIDIA's bet on efficiency rather than benchmark records may prove more farsighted. With mass AI adoption, the operational cost of a model takes center stage, and one that is nearly as smart but five times cheaper wins in real-world deployment. 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.