NVIDIA is giving away powerful AI for free and making more money than its competitors.
On June 4, 2026, NVIDIA released Nemotron 3 Ultra, the largest open AI model in the Nemotron 3 lineup. This is not just a release of weights: the company has made the training data and training methodologies publicly available under a free license. The model is designed for long-running autonomous agents and complex reasoning. And this is not charity, but a subtle strategic move.
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.
Architecture: A Hybrid That Changes the Game
At the core of Nemotron 3 Ultra is 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 with length, rather than explosively 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 experts, forcing each to work narrowly and precisely without unnecessary computation.
The result: the model has around 550 billion parameters, but only about 55 billion are activated for processing each token. This allows it to think like a massive system while behaving cost-wise like a much more compact one. With a context window of 1 million tokens and a speed exceeding 300 tokens per second, this yields five to six times greater throughput and approximately 30% lower task costs.
NVIDIA's Strategy: 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 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 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.
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 rating, 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 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 private data, kept within its secure perimeter, and not share confidential information with outsiders.
My 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 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.