NVIDIA is giving away an AI giant for free: a strategy that brings in billions
On June 4, 2026, NVIDIA released Nemotron 3 Ultra, its largest and most advanced open-source AI model. This is not just another release, but a strategic move that changes the rules of the game in the AI market. The company has made not only the model weights publicly available, but also the training data and training methodologies — all under a free license.
Unlike closed giants 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.
An Architecture That Breaks the Mold
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 efficiently: costs grow linearly, not exponentially like standard attention. Attention, in turn, accurately retains 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 computations.
The result: the model has around 550 billion parameters, but only about 55 billion are activated for processing each token. This provides five to six times greater throughput and roughly 30% lower task costs. A context window of 1 million tokens and a speed of over 300 tokens per second make it a powerful tool for long-running autonomous agents and complex reasoning.
NVIDIA's Strategy: Free, but Profitable
The main value of the release is not the model itself, but the ecosystem NVIDIA is building around its hardware. The logic is simple: whoever runs Nemotron almost certainly does so on NVIDIA GPUs, fine-tunes it using its 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.
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 do with paid access.
The political context adds further weight to the release. An open American model can be inspected, modified, and run on your own servers — making it attractive for countries building independent national AI, from Europe to Southeast Asia. No one can remotely disable such a model, and this is especially valuable in light of recent restrictions surrounding closed models.
Where the Model Falls Short and What's Next
For all its merits, 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.
But this gap matters less and less if an open model is simply good enough 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 a secure perimeter, and not hand over confidential information to outsiders.
Analytical conclusion: 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. One that is almost as smart but five times cheaper wins in real-world operation. NVIDIA has the resources, motivation, and distribution channels to release increasingly powerful open models faster than any other company. The ecosystem will only grow stronger.