NVIDIA is giving away the most powerful AI for free: a strategy that generates billions
On June 4, 2026, NVIDIA released the Nemotron 3 Ultra — the largest open AI model in the Nemotron 3 lineup. Not only the model weights, but also the training data and training methodologies were made publicly available under a free license. This is not merely a "gesture of goodwill" — it is a calculated move that transforms the semiconductor industry giant into an even more dominant player in the artificial intelligence market.
An Architecture That Breaks Efficiency Records
The 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, rather than explosively like the standard attention mechanism. Attention layers accurately retain large volumes of text in memory. And Latent MoE compresses data before passing it to "experts," allowing each to work narrowly and precisely without requiring additional computations.
The result: the model has approximately 550 billion parameters, but only about 55 billion are activated per token processed. With a context window of 1 million tokens and a speed exceeding 300 tokens per second, this yields 5-6 times greater throughput and roughly 30% lower task costs compared to analogs.
NVIDIA's Strategy: Openness as a Weapon
The main value of the release 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. With a market capitalization exceeding $5 trillion, training the Nemotron 3 Ultra, which likely cost hundreds of millions of dollars, is nearly a negligible expense for the company. Graphics card sales more than cover research costs, so NVIDIA can give away the model for free and still earn more than closed competitors charge for paid access.
The political context adds extra 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. No one can remotely disable such a model, and this is especially valuable amid recent restrictions surrounding closed models.
Where the Model Falls Short and What's Next
Despite all its advantages, the 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 trails leaders like Kimi K2.6 (54 points) and DeepSeek. According to analysts, open models lag behind closed ones by three to seven months.
But this lag 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 does not 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 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 nearly as smart but five times cheaper wins in real-world deployment. The open ecosystem will only strengthen: NVIDIA has the resources, motivation, and distribution channels to release increasingly powerful open models faster than any other company. The AI market is changing the rules of the game, and NVIDIA is playing by its own.