NVIDIA is giving away powerful AI for free: a strategy that generates billions
On June 4, 2026, NVIDIA released the Nemotron 3 Ultra — the largest open model in the Nemotron 3 line. This is not just about publishing weights: the company has made training data and training methodologies publicly available under a free license. The model is designed for long-lived autonomous agents and complex reasoning chains.
Unlike closed flagships such as 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.
Architecture: A Hybrid Breakthrough
Nemotron 3 Ultra is not just a "scaled-up transformer." It is based on a hybrid architecture of three components: 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 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.
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. A context window of 1 million tokens and a speed of over 300 tokens per second provide five to six times greater throughput and roughly 30% lower task costs.
NVIDIA's Strategy: Giveaway as a Business Model
The main value of the release, according to industry analysts, 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 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 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, it scored 48 points — the best result among open US models, but globally it lags behind leaders such as Kimi K2.6 (54 points) and DeepSeek. Open models, according to analysts, trail closed ones by three to seven months.
But this lag, in my opinion, 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 expose confidential information to outsiders.
NVIDIA's bet on efficiency rather than test records may prove more far-sighted. 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.
Expert Opinion: While the industry chases test records, NVIDIA is quietly turning open models into a tool for monopolizing infrastructure. Giving away "free" AI is not altruism, but the most effective way to make the world pay for hardware. In the long run, this strategy may prove more profitable than selling subscriptions to closed models.