NVIDIA is giving away powerful AI for free: a clever move that brings in billions
On June 4, 2026, NVIDIA released Nemotron 3 Ultra, the largest open-source AI model in the Nemotron 3 lineup. The company made not only the model weights publicly available, but also the training data and methodologies. This is not charity, but a well-thought-out strategy that is already bringing NVIDIA more revenue than closed competitors earn from paid access.
Unlike flagship models 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.
Architecture: A Hybrid That Hits Competitors in the Wallet
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, not exponentially like with 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 unnecessary computations.
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 context window of 1 million tokens and a speed of over 300 tokens per second, this results in five to six times greater throughput and roughly 30% lower task costs.
Strategy: Give Away Shovels to Sell Gold
The main value of the release is not the model itself, but the ecosystem NVIDIA is building around its hardware. The logic is simple: anyone running Nemotron is almost certainly doing so on NVIDIA graphics cards, fine-tuning it with its software tools, and deploying it on its software stack.
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 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 to countries building independent national AI, from Europe to Southeast Asia. Such a model cannot be remotely disabled, which is especially valuable given recent restrictions surrounding closed models.
Weaknesses and Prospects
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 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 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 share confidential information with 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 grow stronger: NVIDIA has the resources, motivation, and distribution channels to release increasingly powerful open models faster than any other company.