Crypto news

On June 4, 2026, NVIDIA released Nemotron 3 Ultra — the largest open AI model in its lineup, making weights, training data, and methodologies publicly available under a free license. This is not just "another model," but a strategic move that upends the rules of the game in the artificial intelligence market.

Unlike closed giants such as ChatGPT or Claude, Nemotron 3 Ultra can be downloaded, fine-tuned on proprietary data, and run on your own infrastructure. The bet here is not on maximum intelligence, but on openness, efficiency, and control.

Architecture: Why Nemotron 3 Ultra is Faster and Cheaper

At the core of Nemotron 3 Ultra lies 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 economically — costs grow linearly, not exponentially. Attention layers precisely retain large volumes of text in memory. And Latent MoE compresses data before passing it to experts, forcing each to work narrowly and accurately.

The model has approximately 550 billion parameters, but only about 55 billion are activated for processing each token. This yields five to six times higher throughput and roughly 30% lower task costs. A context window of 1 million tokens and a speed exceeding 300 tokens per second are metrics that make it one of the most efficient on the market.

Strategy: Give Away the Model, Sell the Shovels

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 GPUs, 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 Nemotron 3 Ultra, which likely cost hundreds of millions of dollars, is a nearly negligible expense for NVIDIA. GPU sales more than cover research costs, so the company can give away the model for free and still earn more than closed competitors charging for access.

The release gains additional weight from the political context: an open American model can be inspected, modified, and run on private 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 Comes Next

Despite all its advantages, Nemotron 3 Ultra is not the smartest model on the market. On the Artificial Analysis Intelligence Index, it scored 48 points — the best result among open U.S. 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 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 proprietary data, kept within a secure perimeter, and not share confidential information with outsiders.

My analysis: NVIDIA's bet on efficiency rather than benchmark records may prove more farsighted. 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. NVIDIA has the resources, motivation, and distribution channels to release increasingly powerful open models faster than any other company. This is not philanthropy — it is the most elegant way to monopolize the market.