NVIDIA gives away powerful AI for free — and earns more than its competitors from it
On June 4, 2026, NVIDIA released its largest AI model to date — Nemotron 3 Ultra — as open source. The model weights, training data, and training methodologies were published under a free license. This is not just another release; it is a strategic move that upends conventional ideas about monetizing artificial intelligence.
An Architecture That Changes the Game
Nemotron 3 Ultra is not a scaled-up transformer. It is based on a hybrid architecture combining Mamba-2 layers, an attention mechanism, and a latent mixture of experts (Latent MoE). Mamba-2 efficiently processes long sequences with linear cost growth, while Latent MoE compresses data before passing it to experts, allowing each to work narrowly and precisely. As a result, with a total of approximately 550 billion parameters, only about 55 billion are activated per token processed. This gives the model a context window of 1 million tokens and a speed of over 300 tokens per second, boosting throughput by 5-6 times and reducing task costs by about 30% compared to counterparts.
NVIDIA's Strategy: Betting on the Ecosystem
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 graphics cards, 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 — likely costing hundreds of millions of dollars — is a nearly negligible expense for NVIDIA. Graphics card sales more than cover research costs, so the company can give the model away for free and still earn more than closed competitors charging for access.
The political context also adds weight to the release. An open American model can be inspected, modified, and run on private servers — making it attractive for countries building independent national AI, from Europe to Southeast Asia. No one can remotely disable such a model, which is especially valuable in light of recent restrictions around closed models.
Weaknesses and Prospects
Despite its strengths, 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 lag behind closed ones by three to seven months.
However, 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 does not 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.
My view as an analyst: NVIDIA's bet on efficiency rather than test records may prove more farsighted. In mass AI adoption, the cost of running a model comes to the forefront. One that is nearly 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.