NVIDIA is giving away powerful AI for free — and making more money than its competitors
On June 4, 2026, NVIDIA released the Nemotron 3 Ultra, the largest open-source AI model in the Nemotron 3 lineup. The company made the model weights, training data, and training methodologies publicly available under a free license. The model is designed for long-running autonomous agents and complex reasoning.
Unlike closed-source flagships 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 over the model.
What Makes the Model's Architecture Special
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 with length, rather than exponentially. Attention layers precisely retain large volumes of text in memory. Latent MoE compresses data before passing it to experts, allowing each expert to work narrowly and accurately without requiring additional computation.
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 exceeding 300 tokens per second, this results in five to six times greater throughput and roughly 30% lower task costs.
NVIDIA's Strategy and Bet on the Ecosystem
According to industry analysts, 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 GPUs, fine-tunes it using NVIDIA's software tools, and deploys it on NVIDIA's software. Openness here is not charity, but a way to steer developers back towards purchasing the company's hardware.
NVIDIA can afford this because its financial resources 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. GPU sales more than cover the research, allowing NVIDIA to give the model away for free and still earn more than closed-source 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 private servers — making it attractive for countries building independent national AI, from Europe to Southeast Asia. Such a model cannot be remotely disabled, which is especially valuable in light of recent restrictions surrounding closed models.
Where the Model Falls Short and What's Next
Despite 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-source US models, but globally it trails leaders like Kimi K2.6 (54 points) and DeepSeek. Analysts estimate that open-source models lag behind closed-source ones by three to seven months.
However, in my opinion, this gap matters less and less if an 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 expose confidential information to third parties.
NVIDIA's bet on efficiency, rather than test records, may prove more forward-thinking. In mass AI adoption, the operational cost of a model takes center stage, and one that is nearly as capable but five times cheaper wins in real-world deployment. 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: NVIDIA is using the open model as a Trojan horse for its infrastructure. While competitors measure test scores, the company is cementing its control over the hardware that will power enterprise AI. This is not an algorithm race — it's a platform war.