Nvidia’s Jensen Huang says AI may need a billion times more compute

Nvidia CEO Jensen Huang has a new number for the AI crowd, and it has a lot of zeros. He says AI may soon require a billion times more computing power for the problem-solving methods that run on GPUs. From chatbots to reasoning machines Huang’s argument rests on a shift in how AI works. Early large language models mostly predicted the next word in a sentence, fast and in a single pass. Newer reasoning and agentic systems behave differently. They break problems into steps, check their own work, and sometimes take actions on a user’s behalf. Huang has been building this case for a while. At Nvidia’s GPU Technology Conference (GTC) in March 2025, he said reasoning and agentic AI need at least 100 times more computation than previous models. By GTC 2026, the estimate had grown considerably. Huang said computing demand had spiked roughly 1 million times over a two-year span. The billion-times figure is the furthest point on that curve. In scenarios Huang has presented, advanced reasoning AI could potentially need up to 1 billion times more computation than earlier models to reach full reasoning capability. Nvidia’s answer: Vera Rubin and a trillion-dollar pitch Nvidia’s next-generation ...