Three charts to understand NVIDIA GTC: The cheaper the compute power, the more you spend Last night at GTC 2026, Jensen Huang unveiled the Vera Rubin platform, claiming it delivers 10x the inference performance per watt compared to Blackwell, reduces inference token costs to one-tenth, and announced that combined orders for Blackwell and Vera Rubin are expected to surpass $1 trillion by 2027. Over the past two years, inference costs for GPT-4-level APIs have dropped 94%, from $36 per million tokens to less than $2. Intuitively, cheaper compute power should mean companies spend less, right? But the combined capital expenditures of the four cloud giants—Amazon, Alphabet, Meta, and Microsoft—have surged from $154 billion to $416 billion, nearly tripling. Jensen Huang’s trillion-dollar forecast isn’t just marketing hype; there’s a data-driven curve behind it :