Nvidia now controls an estimated 74% of the AI inference chip market, up from 66%. That’s not a rounding error. That’s a company pulling away from the pack in what may be the most consequential hardware race of the decade.
The distinction matters because inference, the process of running trained AI models in real time, is where the money is shifting. Training a model is a one-time expense. Running it for millions of users, every second of every day, is the recurring cost that keeps CTOs up at night.
Why inference is eating the AI budget
The broader AI inference market is estimated somewhere between $76 billion and over $100 billion for the 2025-2026 period. Analysts project compound annual growth rates between 12% and 19% stretching through the end of the decade and beyond.
At GTC 2026 in March, Nvidia raised its own revenue forecast for AI chips to at least $1 trillion in cumulative opportunity through 2027. That figure was up from $500 billion through 2026.
