The Real Threat to AI Stocks Is the Collapse of Compute Prices

Today, Wall Street is obsessed with a question: “Where is the money from AI?” Analysts are meticulously calculating return on investment (ROI), studying the revenue from subscriptions, and doubting whether software companies will be able to monetize the gigantic capital expenses that Big Tech is pouring into infrastructure. In my opinion, though, there is another…


The Real Threat to AI Stocks Is the Collapse of Compute Prices

Today, Wall Street is obsessed with a question: “Where is the money from AI?” Analysts are meticulously calculating return on investment (ROI), studying the revenue from subscriptions, and doubting whether software companies will be able to monetize the gigantic capital expenses that Big Tech is pouring into infrastructure.

In my opinion, though, there is another question to ask. The real threat to the tech sector — and the whole U.S. stock market — is not hiding in a deficit of ideas for AI monetization but in a classic economic shock: a crisis of computing power overproduction. Investors are used to thinking that the GPU shortage will last forever. But the flywheel of the investment cycle is already launched, and the reverse countdown has begun.

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The Anatomy of Demand and Supply

In 2023 and 2024, this industry faced a harsh bottleneck. Chips were in short supply, cloud giants stood in queues, and rental rates for flagship Nvidia (NVDA) H100 GPUs peaked near $8 an hour. The logic of businesses back then was simple: Grab any accessible capacity no matter the price. An unprecedented building boom began in response to this shortage. Hyperscalers — Microsoft (MSFT), Amazon (AMZN), Alphabet (GOOGL) — and hundreds of other companies began to build data centers in huge volumes.

This is where the time lag plays out. Data centers, which began to be built in 2024 and 2025, are coming online right now in a big way. They’re also hitting the market simultaneously with chips from the latest generations, such as the Blackwell (B200) architecture, which is multiple times more efficient than its predecessors.

Oversupply has already begun to corrode unit economics. As fresh academic research on the dynamics of the cloud market shows, spot rates for once-scarce H100 chips at specialized providers have already collapsed to $1.49 to $1.99 an hour, while AWS has been forced to conduct an aggressive lowering of prices.

Paradox of Demand: Teraflops Against Dollars

We should clarify that there is a difference between the physical and monetary volume of demand. Demand in teraflops — the volume of calculations — will continue to grow exponentially since humanity needs more and more neural networks, video generation, and data processing. The demand in dollars, however — the revenue of providers — could differ and show another dynamic.

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