How Nvidia Became a Victim of Its Own Compute Market

Long the dominant force in the industry, Nvidia has experienced a rough stretch over the last two months. Bloomberg outlines the troubling details: the company’s stock price has dropped 15% from its May peak, even as projected revenue continues to climb. When measured against expected earnings, Nvidia is now trading at a discount relative to the S&P 500 average. Investors are currently paying less per dollar of Nvidia’s anticipated profit than they would for a typical large American corporation.

Money continues to pour into AI infrastructure stocks, but the flow is increasingly directed toward memory companies. Over the same period, Micron, a leading producer of DRAM (the standard memory chip found in computers and servers), has nearly tripled in value. This shift positions memory as the new bottleneck for data centers and the hottest AI trade. The core reason is straightforward: the GPU shortage that seemed alarming last year has eased somewhat. Meanwhile, data centers are consuming memory at an unprecedented rate.

For those who admire Nvidia’s technological achievements, this trend can feel deflating. The company’s rise was powered by genuinely impressive innovation, from developing CUDA, its widely adopted programming platform that made Nvidia GPUs the default engine for AI research, to accelerating GPU development at a pace few thought possible. Nvidia’s success is the kind of story that fills books, and its GPUs are among the most complex devices ever created, operating at the cutting edge of human capability.

For memory companies like Micron, the narrative is far simpler. They produce high-bandwidth memory chips, specialized components designed to shuttle data in and out of processors as quickly as possible. These chips have improved incrementally over the past two decades. Without major changes to the technology or the companies themselves, the service they provide suddenly became extremely valuable. Since demand is outpacing supply growth, they have been able to raise prices tenfold over the past year.

According to Datatrack, the spot price for DRAM, which reflects what buyers pay on the open market rather than under long-term contracts, has risen sharply since 2023. You might assume a major technical breakthrough occurred in the summer of 2025, but that is not the case. The industry simply underestimated how much memory the data center buildout would require.

In contrast, data from the compute market Ornn shows how the spot price for an hour of time on an Nvidia H100 GPU has changed over the last year. Like Nvidia’s stock price, it peaked in May at around $3.20 per hour and has since declined steadily. For better or worse, Nvidia’s value is tied to the price of compute, and that price is falling. Micron and its peers are tied to the price of DRAM, which keeps rising.

When I spoke with Ornn co-founder and CTO Wayne Nelms about the forces behind this disparity, he described it as a simple matter of supply and demand. Google, Amazon, Microsoft, and even OpenAI have launched their own custom processors to reduce reliance on Nvidia. Even if these chips are not as powerful as Nvidia’s latest models, they are good enough to drive down the price of compute.

“More GPU and accelerator players are entering the market. Everyone wants to make their own silicon, but no one is making their own DRAM,” Nelms told me. “Until there’s a major technological breakthrough on HBM, a shift in supply and demand, or someone new enters the memory market, I think things will more or less persist as we see today.”

This is a frustrating situation for Nvidia, and largely a product of its own success. By proving how valuable compute can be, the company now finds itself at the center of a market everyone wants to enter. Meanwhile, simpler technologies and less interesting companies are getting rich on the sidelines.