With fears swirling about an AI bubble, many were watching Nvidia’s rundown of its quarterly performance with bated breath—even more so than usual.
Sales of the company’s chips not only serve as a temperature check on AI fever but also a read on the market’s health as a whole, given that AI spending now accounts for a growing chunk of the country’s economic growth.
All the heightened stakes didn’t yield anything too dramatic, though: In a somewhat familiar arc, the world’s most valuable company narrowly beat most analyst consensus estimates for its Q2 performance, while its stock dipped slightly, partly due to just how inflated expectations already were.
Nvidia said it made $46.7 billion in the quarter that ended in late July, up 6% from Q1 and 56% YoY. An LSEG analyst poll had expected around $46 billion, according to CNBC. The company predicted that it’ll pull in $54 billion during the current quarter, above the $53.1 billion analyst estimate.
But there were also some weaker spots in the report. Data center revenue came in below analyst expectations—$41.1 billion versus $41.2 billion predicted—due in part to a lack of sales of its H20 chips in China, CFO Colette Kress said in an earnings call. The sequential revenue growth was also the lowest the company has reported in two years.
Nvidia’s stock dipped up to 4% in after-hours trading on Wednesday, but was more or less flat by Thursday morning.
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Big spenders: It helps that many of Nvidia’s biggest customers had already affirmed that they continued to spend big on building data centers last quarter and would continue to do so in the current one. Kress said in the call that Nvidia expects companies to spend $3 trillion to $4 trillion on AI infrastructure by the end of the decade.
“The capex of just the top four hyperscalers has doubled in two years as the AI revolution went into full steam. As the AI race is now on, the capex spend has doubled to $600 billion per year,” CEO Jensen Huang said in response to an analyst question about that prediction. “There’s five years between now and the end of the decade, and $600 billion only represents the top four hyperscalers. We still have the rest of the enterprise companies building on [premises]. You have cloud service providers building around the world.”
Bubble brewing? But investors and analysts have begun to fret about a potential AI bubble burst, as they have periodically over the past few years. Muted reactions to OpenAI’s GPT-5 have raised the possibility of slowing research progress. An MIT report found that 95% of enterprise GenAI pilots fail. OpenAI CEO Sam Altman recently warned of a bubble.
Nvidia’s performance didn’t necessarily add to these anxieties, but it’s not clear it was strong enough to put them to bed either.