One of the most anticipated earnings announcements of the summer dropped yesterday—and Nvidia has booked yet another quarter of stratospheric growth. The company posted record quarterly revenues of $30 billion, up 122% from a year before, and 15% higher than the record breaking last quarter.
Almost all of that revenue (some $26.3 billion) came from its data center business, which was up 154% year-on-year. “Nvidia achieved record revenues as global data centers are in full throttle to modernize the entire computing stack with accelerated computing and generative AI,” said Nvidia CEO Jensen Huang in a statement accompanying the results.
Nvidia’s continued success is owed to sales of its graphics processing units, computer chips that are powering today’s AI models. Its $30,000 H100 is the market-leading chip, while the cheaper A100 GPU costs around $8,000.
Nvidia’s results outstripped most analysts’ forecasts, which expected around $28.6 billion of revenue in the quarter. Yet market watchers—and the wider economy, which is responding to the buoyancy of Nvidia—were split. After-hours traders caused the stock price to fall more than 6% as Nvidia chief financial officer Colette Kress closed her preprepared statement on the firm’s earning call.
“The stock is getting pummeled because it turns out when you get the market used to having these ridiculous revenue multipliers quarter-over-quarter, the market gets upset when you don’t keep doing it,” says the podcaster and financial commentator Ed Zitron. “$30 billion of revenue—$16.59 billion of profit—is huge, but not when you’ve accelerated your revenue so dramatically.”
That uncertainty matters, because—like it or not—Nvidia plays a central role in our economy. Dan Ives, managing director and senior equity research analyst at Wedbush Securities, says that Nvidia’s performance is uniquely responsible for the wider generative AI revolution, in large part because of its integral role in the supply of GPUs. (According to estimates by Morgan Stanley researchers, Nvidia’s demand for leading-edge semiconductor wafers is so great that it accounts for half the whole global market this year.)
Nvidia is also the largest consumer of HBM memory chips, whose low power consumption and wide communication lanes are useful for GPUs, the Morgan Stanley researchers add. Nvidia believes it’s likely to see even greater performance in the rest of the year, forecasting third quarter revenue of $32 billion, while also expecting billions of dollars from its proprietary Blackwell computer architecture that helps chips run AI systems more smoothly.
The forecast success of Blackwell was enough for Rick Schafer, managing director and senior analyst at Oppenheimer, to maintain his “outperform” rating for Nvidia, despite the stock market response. “We see Nvidia best positioned in AI, benefiting from full-stack AI hardware/software,” he wrote yesterday.
Ives, for his part, believes Nvidia’s performance is “a big piece of the [economic] puzzle” that is responsible for the success of tech stocks more widely. And given that the Magnificent Seven tech firms (a group that includes Nvidia) account for around a third of the entire value of the S&P 500—double the proportion it was a decade ago—success for the chipmaker means success for the wider economy.
In fact, Ives believes that every dollar spent on an Nvidia GPU has a wider halo effect of around $8 to $10 on the wider tech sector, which he says “speaks to our firmly bullish view of tech stocks over the next year.”
But that concentration of market power worries others—not least because it’s not clear whether the company is leading with a good example. “Nvidia has yet to share a single life cycle analysis for any of their products,” says Sasha Luccioni, a researcher in ethical and sustainable AI at Hugging Face, “so we don’t know how much water, energy, and rare earth metals are going into these things.”
And on the flip side, while success for Nvidia means success for the wider economy, failure or stumbles have the same wider effect. The notion that Nvidia could be the face of a tech bubble with echoes of the dotcom boom raises a red flag for some analysts, not least because a good number of the early use cases for generative AI have yet to come to fruition.
“The problem is that there is a fundamental anxiety about this company based on the fact its growth is sustained by interest in generative AI,” says Zitron.
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