Nvidia Corp. NVDA-Q on Wednesday overshot Wall Street estimates as its profit skyrocketed, bolstered by the chip-making dominance that has made the company an icon of the artificial-intelligence boom.
Its net income rose more than sevenfold compared with a year earlier, jumping to US$14.88-billion in its first quarter that ended April 28 from US$2.04-billion a year earlier. Revenue more than tripled, rising to US$26.04-billion from US$7.19-billion in the previous year.
The company reported earnings per share adjusted to exclude one-time items of US$6.12, well above the US$5.60 Wall Street analysts had expected, according to FactSet. It also announced a 10-for-1 stock split, a move that it noted will make its shares more accessible to employees and investors.
And it increased its dividend to 10 U.S. cents a share from four U.S. cents.
Shares in Nvidia rose more than 4 per cent in after-hours trading to US$991.85. The stock has risen more than 200 per cent in the past year.
The company, based in Santa Clara, Calif., carved out an early lead in the hardware and software needed to tailor its technology to AI applications, partly because founder and chief executive officer Jensen Huang began to nudge the company into what was then seen as a still half-baked technology more than a decade ago. It also makes chips for gaming and cars.
The company now boasts the third-highest market value on Wall Street, behind only Microsoft and Apple.
“Nvidia defies gravity again,” Jacob Bourne, an analyst with Emarketer, said of the quarterly report. While many tech companies are eager to reduce their dependence on Nvidia, which has achieved a level of hardware dominance in AI rivalling that of earlier computing pioneers such as Intel Corp., “they’re not quite there yet,” he added.
Demand for generative AI systems that can compose documents, make images and serve as increasingly lifelike personal assistants has fuelled astronomical sales of Nvidia’s specialized AI chips over the past year. Tech giants Amazon, Google, Meta and Microsoft have all signalled they will need to spend more in coming months on the chips and data centres needed to train and operate their AI systems.