Nvidia, which makes the microchips that power most artificial intelligence applications, began its extraordinary rise a year ago.
Buoyed by an explosion of interest in AI, the Silicon Valley company announced last May that it expected its chip sales to soar. In fact, that's exactly what happened. And the excitement hasn't stopped, with NVIDIA continuing to raise its revenue forecasts every few months. The company's stock price has soared, and its market capitalization has surpassed $2 trillion, making it more valuable than Google's parent company, Alphabet.
Nvidia reported another surge in revenue and profit on Wednesday, underscoring how the company remains a clear winner in the AI boom even as it struggles with inflated expectations and increasing competition.
Sales for the three months through April were $26 billion, beating the $24 billion forecast in February and marking the third consecutive quarter in which sales tripled from a year ago. Net income jumped sevenfold to $5.98 billion.
Nvidia also forecast revenue of $28 billion for the current quarter ending in July, more than double the revenue from the same period a year ago and above Wall Street expectations.
“We are poised for our next wave of growth,” Nvidia CEO Jensen Hwang said in a statement.
The 2x rather than 3x revenue likely reflects the surge in AI chip sales that began to change Nvidia's performance a year ago. These growth rates are expected to slow now that initial increases have made year-over-year comparisons tougher.
Nvidia's stock price, which has risen more than 90% this year, rose in after-hours trading after the company announced its earnings results. The company also announced a 10-for-1 stock split.
Nvidia, which originally sold chips for rendering images in video games, has profited after making big early bets to adapt its graphics processing units (GPUs) for other computing tasks. More than a decade ago, when AI researchers began using the chips to speed up tasks such as recognizing objects in photos, Mr. Huang jumped at the opportunity. He has extended Nvidia's chips for AI tasks and developed software to help advance the field.
The company's flagship processor, the H100, is in enthusiastic demand for powering AI chatbots such as OpenAI's ChatGPT. While most high-end standard processors cost a few thousand dollars, the H100 sells for between $15,000 and $40,000 each, depending on sales volume and other factors, analysts said.
Analysts are discussing the potential impact of the H100's powerful successor, codenamed Blackwell, which was announced in March and early models are expected to start arriving in the fall.
Demand for the new chips already appears strong, raising the possibility that some customers will forgo the H100 and wait for faster models. But there were few signs of such slowdown in Nvidia's latest results.
Wall Street analysts are also looking for signs that some well-funded rival could grab a significant share of Nvidia's business. Microsoft, Meta, Google and Amazon are all developing their own chips that can be customized for AI work, but they also say they are increasing their purchases of Nvidia chips.
Traditional rivals like Advanced Micro Devices and Intel are also making optimistic predictions for their own AI chips: AMD said it expects to sell $4 billion worth of its new MI300 AI processor this year.
Huang frequently points to this as a sustainable benefit. Customers don't have to worry about being locked into using that GPU, as it's the only one offered by all major cloud services such as Amazon Web Services and Microsoft Azure. Our unique chip technology provides superior service.
Nvidia also remains popular among computer makers that have long used the company's chips in their systems, including Dell Technologies, which hosted an event in Las Vegas on Monday where Huang also appeared.
Michael Dell, Dell's CEO and founder, said the company plans to offer a new data center system with 72 new Blackwell chips in a standard-built computer rack slightly taller than a refrigerator. Ta.
“Don't tempt me with that,” Huang joked. “That would make me really excited.”