Nvidia's latest earnings announcement on Wednesday once again followed a familiar script: After weeks of nervous anticipation, Nvidia delivered results that beat expectations, CEO Jensen Huang reaffirmed his bullish outlook on AI and Nvidia's role in the AI buildout, and Wall Street breathed a collective sigh of relief. And yet, despite another round of record-breaking results, investors were somehow left unimpressed. On Thursday, Nvidia's share price dropped almost 2 percent, which is also something we've seen before.
On paper, there were no reasons to be down about Nvidia's latest result – in fact, the company’s growth accelerated once more and will pick up even more momentum in the current quarter, according to Nvidia’s outlook for the second quarter of its fiscal year 2027. In the three months ended April 26, Nvidia’s revenue grew 85 percent from the same period last year, reaching $81.6 billion and beating its own forecast of $78 billion as well as analyst expectations.
Once again, Nvidia's data center business was at the heart of the company's record-breaking quarter, as it saw a 92-percent increase in revenue versus a year ago and accounted for more than 90 percent of total sales. Net income more than tripled to $58 billion, putting Nvidia on track to become the first company to surpass $200 billion in annual profit. For the current quarter, Nvidia expects revenue of $91 billion, which would bring its growth rate to 95 percent – another increase from this quarter’s 85-percent growth.
In his comments accompanying the earnings release, Nvidia CEO Jensen Huang didn't temper his optimism for the AI landscape and his company's role in it. "The buildout of AI factories - the largest infrastructure expansion in human history - is accelerating at extraordinary speed," Huang said. "Agentic AI has arrived, doing productive work, generating real value and scaling rapidly across companies and industries. Nvidia is uniquely positioned at the center of this transformation as the only platform that runs in every cloud, powers every frontier and open source model, and scales everywhere AI is produced - from hyperscale data centers to the edge."
