Nvidia CFO says about half of its data center business comes from customers beyond hyperscalers

Good morning.

Nvidia just handed AI bubble skeptics their toughest rebuttal yet.

Tech giant Nvidia reported its fiscal second quarter earnings on Wednesday, with revenue of $96.2 billion, up 106% year over year and above analyst estimates.

Non-GAAP EPS came in at $2.22, while Data Center revenue reached $89.0 billion, up 117% year over year.

The company also issued Q3 guidance of $105.8–$110.1 billion and forecast fiscal 2028 annual sales to increase 70% from the prior year.

“Demand is accelerating,” Jensen Huang, founder and CEO of Nvidia, said in a statement.

The results reignited debate over whether AI spending is sustainable and gave both bulls and Nvidia itself new evidence for continued growth.

“This was a masterpiece quarter with stunning guidance that speaks to the massive demand Nvidia is seeing in the AI Revolution,” Dan Ives, partner and senior managing director at Yorkville Ives, told me.

“The guidance for next quarter was well ahead of whisper numbers, and this will be a spark that is a boost for tech stocks and the broader sector.” During the earnings call, CFO Colette Kress offered a data-driven rebuttal to the AI-bubble narrative.

Rather than simply asserting that demand is durable, Kress argued that Nvidia’s growth is increasingly diversified beyond hyperscalers such as Microsoft , Google, Amazon and Meta .

“Hyperscalers will remain a major growth driver, but non-hyperscaler growth, our AICE segment, spanning sovereign, regional NeoClouds, enterprise edge and air-gap data centers, will represent roughly half of our data center business,” Kress said.

That $89 billion in Data Center revenue splits into $49 billion from hyperscalers, up 13% sequentially, and what Nvidia calls ACI&E — enterprise, industrial and NeoCloud customers, which Kress’s quote groups under “AICE.” This means Nvidia’s fortunes aren’t solely tied to four or five Big Tech capex budgets.

They’re increasingly spread across sovereign AI programs, regional cloud providers, corporate deployments, and air-gapped or edge systems.

“Our AI-native start-up ecosystem developed and running primarily on the Nvidia compute platform is scaling at a rapid pace,” Kress said.