Nvidia Q3: Revenues spike 62 per cent to record $57bn as CEO sees ‘something very different’ from AI bubble

Jensen Huang claims the AI infrastructure giant is benefiting from “three massive platform shifts” happening at once

Nvidia’s third-quarter revenue grew to a record $57bn, marking a 62 per cent year-over-year increase that was largely driven by sales of the company’s Blackwell and Blackwell Ultra GPU platforms.

Net income also jumped 59 per cent and 23 per cent sequentially for the AI infrastructure giant to $31.9bn.

Most of Nvidia’s Q3 revenue came from its datacentre segment, which grew 66 per cent and 25 per cent sequentially to a record $51.2bn, amounting to nearly 90 per cent of total sales for the period.

The datacentre revenue was mostly driven by the company’s Blackwell Ultra GPU platform, Nvidia CFO Colette Kress revealed in an earnings call, and is “now [its] leading architecture across all customer categories” after launching earlier this year.

Nvidia’s datacentre compute achieved record revenue of $43bn, up 56 per cent from a year ago and up 27 per cent sequentially.

As for the networking side of the datacentre segment, revenue grew 162 per cent and 13 per cent sequentially to $8.2bn. Kress credited the massive 12-month jump in revenue to the “introduction and continued growth” of Nvidia’s NVLink compute fabric for its Blackwell-based GB200 and Blackwell Ultra-based GB300 systems.

Jensen Huang on the AI bubble

Nvidia CEO Jensen Huang took on the popular question of whether his company is at the centre of an AI bubble, claiming he sees “something very different” that will “contribute to infrastructure growth in the coming years.”

Arguing against comparisons to the dot-com bubble that led to the stock market crash in 2000, Huang said on Nvidia’s earnings call it is benefiting from “three massive platform shifts” happening at once.

“The first time since the dawn of Moore's law, Nvidia is uniquely addressing each of the three transformations,” he said, referring to Intel founder Gordon Moore’s observation that the transistors on a computer chip will double every two years.

On the call Kress reiterated recent remarks by Huang that the company has “visibility” to $500bn in revenue from the beginning of this year to the end of next year for its Blackwell and next-generation Rubin platforms. The company expects the AI infrastructure market to reach up to $4tn by the end of the decade.

With the company continuing to experience fast sales growth of its products and platforms for AI datacentres, Huang spent the first few minutes of his earnings call appearance to explain why the massive infrastructure investments announced by Nvidia’s customers and partners over the past few years for AI development do not represent a bubble.

Addressing the tech industry’s three platform shifts that are pointing to sustained growth, Huang said the first is the ongoing transition from general-purpose computing, made possible by CPUs, to accelerated computing enabled by GPUs and other accelerator chips.

Stressing his oft-mentioned point that Moore’s law is slowing down, Huang said previously CPU-bound applications—including those for data processing and simulation—are “rapidly shifting” to take advantage of Nvidia’s GPUs through its CUDA programming platform.

“Secondly, AI has also reached a tipping point and is transforming existing applications while enabling entirely new ones for existing applications,” he added. “Generative AI is replacing classical machine learning in search ranking, recommender systems, ad targeting, click-through prediction [and] content moderation.

“Transitioning to generative AI represents substantial revenue gains for hyperscalers,” he said.

To Huang, the third shift is focused on agentic AI and physical AI, which he said “will be revolutionary, giving rise to new applications, companies, products and services.”

Pointing to companies adopting agentic AI features, he cited coding assistants like Cursor and Quadcode, radiology tools like Aidoc, legal assistants like Harvey and autonomous taxis from the likes of Tesla and Google-owned Waymo.

“The fastest-growing companies in the world today—OpenAI, Anthropic, xAI, Google, Cursor, Lovable, Replit, Cognition AI, OpenEvidence, Abridge, Tesla—are pioneering agentic AI,” Huang said.

Earlier in the call, Colette said physical AI “is already a multibillion-dollar business, addressing a multitrillion-dollar opportunity and the next leg of growth for Nvidia.”

Huang claimed these shifts to accelerated computing, generative AI, agentic AI and physical AI will not only continue but accelerate over time to benefit the economy.

“As you consider infrastructure investments, consider these three fundamental dynamics. Each will contribute to infrastructure growth in the coming years,” he added.

“Nvidia is chosen because our singular architecture enables all three transitions and does so for any form and modality of AI across all industries, across every phase of AI, across all of the diverse computing needs in a cloud, and also from cloud to enterprise to robots [with] one architecture,” Huang said.

This article is a combination of two articles that originally appeared on CRN UK sister website CRN here and here.