Nvidia’s Q4 revenues hit $22.1B, up 265% from a year ago

“Accelerated computing and generative AI have hit the tipping point. Demand is surging worldwide across companies, industries and nations,” said Jensen Huang, CEO of Nvidia, in a statement.

He added, “Our Data Center platform is powered by increasingly diverse drivers — demand for data processing, training and inference from large cloud-service providers and GPU-specialized ones, as well as from enterprise software and consumer internet companies. Vertical industries — led by auto, financial services and healthcare — are now at a multibillion-dollar level.”

And he said, “Nvidia RTX, introduced less than six years ago, is now a massive PC platform for generative AI, enjoyed by 100 million gamers and creators. The year ahead will bring major new product cycles with exceptional innovations to help propel our industry forward. Come join us at next month’s GTC, where we and our rich ecosystem will reveal the exciting future ahead.”

Huang recently returned to the Denny’s restaurant in San Jose, California, where Nvidia began as a startup. Before the earnings, Nvidia’s value in the stock market was $1.667 trillion.

Nvidia’s peers in the stock market are the tech giants: Microsoft, valued at $2.988 trillion; Apple, valued at $2.815 trillion; Google, valued at $1.781 trillion; and Amazon, valued at $1.751 trillion.

Nvidia data center segment includes server GPUs, networking and AI cloud software.

Analysts expected Nvidia to report earnings per share of $4.63 on revenue of $20.62 billion.

For the first fiscal quarter ending January 31, 2024, analysts expected earnings per share of $5 on revenue of $22.17 billion. Nvidia’s after-hours stock price is at $724.1, up 7.32%.

Nvidia said its own outlook for the first quarter of fiscal 2024 is that revenue is expected to be $24 billion, plus or minus 2%. GAAP and non-GAAP gross margins are expected to be 76.3% and 77%, respectively, plus or minus 50 basis points.

GAAP and non-GAAP operating expenses are expected to be approximately $3.5 billion and $2.5 billion, respectively. GAAP and non-GAAP other income and expense are expected to be an income of approximately $250 million, excluding gains and losses from non-affiliated investments.

Huang answers analyst questions

Huang said that the U.S. government wants to constrain shipments of devices for the Chinese market. Nvidia paused its shipments and reconfigured products so that they would not be software-hackable and that took some time. Now the company is sampling chips to China again, within the restrictions of the government.

“Fundamentally, the conditions are excellent for continuing growth,” Huang said in an analyst call. “Let me tell you why. We’re at the beginning of two industry wide transitions. The first one is a transition from general to accelerated computing. General purpose computing, as you know, is starting to run out of steam and you can tell by” depreciation for computing (CPUs in particular) extending from four years to six years.

“There’s just no reason to update with more CPUs when you can fundamentally and dramatically enhance its throughput” through GPUs, Huang said. He said you can accelerate computing with GPUs, improve the energy efficiency, and dramatically improve costs, he said.

“That speed is so incredible that we enabled a second industry wide transition called generative AI,” Huang said. “Remember generative AI is a new application enabling a new way of doing software, with new types of software being created. It is a new way of computing. You can’t do generative AI on traditional general purpose computing. You have to accelerate it.”

He also repeated a notion about “sovereign AI.” This means that countries are protecting the data of their users and companies are protecting data of employees through “sovereign AI,” where the large-language models are contained within the borders of the country or the company for safety purposes.

“We now have a new type of data center that is about AI generation, an AI generation factory. And you’ve heard me describe it as AI factories,” Huang said. “Basically, it takes raw material which is data, transforms it with these AI supercomputers and Nvidia builds and it turns them into incredibly valuable tokens. These tokens are what people experience on the amazing” GenAI platforms like Midjourney.

Huang calls the new kind of data centers “AI supercomputers” as AI is the main application driving them, and “the amount of inference that we do is just off the charts now. Almost every single time you interact with ChatGPT,” you’re using Nvidia hardware.

Huang said the largest cloud-service providers (CSPs) are still building out their hardware with capital expenditures.

Regarding sovereign AI, Huang added, “The data is most useful to their society. So they want to protect the data. They want to transform it themselves, with a value added transformation into AI and provision those services themselves,” Huang said. “So we’re seeing sovereign AI infrastructure being built in Japan, in Canada, in France, and so many other regions.”

He added, “My expectation is that what is being experienced here in the United States and the West will will surely be replicated around the world. And these AI generation factories are going to be in every industry, every company, every region. And so I think the last year we’ve seen generative AI really becoming a whole new applications space, a whole new way of doing computing, a whole new industry is being formed.”

Huang noted Hopper has 35,000 parts and it weighs 70 pounds.

The computer industry is making two simultaneous platform shifts at the same time. Data centers are moving from general computing to accelerated computing, he said. Nvidia enabled this and a new computing paradigm, generative AI.

“We believe these two trends will drive a doubling of the world’s data center infrastructure installed base in the next five years and will represent an annual market opportunity to hundreds of billions,” Huang said. “This new AI infrastructure will open up a whole new world of applications not possible today.
We started the AI journey with the hyperscale cloud providers and consumer internet companies. And now every industry is on board. From automotive, to healthcare, to financial services to industrial to Telecom, media and entertainment.”

Segment reports

In the data center, Nvidia launched data center and PC AI optimizations for Google’s Gemma language models.

In data centers, it expanded its strategic collaboration with Amazon Web Services to host Nvidia DGX Cloud on AWS, and it said Amgen will use the Nvidia DGX SuperPod to power insights into drug discovery and medicine.

Collette Kress, CFO, said in a statement these increases reflect higher shipments of the Nvidia Hopper GPU computing platform used for the training and inference of large language models, recommendation engines, and generative AI applications, along with InfiniBand end-to-end solutions. Data center revenue for fiscal year 2024 was up 217%.

In the fourth quarter, large cloud providers represented more than half of data center revenue, supporting both internal workloads and external customers. Strong demand was driven by enterprise software and consumer internet applications, and multiple industry verticals including automotive, financial services, and healthcare.

Customers across industry verticals access Nvidia AI infrastructure both through the cloud and on-premises. Data center sales to China declined significantly in the fourth quarter due to U.S. government licensing requirements. Data center compute revenue was up 488% from a year ago and up 27% sequentially in the fourth quarter; it was up 244% in the fiscal year.

Networking revenue was up 217% from a year ago and up 28% sequentially in the fourth quarter; it was up 133% in the fiscal year.

Gaming revenue

Nvidia said its gaming division saw $2.9 billion in revenue, flat from the previous quarter and up56% from a year ago.

The year-on-year increases for the quarter and fiscal year reflect higher sell-in to partners following the normalization of channel inventory levels and growing demand. The launch of the GeForce RTX 40 Super Series family of GPUs also contributed to revenue in the quarter, Kress said. In an analyst call, she said that the results in the quarter for GeForce RTX cards was better than expected.

In the quarter, it released the GeForce RTX 40 Super Series GPUs starting at $599, with DLSS 3.5 Ray Reconstruction and Nvidia Reflex. With DLSS, seven out of eight pixels can be rendered faster.

It announced generative AI capabilities for its installed base of over 100 million RTX AI PCs. And it reached a milestone of 500 AI-powered RTX games and applications using Nvidia DLSS, ray tracing and other Nvidia RTX technologies. Every major OEM announced RTX laptops at CES 2024.

Professional visualization was $463 million in the quarter, up 11% from the previous quarter and up 105% from a yea ago. Nvidia announced the adoption of Nvidia Omniverse by the global automotive-configurator ecosystem. And it launched the Nvidia RTX 2000 Ada Generation GPU. Enterprises are refreshing their workstations for generative AI and more.

And fourth-quarter revenue for automotive was $281 million, up 8% from the previous quarter and down 4% from a year ago. Nvidia still continues to generate revenue from Nvidia Drive Orin, and it has lined up a successor with Nvidia Drive Thor, coming next year.

Nvidia announced Nvidia Drive deals with Great Wall Motors, Zeekr and Xiaomi using Drive Orin to power intelligent automated driving systems. He closed by saying everyone should attend Nvidia’s GTC conference on March 18 to March 20. I will be moderating a panel on the Omniverse on March 19 at 4 pm.

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