<\/p>\n
Most companies would kill for the biggest problem Nvidia (NVDA) has.<\/p>\n
The AI-chip giant just generated $96.2 billion in quarterly revenue, more than double its sales from a year earlier. Its Data Center division reached $89 billion, and Nvidia forecasts another $108 billion of companywide revenue in the current quarter.<\/p>\n
Then management said something that alters the way investors should look at those numbers.<\/p>\n
Nvidia’s earnings call predicted revenue would rise about 70% in the fiscal year ending January 2028. But the company also expects supply constraints to continue at least through the end of that fiscal year.<\/p>\n
That’s an odd situation for a company that is already running at Nvidia’s scale.<\/p>\n
Demand isn’t currently the obvious ceiling.<\/p>\n
Supply is.<\/p>\n
The difference matters because analysts are starting to think about numbers that would have seemed almost absurd just a few years ago. Raymond James analyst Simon Leopold thinks Nvidia could potentially generate $1 trillion in annual revenue in fiscal 2029.<\/p>\n
That is well above current Wall Street expectations of just under $750 billion.<\/p>\n
But Nvidia’s latest results suggest the path to such numbers could depend on something much more tangible than AI enthusiasm: whether Nvidia and its suppliers can churn out enough GPUs, memory, networking equipment, and complete computing systems to satisfy customers who are already lining up to buy them.<\/p>\n
Nvidia is selling nearly twice as much as it did a year ago<\/p>\n
First, just the sheer number of hardware units Nvidia is already shipping.<\/p>\n
Fiscal second-quarter revenue increased 106% year over year and 18% sequentially to $96.2 billion.<\/p>\n
Data Center revenue soared 117% to $89 billion.<\/p>\n
That means Data Center generated about 92.5 cents of every dollar Nvidia made in the quarter.<\/p>\n
The profit numbers are just as striking.<\/p>\n
GAAP operating income reached $63.7 billion, up 124% from a year ago. Net income climbed 126% to $59.7 billion, while GAAP earnings per diluted share increased 128% to $2.46.<\/p>\n
Nvidia also kept a 75% GAAP gross margin.<\/p>\n
Those numbers matter for the supply story because Nvidia is easily turning demand into profit as it scales.<\/p>\n
The company reported net income of nearly $60 billion on revenue of $96 billion in three months.<\/p>\n
Related: Bank of America doubles down on Nvidia stock<\/p>\n
And the company isn’t expecting the growth to slow this quarter.<\/p>\n
Nvidia expects third-quarter revenue of $108 billion, plus or minus 2%.<\/p>\n
That means Nvidia expects to make more revenue in one quarter than it did in the entire fiscal year ending in January 2024, when annual revenue was $60.9 billion.<\/p>\n
Nvidia’s growth forecast comes with an unusual warning<\/p>\n
The more telling number came when Nvidia looked beyond the next quarter.<\/p>\n
Management provided a preliminary outlook for fiscal 2028, anticipating revenue growth of around 70%.<\/p>\n
That’s a tremendous projection for a business that already makes hundreds of billions of dollars a year.<\/p>\n
But maybe even more important than that forecast is the sentence that comes with it:<\/p>\n
“We expect supply to remain a bottleneck at least through the end of fiscal year 2028,” NVIDIA Chief Financial Officer Colette Kress said during the Q2 FY2027 earnings call.<\/p>\n
That tells investors something about the balance of demand for Nvidia’s chips and the company’s production capacity.<\/p>\n
The company is forecasting less than 70% growth and warns that customers could disappear.<\/p>\n
It is forecasting 70% growth while saying its ability to supply those customers remains constrained.<\/p>\n
More Nvidia:<\/p>\n
Nvidia just made a move Wall Street wasn’t ready for<\/p>\n
Nvidia just locked down deal that changes AI race<\/p>\n
Nvidia stock is doing something it hasn’t done in years<\/p>\n
The demand is also getting broader.<\/p>\n
Revenue from a category that includes AI-native companies, enterprises, and sovereign customers grew 138%, while hyperscaler revenue more than doubled from a year ago, said Nvidia.<\/p>\n
That matters because one of the big bearish arguments that has swirled around AI stocks is concentration: A handful of huge technology companies are pouring huge amounts of money into infrastructure.<\/p>\n
Nvidia’s numbers suggest demand is spreading beyond that initial group.<\/p>\n
Nvidia just told Wall Street what could cap its next leg higher<\/p>\n
Bloomberg \/ Getty Images<\/p>\n
Nvidia’s next AI system makes the supply problem even bigger<\/p>\n
Meanwhile, Nvidia is undergoing yet another major product transition.<\/p>\n
Its Vera Rubin architecture is entering production, and Nvidia expects Rubin to represent roughly 20% of Data Center revenue in the third quarter, with supply ramping further afterward.<\/p>\n
The change is important because it’s not just about discrete graphics processors that Nvidia is shipping anymore.<\/p>\n
Its AI business is increasingly about full systems with GPUs, CPUs, networking, high-bandwidth memory, and other components that need to work together at massive scale.<\/p>\n
That makes for a lot more complicated supply chain. One shortage can impact delivery of a whole system. A particularly important example is memory.<\/p>\n
On its latest earnings call, Nvidia acknowledged what it called “extreme pricing conditions” in memory.<\/p>\n
AI accelerators require high-bandwidth memory, or HBM, capable of moving enormous quantities of data rapidly enough to keep increasingly powerful processors working efficiently.<\/p>\n
The more GPUs that Nvidia ships, the more memory the industry will need.<\/p>\n
The same principle extends to packaging, networking, racks and power infrastructure.<\/p>\n
So Nvidia’s challenge is more than just making another chip.<\/p>\n
It needs to develop a full AI-computing ecosystem fast enough to meet extraordinary customer demand.<\/p>\n
The $1 trillion Nvidia scenario depends on solving this problem<\/p>\n
Here’s where Raymond James’ $1 trillion scenario comes in handy.<\/p>\n
This is not a target, but rather a measure of what could be on the other side of Nvidia’s supply constraints.<\/p>\n
MarketWatch has a current year revenue estimate for Nvidia of about $403.5 billion.<\/p>\n
If revenue then grew at Nvidia’s prior 70% fiscal 2028 growth rate, annual sales would approach $686 billion.<\/p>\n
Nvidia would need another 46% rise from around $686 billion to reach $1 trillion.<\/p>\n
That would normally sound extreme. But Nvidia just grew quarterly revenue 106%. Its Data Center business grew 117%. And another major group of AI customers grew 138%.<\/p>\n
Raymond James’ scenario is still substantially more bullish than consensus. FactSet estimates put fiscal 2029 revenue at below $750 billion.<\/p>\n
That’s about $250 billion a year wrong.<\/p>\n
That gap shows how much hinges on Nvidia’s ability to increase supply.<\/p>\n
If demand stays strong and Nvidia can build and ship many more systems, today’s consensus estimates could be conservative.<\/p>\n
If manufacturing capacity, memory availability, packaging or other infrastructure can’t ramp up quickly enough, Nvidia could be leaving huge amounts of potential revenue on the table.<\/p>\n
Nvidia’s customers are creating another constraint<\/p>\n
There’s another physical limitation that Nvidia can’t fix on its own.<\/p>\n
Its customers need places to put all this equipment.<\/p>\n
AI data centers need huge amounts of electricity, land, cooling equipment and networking infrastructure.<\/p>\n
This makes Nvidia’s growth equation a little bit broader:<\/p>\n
Chip supply + memory + servers + data centers + electricity = potential revenue.<\/p>\n
The larger the scale of AI spending, the more important each of those variables becomes.<\/p>\n
Nvidia CEO Jensen Huang has long argued that the world is moving from traditional general-purpose computing to accelerated computing and AI infrastructure.<\/p>\n
The company’s financial results show the extent of that transition. But now the industry has to physically build the infrastructure to carry it. That’s why Nvidia’s supply warning is more notable than the usual quarterly shortage. Quarterly sales of $96.2 billion can mean very large amounts of revenue from small constraints.<\/p>\n
A bottleneck equal to just 5% of Nvidia’s current quarterly revenue would represent roughly $4.8 billion.<\/p>\n
At a hypothetical $700 billion annual revenue run rate, the same 5% would represent $35 billion.<\/p>\n
The larger Nvidia becomes, the more expensive every constraint becomes.<\/p>\n
Nvidia investors may be watching the wrong risk<\/p>\n
For much of the past year, investors have been focused on whether companies such as Microsoft, Amazon, Alphabet, and Meta can keep spending extraordinary amounts on AI infrastructure.<\/p>\n
But the results from Nvidia don’t take that risk away.<\/p>\n
But they change the immediate question.<\/p>\n
Nvidia just reported a 106% jump in revenue, a 117% jump in Data Center, and almost $60 billion in net income for the quarter. Management guided for about 70% revenue growth for the next fiscal year while simultaneously warning that supply will remain constrained.<\/p>\n
The market responded.<\/p>\n
Nvidia shares jumped 8.7% after earnings, adding about $442 billion in market capitalization in a single session.<\/p>\n
The stock reaction was more than just another earnings beat.<\/p>\n
Investors received evidence that Nvidia believes the expansion of AI infrastructure can remain strong well beyond the next several quarters.<\/p>\n
This news raises the importance of the company’s production capacity.<\/p>\n
One day there will be a plateau in AI demand. No company can double forever, especially one with annual sales in the hundreds of billions of dollars.<\/p>\n
But recent numbers from Nvidia suggest it isn’t there yet.<\/p>\n
Instead, the company is facing a much stranger problem.<\/p>\n
It has customers paying enough to generate $89 billion of Data Center revenue in a three-month period, it expects about 70% growth in the next fiscal year, and it doesn’t believe the supply chain will ever fully catch up.<\/p>\n
That trillion-dollar revenue debate is just an insane headline.<\/p>\n
The more relevant fact for investors is what Nvidia needs to do before that number could ever become possible.<\/p>\n
It has to build enough AI infrastructure to satisfy demand that is already there.<\/p>\n
Related: OpenAI’s agents breached Hugging Face. Nvidia wants it.<\/p>\n
#Nvidias #billion #quarter #revealed #surprising #constraint<\/p>\n","protected":false},"excerpt":{"rendered":"
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