Nvidia’s latest quarterly results have highlighted the extraordinary scale of spending on artificial intelligence infrastructure, with the chip designer generating more revenue in three months than Taiwan Semiconductor Manufacturing Co. generated during all of 2024.
Nvidia (NASDAQ: NVDA) reported quarterly revenue of $96.2 billion, an increase of 106% from a year earlier. Its Data Center business accounted for $89 billion of that total, up 117% year over year.
The comparison with TSMC (NYSE: TSM; TSE: 2330) underscores how rapidly Nvidia’s business has expanded. TSMC, which manufactures chips designed by Nvidia and other leading semiconductor companies, reported revenue of $88.268 billion for 2024. Nvidia therefore generated more revenue in a single quarter than TSMC did across the entire year.
Nigel Green, CEO of financial advisory firm deVere Group, said the comparison illustrates the unusual combination of scale and growth currently being achieved by Nvidia.
“Companies typically grow fast or grow big. Doing both at once, at this pace and this scale, is exceptionally rare,” Green said.
Nvidia’s growth is being driven primarily by demand for computing infrastructure used to train and run increasingly sophisticated AI models. Data Center revenue has become the company’s dominant business, reflecting demand for its graphics processing units, networking products and related computing platforms from cloud providers and other large technology companies.
The company’s outlook suggests that momentum could continue. Nvidia guided for third-quarter revenue of $108 billion, above the roughly $104 billion expected by Wall Street, according to deVere. The company also issued a first-ever forecast extending into fiscal 2028, projecting revenue growth of about 70% over the period.
Green described the guidance as significant because companies of Nvidia’s size typically face greater difficulty sustaining high growth rates as their revenue base expands.
“A $4 billion beat against consensus, in one quarter’s guidance alone, reflects genuine confidence rather than a rounding difference,” he said.
The company’s comments on supply also drew attention. Nvidia indicated that its growth could be even faster if it were able to secure additional hardware supply, highlighting the extent to which AI infrastructure demand is putting pressure on semiconductor manufacturing and the broader technology supply chain.
That constraint is particularly relevant to TSMC and other companies involved in advanced semiconductor production. Nvidia relies on external manufacturing partners for its chips, while the broader AI accelerator ecosystem depends on advanced packaging, high-bandwidth memory, networking components and increasingly sophisticated data center infrastructure.
The relationship between Nvidia’s growth and TSMC’s manufacturing capacity also illustrates a broader shift in the semiconductor industry. Chip designers are capturing enormous amounts of value from the AI boom, while foundries, memory manufacturers and equipment suppliers are expanding capacity to meet demand.
Nvidia’s financial performance has also raised questions about how investors should value companies exposed to the AI infrastructure cycle. Green argued that the market may still be assessing the implications of Nvidia’s longer-term forecast.
“Companies this large do not usually hand investors a two-year growth number, because the risk of being wrong is enormous,” he said.
Nvidia shares moved higher following the results, although market trading remained volatile, according to deVere. Green said the mixed price movement indicated that investors were still weighing the sustainability of AI-related spending against the company’s exceptional near-term performance.
The bigger issue may extend beyond Nvidia’s valuation. The company sits at the center of an ecosystem spanning semiconductor manufacturing, advanced packaging, memory, networking, data centers and cloud computing. Continued growth in AI workloads could therefore have significant implications for companies throughout that chain.
Nvidia’s results also provide another measure of the extraordinary capital being deployed to build AI infrastructure. Hyperscalers and technology companies are investing heavily in data centers and computing capacity as they seek to support generative AI, large language models and increasingly autonomous AI systems.
For semiconductor manufacturers, that demand creates opportunities while increasing pressure to expand production capacity and maintain technological leadership. TSMC has been investing heavily in advanced process technologies and manufacturing capacity as demand grows for leading-edge chips.
The scale comparison between Nvidia and TSMC should not be interpreted as a direct measure of their relative profitability or economic value. Nvidia and TSMC occupy different positions in the semiconductor value chain and have substantially different business models. Nvidia’s revenue includes the sale of complete computing platforms and related products, while TSMC primarily generates revenue from manufacturing chips for customers.
Still, the comparison illustrates the speed at which AI-related semiconductor demand has reshaped the industry. Nvidia’s ability to generate nearly $100 billion in quarterly revenue, with most of it coming from Data Center operations, reflects a market that has moved well beyond early-stage experimentation.
The next test for Nvidia will be whether its projected growth can be sustained as its revenue base becomes increasingly large, competitors expand their AI offerings and customers assess the returns from massive infrastructure investments. For the wider semiconductor industry, the company’s results offer a powerful signal that AI computing demand remains one of the sector’s most consequential growth drivers.
