NVIDIA Q1 FY2027 Revenue Exceeds $81.6 Billion as Demand for AI Infrastructure Continues to Grow

As long as applications continue to generate demand, the AI infrastructure chain is far from reaching its end.

Written by Jim, Maitong MSX

Google and NVIDIA, the application and foundational entry points in the AI world, both delivered their results this week.

If Google I/O was about envisioning the possibilities of AI applications, then NVIDIA’s latest earnings report confirms whether the underlying compute demands behind those visions have been realized.

After market close on May 20 Eastern Time, NVIDIA reported its first fiscal quarter of FY2027, with revenue reaching $81.615 billion, an 85% year-over-year increase and a 20% sequential increase; data center revenue reached $75.2 billion, up 92% year-over-year and 21% sequentially. NVIDIA also announced an additional $80 billion authorization for stock repurchases and increased its quarterly cash dividend from $0.01 to $0.25 per share.

This set of data is already strong on its own, but what the market truly cares about is not whether NVIDIA is still growing, but whether, amid already high market expectations, it can still prove that the AI narrative remains intact, that demand for computing power has not peaked, and that NVIDIA’s pricing power remains solid.

First, it’s important to clarify that NVIDIA’s most core business is no longer traditional “graphics cards,” but rather data centers—the computing infrastructure behind AI factories.

This quarter, NVIDIA’s data center revenue reached $75.2 billion, accounting for over 92% of total revenue. Breaking it down by the previous business classification, data center computing revenue was $60.4 billion, a 77% year-over-year increase; data center networking revenue reached $14.8 billion, a 199% year-over-year increase, also setting a new all-time high.

This highlights a key issue: AI demand is no longer limited to just GPUs, but is expanding toward a comprehensive AI infrastructure—where GPUs handle computation, networks connect computing power, and entire server racks, NVLink, InfiniBand, Ethernet, optical communication, power, and cooling all become integral parts of an AI factory.

Therefore, the significance of this data center revenue isn't just about "NVIDIA selling more"—it indicates that global cloud providers, AI model companies, enterprise customers, and sovereign AI initiatives have not yet significantly reduced their investment in computing power. From this perspective, if data center revenue continues to exceed expectations, risk appetite across the AI hardware supply chain is likely to keep expanding; however, if this metric begins to fall below expectations, the market will truly start to worry that AI capital expenditures have peaked.

Of course, for a high-expectation company like NVIDIA, after the earnings report, the stock price often depends not just on the current quarter's numbers, but more importantly on the guidance for the next quarter.

NVIDIA's revenue guidance for the second quarter of fiscal year 2027 is $91 billion (±2%), significantly above the pre-earnings market consensus of approximately $86–87 billion. The company also explicitly stated that this guidance does not assume any revenue from data center computing in China. This is significant because, even without including China’s data center computing revenue, the guidance still reaches $91 billion, indicating that demand from overseas cloud providers, AI factories, enterprise AI, and other regions is sufficient to sustain strong growth.

In other words, the market had previously worried that NVIDIA’s growth had been too rapid and whether it could continue to exceed expectations. However, this guidance signals that AI computing demand shows no clear signs of slowing down at least over the next quarter.

However, it’s important to note that as market expectations rise, NVIDIA needs to deliver not just a “good earnings report,” but one that is “significantly better than expected.” Therefore, whether the stock surges in the short term still depends on whether investors believe the guidance sufficiently justifies the high valuation.

At the same time, NVIDIA’s high valuation stems not only from its strong revenue growth but also from its exceptional profitability.

This quarter, NVIDIA's GAAP gross margin was 74.9%, and its Non-GAAP gross margin was 75.0%. The company's guidance for next quarter's gross margin is also 74.9% GAAP and 75.0% Non-GAAP, with a ±50 basis point range.

This indicates that although the Blackwell system, HBM, advanced packaging, and rack-scale solutions all lead to higher costs, NVIDIA is still able to maintain its gross margin at around 75%, which for the market clearly signals two things:

• NVIDIA still maintains strong pricing power. Customers are not just buying a single chip—they are purchasing complete platform capabilities;
• Although competition in AI chips has intensified, NVIDIA's profit margins have not yet been significantly compressed. Competitors such as Google TPU, Amazon Trainium, AMD GPUs, and custom ASIC chips will bring competition, but at least based on this earnings report, NVIDIA's profitability has not been noticeably undermined.

Of course, if the gross margin significantly falls below 74% in the future, the market will begin to worry about pressures from product transition costs, customer bargaining power, and alternative solutions—this requires ongoing long-term monitoring.

A notable change in this earnings report is shareholder returns.

In Q1, NVIDIA returned approximately $20 billion to shareholders through stock repurchases and cash dividends. As of the end of the first quarter, $38.5 billion remained under the company’s existing repurchase authorization. Subsequently, the board approved an additional $80 billion in stock repurchase authorization and increased the quarterly dividend from $0.01 to $0.25 per share.

The significance goes beyond the company having cash on its books; more importantly, NVIDIA is sending a positive signal to the market that the AI windfall will not only be reinvested into ecosystem partners, AI startups, and the supply chain, but will also begin to return to shareholders.

After all, the market previously worried that NVIDIA’s substantial investments in AI ecosystem partners like OpenAI and Anthropic might constitute a form of "circular financing." However, if the company simultaneously increases share repurchases and dividends, it can help alleviate long-term investors’ concerns about the efficiency of capital allocation.

This also enables NVIDIA to gradually develop characteristics of an "AI cash flow platform," beyond being just a high-growth AI stock.

Another point of interest for NVIDIA is whether its product cycle can continue.

This quarter, NVIDIA highlighted the Vera Rubin platform, including products such as the Vera CPU and BlueField-4 STX, and mentioned its collaboration with Google Cloud, including Vera Rubin-powered A5X instances and a preview of Google Gemini models running on NVIDIA Blackwell and Blackwell Ultra GPUs.

This indicates that NVIDIA has not stopped at Blackwell but is already laying the groundwork for the next-generation platform.

This is important for investors because if Blackwell is merely a strong cycle, the market will worry about a post-peak decline in growth; but if Vera Rubin can seamlessly follow, NVIDIA won’t just rely on a single-generation product surge—it will demonstrate sustained platform iteration capabilities.

Regarding whether Google's TPU and CPU pose a threat to NVIDIA, I believe it should be viewed from two perspectives.

In the short term, TPU, ASIC, and CPU will indeed take on more tasks in certain scenarios, particularly for internal models and inference workloads within large companies. However, in the medium term, this is less about NVIDIA being immediately replaced and more about multiple approaches coexisting due to the overwhelming demand for AI.

NVIDIA's true advantage lies not just in its GPUs, but in its platform capability—the integrated combination of GPUs, CPUs, networking, software, entire server racks, and ecosystem partners. As long as customers need to rapidly deploy large-scale AI factories, NVIDIA remains at the core of the supply chain.

This earnings report at least proves one thing: the AI theme is intact.

Data center revenue continued to set new records, with next-quarter guidance again exceeding expectations. Gross margin held steady at around 75%, while buybacks and dividends increased significantly. The product cycle has also expanded from Blackwell to Vera Rubin, underscoring NVIDIA’s continued central role in the expansion of AI infrastructure.

But for the stock price, the issue isn’t whether the earnings report is good, but whether it’s good enough to exceed the market’s already high expectations. If the market views this report as merely confirming expectations, short-term volatility may occur; if investors further raise their estimates for AI capital expenditures and NVIDIA’s long-term revenue potential, the AI sector could still continue to expand.

Moreover, from an industry chain perspective, NVIDIA's strong earnings report does not only impact NVDA.M but also prompts the market to reassess the entire AI infrastructure chain:

• ASIC / Manufacturing / HBM: AVGO.M, TSM.M, MU.M
• Network Connectivity: ANET.M, MRVL.M, CRDO.M
• Optical Communication: COHR.M, LITE.M, AAOI.M
• Power cooling: VRT.M, ETN.M, MPWR.M

Of course, if we trace back from the entry point, the fact that Google I/O this week demonstrated the ongoing expansion of AI applications makes it easy to understand why demand for computing power in NVIDIA's earnings report continues to be fulfilled—as long as the application side keeps generating demand, the AI infrastructure chain is far from reaching its end.