Nvidia Earnings Quick Read: Quarterly Revenue Poised to Break the $100 Billion Mark, with Another 70% Growth Expected Next Year

Original: Odaily Planet Daily (@OdailyChina)

Author: Azuma (@azuma_eth)

In the early morning of August 27, Beijing time, Nvidia released its Q2 FY2027 earnings report for the period ending July 26, 2026. The data showed that Nvidia's (NVDA) revenue and profit for the second quarter comprehensively beat expectations, with the data center business continuing to accelerate and next quarter's guidance reaching a new high.

Specifically, Nvidia's Q2 revenue reached $96.221 billion, up 106% year-over-year and 18% quarter-over-quarter, exceeding analyst expectations by 4%; non-GAAP net profit was $53.954 billion, up 118% year-over-year, with adjusted EPS of $2.22, nearly 6% above market expectations. Additionally, Nvidia guided Q3 revenue to $108 billion, signaling the company is about to formally enter the era of "quarterly revenue exceeding $100 billion."

The figures above are impressive enough, but they still weren't the most surprising number in this earnings report. During the investor conference call following the release, Nvidia CFO Colette Kress delivered a signal the market hadn't fully anticipated — the company projects FY2028 revenue will still grow approximately 70% (not including any data center revenue from China), significantly exceeding Wall Street's previous expectation of 45%.

More importantly, Nvidia emphasized that this 70% growth expectation was given even under supply constraints. In other words, the company's primary challenge no longer seems to be "how long AI demand can last," but rather "just how much of Nvidia's demand the supply chain can satisfy."

Following the earnings report and conference call, Nvidia rose over 4% in after-hours trading, last trading at $219.53.

Revenue Structure: AI Demand Still Driven by Hyperscalers

A closer look at Nvidia's $96.2 billion revenue structure reveals that "the data center business remains the absolute core revenue source."

In Q2, Nvidia's data center revenue reached $89 billion, up 117% year-over-year and 18% quarter-over-quarter, accounting for over 90% of the company's total revenue. More importantly, the data center segment's growth rate continues to outpace the company's overall revenue — in Q1, Nvidia's total revenue grew 85% year-over-year while data center revenue grew 92%; by Q2, both growth rates further accelerated to 106% and 117% respectively — even with quarterly revenue approaching $100 billion, Nvidia's core business hasn't shown any signs of slowing down; if anything, it's still accelerating.

Within the data center business, Q2 growth remained primarily driven by hyperscalers. Nvidia disclosed that Q2 revenue from hyperscale customers was approximately $48.7 billion. Meanwhile, major tech companies such as Amazon, Microsoft, Google, and Meta continue to expand their AI infrastructure investments. Just before the earnings release, AWS announced plans to deploy an additional 2 million Nvidia GPUs.

This means that at least from the current revenue structure perspective, the primary driver of AI computing demand remains the capital expenditures of major cloud providers. This is also the most critical variable for observing Nvidia's future growth trajectory and the continuation of the AI cycle. If Microsoft, Amazon, Google, Meta, and others continue to grow their capex, Nvidia's high growth will continue to have the most direct order support; conversely, if these companies' AI investments begin entering a digestion phase, Nvidia will be the first to feel the pressure.

On the other hand, Nvidia's edge computing business recorded $7.2 billion in revenue, up 27% year-over-year and 13% quarter-over-quarter. While still significantly smaller in scale compared to the data center business, as a representative of the company's "physical AI" push, this represents Nvidia's long-term strategy to reduce dependence on a single business segment.

Vera Rubin: A New Product Cycle Has Begun

The most important product-level signal from this earnings report and subsequent conference call was the deployment of Vera Rubin — Nvidia confirmed on the call that Vera Rubin has entered full production and began shipping earlier this month... Every 1 GW of compute deployed with Vera Rubin corresponds to approximately $40 billion in revenue opportunity, and it's expected to contribute roughly 20% of data center revenue in Q3.

This announcement marks Nvidia's gradual transition from the Blackwell cycle to the Rubin cycle.

For a company with such rapid product iteration, this transition between old and new platforms is critical. Historically, one major market concern about the AI chip cycle was whether each generation could seamlessly hand off to the next; if there were significant gaps between two product generations, revenue growth would naturally decelerate rapidly. This time, however, Rubin's commercialization pace is clearly fast enough.

As Nvidia's rack-scale supercomputing platform designed specifically for AI, Vera Rubin integrates seven self-developed chips including the Rubin GPU, Vera CPU, NVLink6, and ConnectX-9, achieving a leapfrog upgrade in performance. This product evolution ultimately translates into value capture — the data anchor of "$40 billion revenue per 1 GW of compute" means that as data centers continue to scale after Vera Rubin's deployment, the value Nvidia can extract from each newly built AI data center will continue to rise.

Additionally, Jensen Huang himself emphasized on the call that Vera Rubin's ramp-up will be the fastest in company history... This may well be the source of Nvidia's confidence in guiding "approximately 70% FY2028 revenue growth."

AI Demand Persists, But Supply Has Become the Bottleneck

Regarding the question of "whether AI demand has peaked," Nvidia management conveyed a stronger signal than ever before during the post-earnings investor call: demand hasn't just held steady — it's still accelerating.

Jensen Huang stated bluntly on the call that AI has entered a new phase. Over the past year, AI computing demand was primarily driven by a few leading model companies; now, demand is spreading across more frontier models, open-source models, enterprise AI, agents, and robotics.

The most significant change indicator here is the accelerating growth in inference demand. As large models move from training to real-world applications, AI computing consumption is no longer just a one-time investment during model training, but rather continues to grow with user usage and token generation. Huang even directly used the phrase "tokens are becoming productive and profitable" to describe this shift.

Furthermore, Nvidia stated on the call that based on current capex plans from major tech companies, there are no visible signs of demand deceleration. The top five global cloud service providers are expected to spend nearly $800 billion in capex this year, potentially reaching approximately $1.3 trillion next year.

These observations collectively form the underlying foundation for Nvidia's assessment of future "AI demand." However, despite such robust demand, supply has emerged as the constraining factor limiting Nvidia's further growth. In other words, the company's current primary bottleneck isn't insufficient orders, but whether components, production capacity, and delivery capabilities can keep pace with order velocity.

Nvidia management explicitly stated on the call that at least through FY2028, supply will remain the primary bottleneck restricting the company's growth. Huang even emphasized that without supply constraints, the company's FY2028 outlook would be "significantly higher."

Here, "supply" isn't limited solely to GPUs themselves. As AI chip scale expands rapidly, HBM, advanced packaging, wafers, networking equipment, and data center power could all become critical factors constraining compute deployment speed. HBM deserves particular attention — Nvidia directly addressed the significant rise in memory prices on this call, projecting Q3 non-GAAP gross margin of approximately 74%, down from 75% in Q2, with rising memory costs continuing to pressure subsequent profit margins.

To break through this bottleneck, Nvidia is extending its role toward that of a "capital organizer" for AI infrastructure. The earnings report revealed that Nvidia has established strategic partnerships with Apollo, BlackRock, Blackstone, Brookfield, Goldman Sachs, and KKR, aiming to mobilize over $500 billion in third-party capital for AI infrastructure construction. Additionally, Nvidia has partnered with SB Energy at the PORTS-Pike Technology Campus in Ohio, securing land, power, and building shell capacity in advance to accommodate its compute deployments.

The $100 Billion Threshold and the Next Starting Point

This earnings report, along with management's statements on the conference call, once again provisionally answered the market's most pressing question — has AI demand peaked, and is the cycle over?

Based on the 70% FY2028 revenue growth guidance, Nvidia's current answer is that "the cycle is far from over" — the ceiling is still distant, and the current growth rate isn't even a true reflection of demand, but rather the limit of what the supply chain can support. When a company with quarterly revenue approaching $100 billion still dares to issue growth targets far exceeding market expectations under supply constraints, it can only mean that the orders Nvidia sees on its books are even deeper than the numbers it dares to put in its guidance.

Nvidia itself, meanwhile, is continuously expanding its commercial role to adapt to market development needs. Today's Nvidia is no longer just a semiconductor company designing GPUs — it's evolving into the general contractor for "AI factories," providing chips, networking, CPUs, software, deployment solutions, and even participating in infrastructure financing and securing land and power.

Of course, high expectations come with high pressure. The modest decline in gross margin guidance and policy uncertainties in global markets are inevitable frictions in billion-scale expansion... But at least for now, the core logic that leads the market to grant Nvidia a premium remains unshaken — on the AI infrastructure track, Nvidia is still the player setting the rules, with no visible challenger in sight.

When Q3 revenue formally crosses the $100 billion quarterly threshold, Nvidia will enter a new order of magnitude. And the 70% growth guidance for next year suggests that this threshold may only be the starting point of the next leg.