By Su Yang, Tencent Technology
NVIDIA delivered another outstanding earnings report, with revenue, operating profit, and earnings per share all reaching record highs.
On August 26 in the United States, NVIDIA announced its financial results for the second quarter of fiscal year 2027, ending on July 26, 2026. The report showed that NVIDIA’s revenue for the quarter reached $96.221 billion, representing a 106% year-over-year increase and an 18% sequential increase; net profit reached $59.688 billion, up 126% year-over-year; and diluted earnings per share were $2.46, up 128% year-over-year.
Compared to the previous quarter's revenue of $81.615 billion, NVIDIA continues to set new growth records. A year ago, the company's quarterly revenue was only $46.743 billion, nearly doubling in just one year.
After the earnings report, NVIDIA's stock dropped about 1.3% in after-hours trading, then surged more than 4%, reflecting shifting and divergent market concerns: investors previously focused on whether NVIDIA could continue to exceed expectations; now they are more concerned about how long AI infrastructure growth can last, and whether next-generation chips and new business models can sustain future growth.
From a profitability standpoint, NVIDIA continues to maintain an extremely high level.
In the second fiscal quarter, the company's operating profit reached $63.734 billion, a 124% year-over-year increase; on a Non-GAAP basis, net profit was $53.954 billion, up 118% year-over-year. During the same period, the company's gross margin reached 75%, higher than 72.4% in the same period last year and slightly above the first fiscal quarter's 74.9%.
Jensen Huang, founder and CEO of NVIDIA, said: "Artificial intelligence has reached a tipping point. It is performing useful work, and its tokens are generating productivity and profitability. Now, computing is revenue."
Now, more AI labs and startups are rapidly expanding, and new directions such asphysical AIare also emerging, as the entire AI industry enters a broader phase of development.
Meanwhile, NVIDIA continues to increase shareholder returns. In the second fiscal quarter, the company returned approximately $26 billion to shareholders through stock buybacks and cash dividends. As of the end of the quarter, approximately $99 billion remained under the company’s stock repurchase authorization.
01 Data center revenue surged, with AI cloud customers growing even faster
The core driver of NVIDIA's current growth remains its data center business.
In the second fiscal quarter, NVIDIA's data center revenue reached $89.023 billion, representing a 117% year-over-year increase and an 18% sequential increase, accounting for nearly all of the company's revenue growth. As global enterprises and cloud service providers continue to invest in AI infrastructure, demand for NVIDIA's GPUs remains high.
NVIDIA adjusted its disclosure methodology for data center revenue in the first fiscal quarter, categorizing customers into two groups: Hyperscale and ACIE.
Among these, hyperscale customer revenue reached $48.71 billion, representing a 102% year-over-year increase and a 13% quarter-over-quarter increase, primarily driven by large public cloud and internet companies.
Meanwhile, revenue from AI Cloud, Industrial, and Enterprise (ACIE) reached $40.313 billion, representing a 138% year-over-year increase and a 25% quarter-over-quarter increase. This business serves AI-native companies, enterprise customers, sovereign AI clients, and those with massive-scale computing demands using AI cloud services.
The new classification shows that AI computing demand is spreading from a few major cloud providers to enterprises, governments, and more industry use cases. However, investors still focus on profitability and long-term demand behind different customer types, not just growth in order volume.
The mainland China market remains an important variable in the financial report.
NVIDIA stated that revenue from Hopper products shipped to data centers in mainland China accounted for less than 1% of total data center revenue in the second fiscal quarter. Additionally, the company did not include any data center computing revenue from mainland China in its guidance for the third fiscal quarter.
In addition to data center operations, edge computing revenue for the second fiscal quarter reached $7.198 billion, representing a 27% year-over-year increase and a 13% sequential increase. Growth was driven by Blackwell workstation sales, but this was partially offset by declines in consumer PCs due to rising memory and system prices.
02 Blackwell UltraIncreased volume, full deployment of Vera Rubin
NVIDIA is advancing its product roadmap from a single GPU to a complete computing platform.
In the second fiscal quarter, Blackwell Ultra became a key driver of growth in the data center business. NVIDIA stated that the quarter's data center revenue growth was primarily driven by large-scale deployments of Blackwell Ultra infrastructure. As cloud service providers and AI companies continue to build large-scale AI computing clusters, Blackwell is entering a broader phase of commercial deployment.
Meanwhile, NVIDIA has begun preparing for the next product cycle. In the second fiscal quarter, the company announced that the Vera Rubin platform is now fully operational, with related rack systems running on cloud platforms of partners such as CoreWeave and Google Cloud.
The Rubin platform includes not only GPUs but also CPUs, networking, software, and system-level solutions. Among them, the Vera CPU is NVIDIA's first CPU designed specifically for AI agents and is planned to be adopted by leading technology providers worldwide.
In addition, NVIDIA has announced that the NVIDIA Groq 3 LPX for interactive AI inference is now fully operational. NVIDIA aims to strengthen its competitive position in real-time AI inference scenarios through products like Groq 3 LPX.
In addition to hardware products, NVIDIA is also strengthening its software ecosystem.
In the second fiscal quarter, the company launched the DSX platform, providing infrastructure builders with a comprehensive solution for designing, building, and operating large-scale AI factories. The platform integrates computing, networking, software, and systems to help customers build larger AI infrastructure.
In the realm of AI software, NVIDIA continues to expand the NVIDIA Agent Toolkit and enhance development capabilities through PhysicsNeMo and the CUDA-X libraries. The company states that it is collaborating with global software platform providers to launch new software, open-source models, and partner projects.
For NVIDIA, product competition is no longer limited to individual chip performance, but has expanded to encompass the entire ecosystem—from chips and networks to software and systems. However, the market continues to focus on the pace of the transition from Blackwell to Rubin, and whether the new generation of platforms can continue to drive customers to expand their AI infrastructure investments.
03 AI infrastructure enters the funding stage, with NVIDIA taking on a greater role in construction
As AI data centers continue to expand, NVIDIA is becoming more involved in infrastructure development.
The second fiscal quarter financial report showed that, as of July 26, 2026, NVIDIA’s future committed amounts reached $360 billion, including $279 billion in supply and capacity commitments, $29 billion in cloud service agreements, $23 billion in capital expenditures, and $25 billion in equity investments.
The above commitments are primarily related to future AI infrastructure expansion, with the most notable being NVIDIA's involvement in theSB EnergyPORTS-Pike project in Ohio.
NVIDIA stated that the company is providing credit support for SB Energy’s technology park in Ohio, which initially involves approximately 4.25 GW of land, power, and facility development for hosting NVIDIA infrastructure for OpenAI. NVIDIA’s guarantee obligations are capped at $105 billion and will be phased in upon fulfillment of conditions such as the data center becoming operational.
Meanwhile, NVIDIA is driving larger-scale capital investment in AI infrastructure. The company has already announced strategic partnerships with Apollo, BlackRock, Blackstone, Brookfield, Goldman Sachs, and KKR, aiming to mobilize over $500 billion in third-party capital for AI infrastructure development in the coming years.
Jensen Huang believes that AI infrastructure development is entering a new phase, requiring significant capital investment to support AI model training, inference, and the growth of more applications.
However, as NVIDIA becomes involved in more infrastructure projects, the market is also beginning to pay attention to the capital pressure this model brings.
As of the end of the second fiscal quarter, NVIDIA's total cash, cash equivalents, and marketable debt securities amounted to $56.6 billion. Meanwhile, the company issued $25 billion in senior unsecured notes during the second fiscal quarter for general corporate purposes. NVIDIA stated that its financial position remains strong, and future investments will primarily focus on supporting supply chains, infrastructure, and long-term growth needs.
04 Q3 revenue to exceed 100 billion, competitive pressures begin to emerge
For the next quarter, NVIDIA has provided guidance for continued growth.
The company expects revenue for the third quarter of fiscal year 2027 to reach $108 billion, plus or minus 2%, with gross margins of 74% under both GAAP and Non-GAAP measures. NVIDIA also emphasized that this guidance does not include any data center computing revenue from China.
Compared to the $96.2 billion in revenue in the second quarter, NVIDIA expects continued growth in the third quarter. However, market focus has shifted from quarterly growth to the long-term competitive landscape.
The AI chip market competition is currently expanding. NVIDIA emphasized in its earnings report that the company is maintaining its advantage through a comprehensive computing platform, including processors, interconnect technologies, software, algorithms, systems, and services. The company aims to meet AI training and inference needs through this entire ecosystem.
At the same time, competitors are accelerating their efforts. AMD continues to launch data center products, and Google is developing its own TPU chips. Major tech companies are both important customers of NVIDIA and are investing resources into building their own computing platforms.
Investors are particularly focused on the development of the AI inference market. As AI applications grow, computing demand is expanding from model training to inference services. NVIDIA aims to maintain its market leadership by enhancing inference capabilities through the Vera Rubin platform, Groq 3 LPX, and its software ecosystem.
However, future growth still depends on answering several questions: whether the Blackwell Ultra and Rubin platforms can continue driving increased customer procurement; whether AI infrastructure investment can maintain its current pace; and whether NVIDIA’s market share in AI computing will be affected as customers develop their own chips.
$96.2 billion in revenue is another milestone for NVIDIA in the AI wave.
For NVIDIA, the record-breaking financial data validates the success of the previous cycle, and the challenge for the next phase is to maintain its core position as the AI industry enters a stage of larger-scale development.