NVIDIA has once again delivered an impressive financial report, with revenue, operating profit, and earnings per share all hitting historical highs.

On August 26, local time in the United States, NVIDIA announced its second fiscal quarter results for the fiscal year 2027, ending on July 26, 2026. The financial report showed that NVIDIA's revenue for the quarter reached $96.221 billion, a year-on-year increase of 106% and a quarter-on-quarter increase of 18%; net profit hit $59.688 billion, a year-on-year increase of 126%; diluted earnings per share were $2.46, a year-on-year increase of 128%.

Compared to last quarter’s revenue of $81.615 billion, NVIDIA continued to break growth records. In the same quarter last year, the company had revenue of only $46.743 billion, essentially doubling its revenue in just one year.

After the financial report was released, NVIDIA's stock price fell about 1.3% in after-hours trading, then surged more than 4%, reflecting the market's differing and changing concerns: in the past, investors focused on whether NVIDIA could continue to exceed expectations; now they are more concerned about how long AI infrastructure development can be sustained, and whether the next generation of chips and new business models can support future growth.

From a profitability perspective, NVIDIA continues to maintain a very high level.

In the second fiscal quarter, the company’s operating profit reached $63.734 billion, a year-on-year increase of 124%; according to Non-GAAP standards, net profit was $53.954 billion, a year-on-year increase of 118%. During the same period, the company’s gross margin reached 75%, up from 72.4% a year earlier and slightly above 74.9% in the first fiscal quarter.

NVIDIA’s founder and CEO Jensen Huang stated, “Artificial intelligence has reached a turning point. It is doing useful work, and its tokens are creating productivity and profitability. Now, computing is revenue.”

Now, more AI laboratories and startups are rapidly expanding, with open-source model ecosystems andphysical AI and other new directions also starting to develop, and the entire AI industry is entering a broader construction cycle.

At the same time, NVIDIA continues to increase shareholder returns. In the second fiscal quarter, the company returned approximately $26 billion to shareholders through share buybacks and cash dividends. As of the end of the quarter, the company's stock repurchase authorization remains approximately $99 billion.

01 Data Center Revenue Soars, AI Cloud Customers Grow Even Faster

The core driving force behind NVIDIA's current growth remains the data center business.

In the second fiscal quarter, NVIDIA's data center revenue reached $89.023 billion, a year-on-year increase of 117% and a quarter-on-quarter increase of 18%, contributing nearly all of the company's revenue growth. With global enterprises and cloud service providers continuously investing in AI infrastructure, the demand for NVIDIA GPUs remains high.

NVIDIA adjusted the way it discloses data center business metrics in the first fiscal quarter, classifying customers into two categories: Hyperscale and ACIE.

Among them, revenue from hyperscale customers reached $48.71 billion, a year-on-year increase of 102% and a quarter-on-quarter increase of 13%, mainly from large public cloud and internet companies.

At the same time, revenue from AI cloud and industrial and enterprise customers (ACIE) reached $40.313 billion, a year-on-year increase of 138% and a quarter-on-quarter increase of 25%. This business encompasses AI-native companies, enterprise customers, sovereign AI clients, and the massive compute needs that utilize AI cloud services.

The new classification method indicates that AI computing demand is spreading from a few cloud giants to enterprises, governments, and more industry scenarios. However, investors remain focused on the profitability and long-term demand behind different customer types, rather than just the growth of order volume.

The mainland Chinese market remains a significant variable in the financial report.

NVIDIA stated that in the second fiscal quarter, revenue from data center Hopper products shipped to mainland China accounted for less than 1% of data center revenue. Additionally, the company’s performance outlook for the third fiscal quarter does not include any revenue from data center computing in mainland China.

Aside from the data center business, edge computing revenue in the second fiscal quarter reached $7.198 billion, a year-on-year increase of 27% and a quarter-on-quarter increase of 13%. Sales of Blackwell workstations drove growth, but consumer PCs were impacted by rising memory and system prices, partially offsetting the growth.

02 Blackwell Ultra Volume Production, Vera Rubin Fully Operational

NVIDIA is advancing its product roadmap from single GPUs to complete computing platforms.

In the second fiscal quarter, Blackwell Ultra became a significant driver of growth in the data center business. NVIDIA stated that data center revenue growth for the quarter mainly stemmed from the large-scale deployment of the Blackwell Ultra infrastructure. As cloud service providers and AI firms continue to build large-scale AI computing clusters, Blackwell is entering a broader commercial deployment phase.

At the same time, NVIDIA has begun preparing for the next generation of product cycles. In the second fiscal quarter, the company announced that the Vera Rubin platform has been fully launched, and related rack systems are running on partner cloud platforms such as CoreWeave and Google Cloud.

The Rubin platform includes not only GPUs but also covers CPUs, networking, software, and system-level solutions. Among them, the Vera CPU is the first CPU designed by NVIDIA for AI agents, which is planned to be adopted by leading technology providers worldwide.

Additionally, NVIDIA announced that the NVIDIA Groq 3 LPX for interactive AI inference has been fully launched. NVIDIA hopes to strengthen its competitive capabilities in real-time AI inference scenarios through products like Groq 3 LPX.

Besides hardware products, NVIDIA is also enhancing its software ecosystem.

In the second fiscal quarter, the company launched the DSX platform, providing infrastructure builders with a complete solution for designing, building, and operating large-scale AI factories. This platform integrates computing, networking, software, and systems to help clients build larger-scale AI infrastructures.

In terms of AI software, NVIDIA continues to expand the NVIDIA Agent Toolkit and enhance its development capabilities through PhysicsNeMo and the CUDA-X library. The company stated that it is working with global software platform providers to launch new software, open-source models, and partnership projects.

For NVIDIA, product competition is no longer limited to single chip performance, but rather revolves around a complete ecosystem spanning chips, networking, software, and systems. However, the market is still focused on the speed of transition from Blackwell to Rubin, and whether the next generation platform can continue to drive customers to increase their investments in AI infrastructure.

03 AI Infrastructure Enters Funding Phase, NVIDIA Takes on More Construction Roles

As the scale of AI data centers continues to expand, NVIDIA is increasingly involved in more infrastructure construction.

The second fiscal quarter financial report indicates that as of July 26, 2026, NVIDIA's future commitments amount to $360 billion. This includes $279 billion in supply and capacity commitments, $29 billion in cloud service agreements, $23 billion in capital expenditures, and $25 billion in equity investments.

These commitments are primarily related to the future expansion of AI infrastructure. Among them, the most notable is NVIDIA's participation in the SB Energy Ohio PORTS-Pike project.

NVIDIA stated that the company provides credit support for SB Energy's technology park in Ohio, which initially involves around 4.25GW of land, electricity, and facility construction, used to host OpenAI's NVIDIA infrastructure. The guarantee obligations provided by NVIDIA can reach up to $105 billion and will be implemented in phases after conditions such as the data center reaching serviceable status have been met.

At the same time, NVIDIA is promoting larger-scale capital investment in AI infrastructure. The company has announced strategic partnerships with institutions like Apollo, BlackRock, Blackstone, Brookfield, Goldman Sachs, and KKR, aiming to mobilize over $500 billion in third-party capital for AI infrastructure construction in the future.

Jensen Huang believes that the construction of AI infrastructure is entering a new phase, and substantial capital investments will be needed in the future to support the development of AI model training, inference, and more applications.

However, as NVIDIA participates in more infrastructure projects, the market is also starting to pay attention to the capital pressures brought by this model.

As of the end of the second fiscal quarter, NVIDIA had a total of $56.6 billion in cash, cash equivalents, and marketable debt securities. At the same time, the company issued $25 billion in senior unsecured notes for general corporate purposes in the second fiscal quarter. NVIDIA stated that the company’s financial position remains healthy, and future investments will mainly focus on supporting supply chains, infrastructure, and long-term growth needs.

04 Q3 Revenue Expected to Exceed $100 Billion, Competitive Pressure Begins to Emerge

For the next quarter, NVIDIA has provided further growth expectations.

The company expects third-quarter revenue for the fiscal year 2027 to reach $108 billion, with a variation of 2%; it forecasts a gross margin of 74% for both GAAP and Non-GAAP measures. NVIDIA also emphasizes that this guidance does not include any revenue from data center computing in China.

Compared to the second quarter’s revenue of $96.2 billion, NVIDIA expects to maintain growth in the third quarter. However, the market's focus has shifted from quarterly growth to long-term competitive landscape.

Currently, competition in the AI chip market is expanding. NVIDIA emphasized in its financial report that the company is maintaining its advantage through a complete computing platform, including processors, interconnection technology, software, algorithms, systems, and services. The company hopes to meet AI training and inference needs through this entire ecosystem.

At the same time, competitors are accelerating their layouts. AMD continues to launch data center products, while Google is also developing self-researched TPU chips. Major technology companies are both important customers of NVIDIA and are investing resources to develop their own computing platforms.

Investors are particularly focused on the development of the AI inference market. As AI applications increase, computing demand is expanding from model training to inference services. NVIDIA aims to maintain its market leadership by strengthening inference capabilities through the Vera Rubin platform, Groq 3 LPX, and its software ecosystem.

However, future growth still needs to address several questions: Can Blackwell Ultra and the Rubin platform continue to drive customers to increase their purchases? Can AI infrastructure investment maintain the current pace? And as clients increase their self-developed chips, will NVIDIA's share in the AI computing market be affected?

The $96.2 billion revenue is another milestone for NVIDIA in the AI wave.

For NVIDIA, the record financial data demonstrates the success of the past cycle, while the next stage of challenge is how to maintain its core position as the AI industry enters a larger-scale construction phase.