With its revenue doubling and data center business surging by 117%, how long can NVIDIA maintain its breakneck growth?

NVIDIA has once again delivered a stunning financial report, with revenue, operating profit and earnings per share all hitting record highs.

On local time August 26, NVIDIA announced its financial results for the second quarter of fiscal 2027, which ended on July 26, 2026. The earnings report shows that NVIDIA's revenue in the quarter reached 96.221 billion US dollars, up 106% year-on-year and 18% quarter-on-quarter; net profit reached 59.688 billion US dollars, up 126% year-on-year; diluted earnings per share was 2.46 US dollars, up 128% year-on-year.

Compared with the revenue of 81.615 billion US dollars in the previous quarter, NVIDIA continues to refresh its growth record. In the same period of last year, the company's single-quarter revenue was only 46.743 billion US dollars, and it has almost doubled its growth in one year.

However, the strong performance did not drive the stock price to continue rising. After the earnings report was released, NVIDIA's after-hours stock price fell by about 1.3% instead. This also reflects that the market focus is changing: in the past, investors were concerned about whether NVIDIA could continue to beat expectations, but now they are more concerned about how long the AI infrastructure construction can last, and whether the next-generation chips and new business models can support future growth.

In terms of profitability, NVIDIA still maintains an extremely high level.

In the second fiscal quarter, the company's operating profit reached 63.734 billion US dollars, up 124% year-on-year; on a Non-GAAP basis, net profit was 53.954 billion US dollars, up 118% year-on-year. In the same period, the company's gross margin reached 75%, higher than 72.4% in the same period last year, and slightly higher than 74.9% in the first fiscal quarter.

Jensen Huang, founder and CEO of NVIDIA, said: "Artificial intelligence has reached an inflection point. It is doing useful work, and its tokens are creating productivity and profitability. Now, computing is revenue."

At present, more AI labs and startups are expanding rapidly, and new directions such as the open-source model ecosystem and physical AI are also starting to develop. The entire AI industry is entering a broader construction cycle.

At the same time, NVIDIA continues to increase its efforts to return value to shareholders. In the second fiscal quarter, the company returned about 26 billion US dollars to shareholders through stock repurchases and cash dividends. As of the end of the quarter, the remaining authorized amount for the company's stock repurchase was about 99 billion US dollars.

01 Data Center Revenue Surges, AI Cloud Customers Grow Faster

The core driving NVIDIA's current round of growth is still the data center business.

In the second fiscal quarter, NVIDIA's data center revenue reached 89.023 billion US dollars, up 117% year-on-year and 18% quarter-on-quarter, contributing almost all of the company's revenue increment. As global enterprises and cloud service providers continue to invest in AI infrastructure construction, the demand for NVIDIA GPUs remains at a high level.

NVIDIA adjusted the disclosure method of its data center business in the first fiscal quarter, dividing customers into two major categories: Hyperscale and ACIE.

Among them, the revenue from Hyperscale customers reached 48.71 billion US dollars, up 102% year-on-year and 13% quarter-on-quarter, mainly from large public cloud and internet companies.

At the same time, the revenue from AI Cloud, Industrial and Enterprise (ACIE) customers reached 40.313 billion US dollars, up 138% year-on-year and 25% quarter-on-quarter. This business covers AI-native companies, enterprise customers, sovereign AI customers, and hyperscale computing demands using AI cloud services.

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

The Chinese mainland market remains an important variable in the earnings report.

NVIDIA stated that in the second fiscal quarter, the revenue from data center Hopper products shipped to the Chinese mainland accounted for less than 1% of the total data center revenue. Meanwhile, the company did not include any data center computing revenue from the Chinese mainland in its performance outlook for the third fiscal quarter.

In addition to the data center business, the edge computing business generated revenue of 7.198 billion US dollars in the second fiscal quarter, up 27% year-on-year and 13% quarter-on-quarter. Among them, the sales of Blackwell workstations drove the growth, but the consumer PC segment was affected by rising memory and system prices, which partially offset the growth.

02 Blackwell Ultra Volume Ramping Up, Vera Rubin Goes Into Full Production

NVIDIA is pushing to upgrade its product roadmap from a single GPU to a full computing platform.

In the second fiscal quarter, Blackwell Ultra became an important factor driving the growth of the data center business. NVIDIA stated that the growth of data center revenue in the quarter mainly came from the large-scale deployment of Blackwell Ultra infrastructure. As cloud service providers and AI enterprises continue to build large-scale AI computing clusters, Blackwell is entering a broader commercial deployment stage.

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

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

In addition, NVIDIA also announced that NVIDIA Groq 3 LPX for interactive AI inference has been fully put into production. NVIDIA hopes to strengthen its competitiveness in real-time AI inference scenarios through products such as 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 complete solution for designing, building and operating large-scale AI factories. This platform integrates computing, network, software and systems to help customers build larger-scale AI infrastructure.

In terms of AI software, NVIDIA continues to expand the NVIDIA Agent Toolkit, and enhances development capabilities through PhysicsNeMo and CUDA-X libraries. The company stated that it is cooperating with global software platform providers to launch new software, open-source models and partner programs.

For NVIDIA, product competition is no longer limited to the performance of a single chip, but unfolds around the complete ecosystem from chips, networks, software to systems. However, the market is still paying attention to the transition speed from Blackwell to Rubin, and whether the new generation platform can continue to drive customers to expand their investment in AI infrastructure.

03 AI Infrastructure Enters Financing Stage, NVIDIA Takes More Construction Roles

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

The second fiscal quarter earnings report shows that as of July 26, 2026, NVIDIA's future commitment amount reached 3600 billion US dollars, including 2790 billion US dollars in supply and capacity commitments, 290 billion US dollars in cloud service agreements, 230 billion US dollars in capital expenditures, and 250 billion US dollars in equity investments.

The above commitments are mainly related to the future expansion of AI infrastructure. Among them, the most concerned one is the SB Energy PORTS-Pike project in Ohio that NVIDIA participates in.

NVIDIA stated that it provides credit support for the tech park of SB Energy located in Ohio. The initial phase of the project involves the construction of about 4.25GW of land, power plants and factory buildings, which is used to host NVIDIA's infrastructure for OpenAI. The maximum guarantee obligation provided by NVIDIA reaches 1050 billion US dollars, and will take effect in phases after conditions such as the data center reaching a serviceable state are met.

At the same time, NVIDIA is promoting larger-scale capital investment in AI infrastructure. The company has announced the establishment of strategic partnerships with institutions including Apollo, BlackRock, Blackstone, Brookfield, Goldman Sachs and KKR, with the goal of mobilizing more than 5000 billion US dollars of third-party capital in the future for AI infrastructure construction.

Jensen Huang believes that the construction of AI infrastructure is entering a new stage, and a large amount of capital investment is 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 has begun to pay attention to the capital pressure brought by this model.

As of the end of the second fiscal quarter, NVIDIA's cash, cash equivalents and marketable debt securities totaled 56.6 billion US dollars. In the same period, the company issued 25 billion US dollars of senior unsecured notes in the second fiscal quarter for general corporate purposes. NVIDIA stated that the company's financial position remains robust at present, and future investments will mainly focus on supporting the supply chain, infrastructure and long-term growth needs.

04 Q3 Revenue Will Exceed 100 Billion US Dollars, Competitive Pressure Begins to Emerge

For the next quarter, NVIDIA has given an expectation of continued growth.

The company expects its revenue in the third quarter of fiscal 2027 to reach 108 billion US dollars, with a fluctuation range of ±2%; it expects the gross margin under both GAAP and Non-GAAP standards to be 74%. NVIDIA also emphasized that this guidance does not include any data center computing revenue from China.

Compared with the revenue of 96.2 billion US dollars in the second quarter, NVIDIA expects to maintain growth in the third quarter. However, the market focus has shifted from single-quarter growth to the long-term competitive landscape.

At present, competition in the AI chip market is expanding. NVIDIA emphasized in its earnings report that the company maintains its advantages through a complete computing platform, including processors, interconnection technologies, software, algorithms, systems and services. The company hopes to meet the needs of AI training and inference through this full set of ecosystems.

But at the same time, competitors are accelerating their layout. AMD continues to launch data center products, and Google is also developing self-developed TPU chips. Large technology companies are not only important customers of NVIDIA, but also investing resources to develop their own computing platforms.

Investors are particularly concerned about the development of the AI inference market. As AI applications increase, computing demand is expanding from model training to inference services. NVIDIA strengthens its inference capabilities through the Vera Rubin platform, Groq 3 LPX and software ecosystem, hoping to maintain its leading position in the market.

However, future growth still needs to answer several questions: whether Blackwell Ultra and Rubin platforms can continue to drive customers to increase procurement; whether AI infrastructure investment can maintain the current pace; and whether NVIDIA's share in the AI computing market will be affected as customers develop more self-designed chips.

Revenue of 96.2 billion US dollars is another milestone for NVIDIA in the AI wave.

For NVIDIA, the record-breaking financial data proves the success of the previous cycle, and the challenge in the next stage is how to maintain its core position after the AI industry enters a larger-scale construction phase.

Special translator Jin Lu also contributed to this article

This article is from "Tencent Tech", author: Su Yang, editor: Xu Qingyang, published with authorization from 36Kr.