Wall Street's Imagination Can't Keep Up with NVIDIA's 'Speed'

By Su Yang, Tencent Technology

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

On August 26, local time in the U.S., NVIDIA announced its second-quarter results for the fiscal year 2027, which ended on July 26, 2026. The 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 reached $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 the previous quarter's revenue of $81.615 billion, NVIDIA continues to break growth records. In the same quarter last year, the company's revenue was only $46.743 billion, achieving nearly a doubling in just one year.

After the earnings report was released, NVIDIA's stock price initially fell about 1.3% in after-hours trading, then surged over 4%. This reflects the divergence and changes in market focus: previously, investors were concerned about whether NVIDIA could continue to exceed expectations; now they are more interested in how long AI infrastructure construction can sustain, and whether the next generation of chips and new business models can support future growth.

From a profitability perspective, NVIDIA still maintains a very high level.

In the second quarter, the company's operating profit reached $63.734 billion, a year-on-year increase of 124%; on a Non-GAAP basis, net profit was $53.954 billion, a year-on-year increase of 118%. 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 quarter's 74.9%.

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 equals revenue."

Currently, more AI labs and startups are rapidly expanding, and new directions such as open-source model ecosystems and physical AI are also beginning to develop, with the entire AI industry entering a broader construction cycle.

At the same time, NVIDIA continues to increase shareholder returns. In the second quarter, the company returned about $26 billion to shareholders through stock buybacks and cash dividends. As of the end of the quarter, the company's stock buyback authorization still had about $99 billion remaining.

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

The core driver of NVIDIA's current growth remains its data center business.

In the second 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 almost all of the company's revenue growth. As global enterprises and cloud service providers continue to invest in AI infrastructure, the demand for NVIDIA GPUs remains high.

In the first quarter, NVIDIA adjusted the way it discloses data center business, categorizing customers into two main 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.

Meanwhile, revenue from AI cloud, 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 covers AI-native companies, enterprise customers, sovereign AI customers, and the massive computing demand from those using AI cloud services.

The new classification shows that the demand for AI computing is spreading from a few cloud giants to enterprises, governments, and more industry scenarios. However, investors are still focused on the profitability and long-term demand behind different customer types, not just the growth in order size.

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

NVIDIA stated that in the second quarter, revenue from data center Hopper products shipped to mainland China accounted for less than 1% of data center revenue. Additionally, the company did not include any revenue from mainland China's data center computing in its third-quarter earnings outlook.

Aside from the data center business, revenue from edge computing in the second quarter reached $7.198 billion, a year-on-year increase of 27% and a quarter-on-quarter increase of 13%. Among them, sales of Blackwell workstations drove growth, but the consumer PC segment was affected by rising memory and system prices, partially offsetting the growth.

02 Blackwell Ultra Volume Production, Vera Rubin Fully Operational

NVIDIA is pushing its product line from a single GPU to a complete computing platform.

In the second quarter, Blackwell Ultra became an important factor driving growth in the data center business. NVIDIA stated that the growth in data center revenue for the quarter was mainly due to the large-scale deployment of Blackwell Ultra infrastructure. As cloud service providers and AI companies 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 quarter, the company announced that the Vera Rubin platform has been fully operational, with related rack systems running on partner cloud platforms such as CoreWeave and Google Cloud.

The Rubin platform includes not only GPUs but also CPUs, networks, software, and system-level solutions. Among them, the Vera CPU is NVIDIA's first CPU designed 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 produced. NVIDIA hopes to strengthen its competitive ability 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 quarter, the company launched the DSX platform, providing a complete solution for infrastructure builders to design, build, and operate large-scale AI factories. This platform integrates computing, networking, software, and systems to help customers build larger-scale AI infrastructure.

In AI software, NVIDIA continues to expand the NVIDIA Agent Toolkit and enhance development capabilities through PhysicsNeMo and the CUDA-X library. The company stated 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 the performance of individual chips but revolves around the complete ecosystem from chips, networks, and software to systems. However, the market is still focused on the speed of transition from Blackwell to Rubin and whether the new generation platform can continue to drive customers to expand their AI infrastructure investments.

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

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

The second-quarter financial report showed that as of July 26, 2026, NVIDIA's future commitment amount reached $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 mainly related to the future expansion of AI infrastructure. Among them, the most notable is NVIDIA's participation in the SB Energy PORTS-Pike project in Ohio.

NVIDIA stated that it provides credit support for SB Energy's technology park in Ohio, with the initial phase involving approximately 4.25GW of land, power, and factory construction to host NVIDIA's infrastructure for OpenAI. The guarantee obligations provided by NVIDIA can reach up to $105 billion and will take effect in phases after the data center reaches a serviceable state.

At the same time, NVIDIA is promoting larger-scale capital investment in AI infrastructure. The company has announced strategic partnerships with institutions such as 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 AI infrastructure construction is entering a new phase, requiring substantial capital investment to support the development of AI model training, inference, and more applications.

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

As of the end of the second quarter, NVIDIA's cash, cash equivalents, and marketable securities totaled $56.6 billion. Meanwhile, the company issued $25 billion in senior unsecured notes in the second quarter for general corporate purposes. NVIDIA stated that its financial condition remains sound, 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 Show

For the next quarter, NVIDIA has provided expectations for continued growth.

The company expects revenue for the third quarter of fiscal year 2027 to reach $108 billion, with a fluctuation of 2%; it expects gross margins under both GAAP and Non-GAAP to be 74%. NVIDIA also emphasized 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, market 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, interconnect technologies, software, algorithms, systems, and services. The company hopes to meet AI training and inference needs through this entire ecosystem.

However, at the same time, competitors are accelerating their layouts. AMD continues to launch data center products, and Google is also developing its self-developed TPU chips. Large technology companies are both important customers of NVIDIA while also 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 through the Vera Rubin platform, Groq 3 LPX, and software ecosystem to strengthen its inference capabilities.

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

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

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