NVIDIA CORP (NVDA)

Business overview

Business Our Company NVIDIA pioneered accelerated computing to help solve the most challenging computational problems. NVIDIA is now a data center scale AI infrastructure company reshaping all industries. Our technology stack includes the foundational NVIDIA CUDA development platform that runs on all NVIDIA GPUs, as well as hundreds of domain-specific software libraries, frameworks, algorithms, software development kits, or SDKs, and application programming interfaces, or APIs. This deep and broad software stack accelerates the performance and facilitates the deployment of NVIDIA accelerated computing for computationally intensive workloads such as artificial intelligence, or AI, model training and inference, data analytics, scientific computing, robotics, and 3D graphics, with vertical-specific optimizations to address industries ranging from healthcare and telecom to automotive and manufacturing.

Introduced with the Blackwell architecture, our data-center-scale offerings feature extreme co-design where the infrastructure’s chips, networking, systems, software, and algorithms are holistically architected and optimized to maximize performance and scale. Hundreds of thousands of GPUs can be interconnected to function as a single giant computer. This type of data center architecture and scale is needed for the development and deployment of modern AI and accelerated computing applications. The GPU was initially used to simulate human imagination, enabling the virtual worlds of video games and films. Today, it also simulates human intelligence, enabling a deeper understanding of language, science, and the physical world. Its parallel processing capabilities, supported by tens of thousands of computing cores, are essential for deep learning algorithms.

This form of AI, in which software writes itself by learning from large amounts of data, can serve as the brain of computers, robots, and self-driving cars that can perceive, understand and reason about the world. GPU-powered AI solutions are being developed by thousands of enterprises to deliver services and products that would have been immensely difficult or even impossible with traditional coding. Examples include generative AI, which can create new content such as text, code, images, audio, video, molecule structures, and recommendation systems; and agentic AI where systems of AI models work in concert to automatically complete a task. NVIDIA has a platform strategy, bringing together hardware, systems, software, algorithms, libraries, AI models and training data sets, and services to create unique value for the markets we serve.

While the computing requirements of these end markets are diverse, we address them with a unified underlying programmable architecture allowing us to support several multi-billion-dollar end markets with the same underlying technology by using a variety of software stacks developed either internally or by third-party developers and partners. The large and growing number of developers and installed base across our platforms strengthens our ecosystem and increases the value of our platform for our customers. Innovation is at our core. We have invested over $76. 7 billion in research and development since our inception, yielding inventions that are essential to modern computing. Our invention of the GPU in 1999 sparked the growth of the PC gaming market and redefined computer graphics.

With our introduction of CUDA in 2006, we opened the parallel processing capabilities of our GPU to a broad range of compute-intensive applications, paving the way for the emergence of modern AI. In 2012, the AlexNet neural network, trained on NVIDIA GPUs, won the ImageNet computer image recognition competition, marking the “Big Bang” moment of AI. We introduced our first Tensor Core GPU in 2017, built from the ground-up for the new era of AI, and our first autonomous driving system-on-chips, or SoC, in 2018. Our acquisition of Mellanox in 2020 expanded our offerings to include networking, enabled our platforms to be data center scale, and led to the introduction of a new processor class – the data processing unit, or DPU.

Over the past 5 years, we have built full software stacks that run on top of our GPUs and CUDA to bring AI to the world’s largest industries, including NVIDIA DRIVE stack for autonomous driving, Clara for healthcare, Omniverse for physical AI applications, and NVIDIA AI Enterprise software – essentially an operating system for enterprise AI applications. In 2023, we introduced our first data center CPU, Grace, built for giant-scale AI and high-performance computing, or HPC. In 2024, we launched the NVIDIA Blackwell architecture – connecting 36 Grace CPUs and 72 Blackwell GPUs in a data center scale, liquid-cooled design – for real-time trillion-parameter inference and training. In fiscal year 2026, we launched and scaled the NVIDIA Blackwell Ultra platform, optimized for agentic, reasoning, and physical AI. […]

Management discussion and analysis

Management's Discussion and Analysis of Financial Condition and Results of Operations The following discussion and analysis of our financial condition and results of operations should be read in conjunction with “Item 1A. Risk Factors,” our Consolidated Financial Statements and related Notes thereto, as well as other cautionary statements and risks described elsewhere in this Annual Report on Form 10-K, before deciding to purchase, hold, or sell shares of our common stock. Overview Our Company and Our Businesses NVIDIA pioneered accelerated computing to help solve the most challenging computational problems. Since our original focus on PC graphics, we have expanded to several other large and important computationally intensive fields. Fueled by the sustained demand for exceptional 3D graphics and the scale of the gaming market, NVIDIA has leveraged its GPU architecture to create platforms for scientific computing, AI, data science, autonomous vehicles, robotics, and digital twin applications.

NVIDIA is now a data center scale AI infrastructure company reshaping all industries. Our two operating segments are "Compute & Networking" and "Graphics." Refer to Note 16 of the Notes to the Consolidated Financial Statements in Part IV, Item 15 of this Annual Report on Form 10-K for additional information. Headquartered in Santa Clara, California, NVIDIA was incorporated in California in April 1993 and reincorporated in Delaware in April 1998. Recent Developments, Future Objectives and Challenges Revenue growth in fiscal year 2026 was driven by data center compute and networking platforms for accelerated computing and AI solutions. Our Blackwell architectures represented the majority of our Data Center revenue.

The availability of data centers, energy, and capital to support the buildout of NVIDIA AI infrastructure by our customers and partners is crucial, and any shortage of these or other necessary resources could impact our future revenue and financial performance. Expanding energy capacity to meet demand is a complex, multi-year process that involves significant regulatory, technical, and construction challenges. In addition, access to capital can be particularly constrained for less-capitalized companies, which may face difficulties securing financing for large-scale infrastructure projects. These limitations could delay customer and partner deployments or reduce the scale of accelerated computing and AI adoption. We continue to execute Data Center compute product introductions, bringing new advanced architectures on a one-year product cadence, including our Rubin platform.

We began shipping production units of our new Blackwell Ultra platforms including GB300 in the second quarter of fiscal year 2026. The complexity of our product transitions and sophisticated system configurations has and may in the future cause delays in production and create challenges in managing supply and demand. This could further result in revenue volatility, quality issues, increased inventory provisions, decreases in product yields and higher material costs, and/or increased warranty costs. Customers may postpone purchasing new architectures or may adopt new technologies more gradually than anticipated, affecting our revenue timing and supply chain expenses. In April 2025, the USG informed us that a license is required for exports of our H20 product into the China market.

As a result of these requirements, we incurred a $4. 5 billion charge in the first quarter of fiscal year 2026 associated with H20 for excess inventory and purchase obligations, as the demand for H20 diminished. In August 2025, the USG granted licenses that would allow us to ship certain H20 products to certain China-based customers. We generated approximately $60 million in H20 revenue under those licenses. In February 2026, the USG granted a license that would allow us to ship small amounts of H200 products to specific China-based customers. To date, we have not generated any revenue under the H200 licensing program, and do not yet know whether any imports will be allowed into China.

The license requires that the H200s go through an inspection process in the United States prior to any shipment to the customer. As a result, any H200 shipped under the new licensing program will be subject to a 25% tariff upon importation into the United States. The recent rise in high-quality open-source foundation models is making advanced AI capabilities broadly accessible. Open-source AI is dependent on developer adoption and if deployed on our competitors’ platforms, it could reduce demand for our products and services. While currently our supply chain is mainly concentrated in Asia, we are expanding into the U. S. and Latin America. These moves are expected to strengthen our supply chain, add resiliency and redundancy, and meet the growing demand for AI infrastructure. […]

Key risk disclosures

Risk Factors – Risks Related to Regulatory, Legal, Our Stock, and Other Matters” for a discussion of this potential impact. Compliance with laws, rules, and regulations has not otherwise had a material effect upon our capital expenditures, results of operations, or competitive position and we do not currently anticipate material capital expenditures for environmental control facilities. Compliance with existing or future governmental regulations, including, but not limited to, those pertaining to IP ownership and infringement, taxes, import and export requirements and tariffs, anti-corruption, business acquisitions, foreign exchange controls and cash repatriation restrictions, data privacy requirements, competition and antitrust, advertising, employment, product regulations, cybersecurity, environmental, health and safety requirements, the responsible use of AI, climate change, cryptocurrency, and consumer laws, could further increase our costs, impact our competitive position, and otherwise may have a material adverse impact on our business, financial condition and results of operations in subsequent periods.

Refer to “Item 1A. Risk Factors” for a discussion of these potential impacts. Human Capital Management As of the end of fiscal year 2026, we had approximately 42,000 employees in 38 countries; 31,000 were engaged in research and development and 11,000 were engaged in sales, marketing, operations, and administrative positions. To execute our business strategy successfully, we focus on recruiting, developing, and retaining top global talent. Within our workforce, more than 80 percent have technical roles and more than half of the workforce hold an advanced degree. Our employees also help to surface top talent, with over 40 percent of our new hires in fiscal year 2026 coming from employee referrals.

In fiscal year 2026, our turnover rate was 3. 7 percent. We invest in employee development through on-the-job trainings and tuition reimbursement programs. Our compensation and benefits are designed to reward performance and align employee interests with those of our shareholders through equity participation and comprehensive health and financial wellness programs. We also utilize employee listening systems to gather feedback and maintain an inclusive culture where hiring and promotions are based on merit. Information About Our Executive Officers The following sets forth certain information regarding our executive officers, their ages, and positions as of February 20, 2026: Name Age Position Jen-Hsun Huang 63 President and Chief Executive Officer Colette M.

Kress 58 Executive Vice President and Chief Financial Officer Ajay K. Puri 71 Executive Vice President, Worldwide Field Operations Debora Shoquist 71 Executive Vice President, Operations Timothy S. Teter 59 Executive Vice President and General Counsel Jen-Hsun Huang co-founded NVIDIA in 1993 and has served as our President, Chief Executive Officer, and a member of the Board of Directors since our inception. From 1985 to 1993, Mr. Huang was employed at LSI Logic Corporation, a computer chip manufacturer, where he held a variety of positions including as Director of Coreware, the business unit responsible for LSI's SOC. From 1983 to 1985, Mr.

Huang was a microprocessor designer for AMD, a semiconductor 11 company. Mr. Huang holds a B. S. E. E.

degree from Oregon State University and an M. S. E. E. degree from Stanford University. Colette M.

Kress joined NVIDIA in 2013 as Executive Vice President and Chief Financial Officer. Prior to NVIDIA, Ms. Kress most recently served as Senior Vice President and Chief Financial Officer of the Business Technology and Operations Finance organization at Cisco Systems, Inc. , a networking equipment company, since 2010. At Cisco, Ms. Kress was responsible for financial strategy, planning, reporting and business development for all business segments, engineering and operations.

From 1997 to 2010 Ms. Kress held a variety of positions at Microsoft, a software company, including, beginning in 2006, Chief Financial Officer of the Server and Tools division, where Ms. Kress was responsible for financial strategy, planning, reporting and business development for the division. Prior to joining Microsoft, Ms. Kress spent eight years at Texas Instruments Incorporated, a semiconductor company, where she held a variety of finance positions. Ms.

Kress holds a B. S. degree in Finance from University of Arizona and an M. B. A. degree from Southern Methodist University.

Ajay K. Puri joined NVIDIA in 2005 as Senior Vice President, Worldwide Sales and became Executive Vice President, Worldwide Field Operations in 2009. Prior to NVIDIA, he held positions in sales, marketing, and general management over a 22-year career at Sun Microsystems, Inc. , a computing systems company. Mr. Puri previously held marketing, management consulting, and product development positions at Hewlett-Packard, an information technology company, Booz Allen Hamilton Inc.

, a management and technology consulting company, and Texas Instruments Incorporated. Mr. Puri holds a B. S. E. E. degree from the University of Minnesota, an M. S. E. E. […]

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