NVIDIA Corporation provides graphics, and compute and networking solutions in the United States, Taiwan, China, and internationally. The company's Graphics segment offers GeForce GPUs for gaming and PCs, the GeForce NOW game streaming service and related infrastructure, and solutions for gaming platforms; Quadro/NVIDIA RTX GPUs for enterprise workstation graphics; vGPU software for cloud-based visual and virtual computing; automotive platforms for infotainment systems; and Omniverse software for building 3D designs and virtual worlds. Its Compute & Networking segment provides Data Center platforms and systems for AI, HPC, and accelerated computing; Mellanox networking and interconnect solutions; automotive AI Cockpit, autonomous driving development agreements, and autonomous vehicle solutions; cryptocurrency mining processors; Jetson for robotics and other embedded platforms; and NVIDIA AI Enterprise and other software. The company's products are used in gaming, professional visualization, datacenter, and automotive markets. NVIDIA Corporation sells its products to original equipment manufacturers, original device manufacturers, system builders, add-in board manufacturers, retailers/distributors, independent software vendors, Internet and cloud service providers, automotive manufacturers and tier-1 automotive suppliers, mapping companies, start-ups, and other ecosystem participants. It has a strategic collaboration with Kroger Co. NVIDIA Corporation was incorporated in 1993 and is headquartered in Santa Clara, California.
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The Intel of the AI era, providing the essential processing power for artificial intelligence and high-performance computing.
The Qualcomm for AI, specializing in the advanced chips and software platforms that power intelligent systems.
The Caterpillar for the AI gold rush, supplying the critical tools and infrastructure needed to build and train artificial intelligence models.
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Here are NVIDIA's major products:
- GeForce GPUs: Graphics processing units designed for high-performance PC gaming and consumer applications.
- NVIDIA RTX / Quadro Professional GPUs: High-performance graphics cards and platforms tailored for professional visualization, content creation, design, and engineering workstations.
- Data Center GPUs (e.g., NVIDIA H100, A100): Advanced GPUs specifically engineered for artificial intelligence, machine learning, and high-performance computing workloads in data centers.
- NVIDIA AI Software Platform: A comprehensive suite of software, libraries (like CUDA, cuDNN), and developer tools that optimize and accelerate AI and deep learning applications on NVIDIA GPUs.
- NVIDIA Mellanox Networking Products: High-performance InfiniBand and Ethernet networking solutions critical for connecting computing infrastructure in data centers and supercomputers.
- NVIDIA DRIVE Platform: An end-to-end hardware and software platform designed to enable autonomous vehicles, robotics, and intelligent machines.
- GeForce NOW: A cloud-based gaming service that streams a library of PC games to various devices, leveraging NVIDIA's cloud GPU infrastructure.
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NVIDIA (NVDA) primarily sells its products and platforms to other companies (B2B). Its major customers are diverse and span several industries, leveraging NVIDIA's GPUs, networking solutions, and software platforms for various applications including AI, data centers, gaming, professional visualization, and automotive.
Here are some of NVIDIA's major customer companies:
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Cloud Service Providers (CSPs) and Hyperscalers: These companies purchase NVIDIA's data center GPUs (e.g., H100, A100) and networking solutions in massive quantities to power their AI infrastructure, cloud computing services, and large-scale internal operations.
- Microsoft (Azure) - MSFT
- Amazon (AWS) - AMZN
- Google (Google Cloud) - GOOGL
- Oracle (Oracle Cloud Infrastructure - OCI) - ORCL
- Meta Platforms (for internal AI infrastructure) - META
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Server and System Manufacturers: These companies integrate NVIDIA's GPUs, chipsets, and networking components into servers, workstations, and high-performance computing systems, which they then sell to enterprises, research institutions, and governments.
- Dell Technologies - DELL
- Hewlett Packard Enterprise (HPE) - HPE
- Super Micro Computer - SMCI
- Lenovo (0992.HK / LNVGY on OTC market)
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PC Original Equipment Manufacturers (OEMs): These companies incorporate NVIDIA's GeForce GPUs (for gaming and consumer PCs) and NVIDIA RTX GPUs (for professional workstations) into their desktop and laptop computers.
- HP Inc. - HPQ
- Dell Technologies - DELL
- Lenovo (0992.HK / LNVGY on OTC market)
- Acer
- ASUS
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- Taiwan Semiconductor Manufacturing Company (TSM)
- SK Hynix (000660.KS)
- Samsung Electronics (005930.KS)
- Micron Technology (MU)
- ASE Technology Holding Co. Ltd. (ASX)
- Amkor Technology (AMKR)
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Jensen Huang, Founder, President & CEO
Jensen Huang co-founded NVIDIA in 1993 and has served as its President and CEO since its inception. Before founding NVIDIA, Huang worked at Advanced Micro Devices for approximately a year and then at LSI Logic Corporation, where he rose to become a division director. He holds a bachelor's degree in electrical engineering from Oregon State University and a master's degree in electrical engineering from Stanford University.
Colette Kress, EVP & Chief Financial Officer
Colette Kress joined NVIDIA in September 2013 as Executive Vice President and Chief Financial Officer, overseeing the company's financial strategy and operations. Prior to NVIDIA, she accumulated over two decades of experience in senior finance roles at major technology corporations. She spent 13 years at Microsoft, including four years as CFO of the Server and Tools division, and three years at Cisco as Senior Vice President and CFO of the Business Technology and Operations Finance organization. Kress began her career at Texas Instruments and has played a key financial role in strategic acquisitions for NVIDIA, such as Mellanox.
Chris A. Malachowsky, Founder & NVIDIA Fellow
Chris A. Malachowsky co-founded NVIDIA in 1993 and brings over 40 years of industry experience. He serves as a member of the executive staff and has been instrumental in managing, defining, and driving NVIDIA's core technologies. Malachowsky has led numerous functions within the company, including IT, operations, and all facets of product engineering.
Jay Puri, EVP, Worldwide Field Operations
Jay Puri leads NVIDIA's global sales, marketing, and customer engagement strategy, a role he has held since joining the company in 2005. Before his tenure at NVIDIA, Puri spent more than two decades in various sales, marketing, and management positions at Sun Microsystems, including serving as Senior Vice President of its Asia-Pacific Group. His prior experience also includes roles at Hewlett-Packard, Booz Allen, and Texas Instruments.
Debora Shoquist, EVP, Operations
Debora Shoquist manages NVIDIA's global operations, having joined the company in 2007. With over 20 years of experience in operations management, she previously held leadership roles at companies such as Quantum and Coherent.
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Major cloud service providers and hyperscalers (e.g., Google with TPUs, Amazon with Inferentia and Trainium, Microsoft with Maia and Athena, and Meta with MTIA) are heavily investing in and deploying their own custom-designed AI accelerators (ASICs). These in-house chips are developed to optimize for their specific AI workloads, offering potential cost efficiencies and performance advantages within their own data centers, thereby reducing their reliance on NVIDIA's GPUs for a portion of their AI infrastructure needs.
AMD's growing competitiveness in the high-performance AI accelerator market, particularly with its Instinct MI300X and MI300A chips. These products are being increasingly adopted by major cloud providers and enterprises as a viable and high-performance alternative to NVIDIA's H100 and H200 GPUs, offering significant memory capacity and aggregate bandwidth at competitive price points. This emergence of a strong alternative directly challenges NVIDIA's near-monopoly in the lucrative AI training and inference hardware segment.
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NVIDIA's main products and services address several significant and growing markets globally. The estimated addressable markets for their key segments are as follows:
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Data Center / Artificial Intelligence (AI):
- NVIDIA's CEO anticipates the Total Addressable Market (TAM) for its data center segment to reach approximately $1 trillion by 2028 globally.
- The global AI semiconductor market is projected to grow to $273 billion by 2029.
- The data center GPU market was valued at $16.84 billion in 2024 and is projected to reach $123.61 billion by 2032 globally, with North America holding a 41% share, Europe 28%, and Asia-Pacific 23%.
- The global AI infrastructure market was estimated at $87.6 billion in 2025 and is projected to nearly double by 2030.
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Gaming:
- The global gaming GPU market was valued at $72.3 billion in 2024, is expected to rise to $87.57 billion in 2025, and is projected to reach $405.58 billion by 2033.
- Another estimate indicates the global gaming GPU market is expected to be worth around $144.9 billion by 2034, growing from $5.5 billion in 2024.
- The U.S. gaming GPU market reached a valuation of $1.55 billion in 2024.
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Professional Visualization:
- The global data visualization tools market size is projected to expand from $8.55 billion in 2024 to $9.46 billion in 2025. North America was the largest region in this market in 2024.
- The global advanced visualization market size was $3.9 billion in 2024 and is expected to reach $8.8 billion by 2032.
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Automotive:
- NVIDIA estimates the autonomous machine market, which encompasses automotive, as a $300 billion opportunity over the long term globally.
- The combined value of automotive Advanced Driver-Assistance Systems (ADAS) and infotainment systems is expected to exceed $100 billion by 2030 globally.
- The global automotive AI hardware market was valued at approximately $15 billion and is projected to surge to $40 billion by 2034.
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NVIDIA Corporation (NVDA) is expected to experience significant revenue growth over the next 2-3 years, driven by several key factors:
- Continued Robust Demand in Data Center and AI Infrastructure: The escalating global investment in artificial intelligence (AI) infrastructure is a primary catalyst for NVIDIA's growth. The company's GPUs, including the Hopper and H200 series, and the newer Blackwell architecture, are critical for training and deploying AI models across hyperscale cloud service providers (CSPs) and enterprise data centers. NVIDIA's leadership in this segment is reinforced by the ongoing build-out of "AI factories" and "gigafactories" worldwide, which heavily rely on its computing platforms. The demand for NVIDIA Hopper and H200 has been exceptional, with Blackwell production already in full gear and exceeding expectations. This trend is expected to continue as companies race to scale infrastructure for next-generation AI models.
- Introduction of Next-Generation GPU Architectures: NVIDIA's continuous innovation in GPU technology, with the launch of new architectures like Blackwell and the anticipated Rubin platform, is a significant driver. The Blackwell architecture, already in production, has quickly ramped up, delivering substantial revenue and expanding customer adoption due to its enhanced performance and scaling capabilities for AI workloads. The upcoming Rubin platform, expected to ship starting in 2026, will further drive upgrade cycles and new deployments as it succeeds Blackwell, offering even greater advancements in AI processing.
- Expansion into Emerging High-Growth Verticals: NVIDIA is actively diversifying its revenue streams by expanding into new, high-growth market segments. Key areas include the automotive sector, particularly for autonomous driving technologies, and the burgeoning fields of robotics and industrial AI. The NVIDIA Omniverse platform, designed for developers to build, train, and operate industrial AI and robotics, is accelerating adoption in these areas, triggered by breakthroughs in physical AI and foundation models that understand the physical world. Additionally, sovereign AI initiatives globally, where countries invest in developing their own national AI infrastructure, present substantial opportunities for NVIDIA's GPU technologies.
- Growth of High-Performance Networking Solutions: The increasing complexity and scale of AI clusters necessitate advanced networking solutions, which is a growing revenue driver for NVIDIA. The company's InfiniBand and Spectrum-X Ethernet switches, SmartNICs, and BlueField DPUs are crucial for connecting thousands of GPUs to handle demanding AI workloads efficiently. Demand for networking is strong and growing, with Spectrum-X Ethernet for AI revenue increasing significantly year-over-year and a building pipeline with multiple CSPs and consumer internet companies planning large cluster deployments. This segment is integral to the overall AI infrastructure and ensures optimal performance of NVIDIA's GPU offerings.
- Accelerated Growth in Software and Services Revenue: Beyond its hardware prowess, NVIDIA's software ecosystem and services are becoming increasingly important revenue contributors. Products like NVIDIA AI Enterprise provide a full-stack offering that enhances the value of its hardware and fosters customer loyalty. The company expects its AI Enterprise full-year revenue to more than double, with overall software, service, and support revenue annualizing at significant and growing rates. This focus on software creates recurring revenue streams and deepens customer lock-in by providing a comprehensive platform for AI development and deployment.
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Share Repurchases
- NVIDIA's board of directors approved an additional $60 billion share repurchase authorization on August 26, 2025, with no expiration.
- As of the end of the second quarter of fiscal 2026 (July 27, 2025), $14.7 billion remained under NVIDIA's existing share repurchase authorization.
- In fiscal year 2025, NVIDIA repurchased 310 million shares of its common stock for $34.0 billion.
Outbound Investments
- NVIDIA announced a $100 billion partnership with OpenAI in September 2025, where NVIDIA will invest, and OpenAI will use most of the funds to lease NVIDIA chips.
- In September 2025, NVIDIA agreed to invest $5 billion in Intel common stock.
- NVIDIA made a $2 billion equity investment in xAI in October 2025 as part of xAI's $20 billion funding round.
Capital Expenditures
- NVIDIA's capital expenditures for fiscal year 2025 were $3.2 billion, primarily focused on expanding Blackwell accelerator production and AI infrastructure.
- Capital expenditures are forecast to be $6.514 billion for the upcoming fiscal year (fiscal 2026).
- NVIDIA's trailing twelve-month (TTM) annual capital expenditures peaked at $5.012 billion in July 2025.
