NVIDIA Corporation (NVIDIA) operates as a full-stack computing infrastructure company with data-center-scale offerings that are reshaping industry.
The company’s full-stack includes the foundational CUDA programming model that runs on all NVIDIA GPUs, as well as hundreds of domain-specific software libraries, software development kits, or SDKs, and Application Programming Interfaces, or APIs. This deep and broad software stack accelerates the performance and eases the deployment of NVIDIA accel...
NVIDIA Corporation (NVIDIA) operates as a full-stack computing infrastructure company with data-center-scale offerings that are reshaping industry.
The company’s full-stack includes the foundational CUDA programming model that runs on all NVIDIA GPUs, as well as hundreds of domain-specific software libraries, software development kits, or SDKs, and Application Programming Interfaces, or APIs. This deep and broad software stack accelerates the performance and eases the deployment of NVIDIA accelerated computing for computationally intensive workloads, such as artificial intelligence, or AI, model training and inference, data analytics, scientific computing, and 3D graphics, with vertical-specific optimizations to address industries ranging from healthcare and telecom to automotive and manufacturing.
The company’s data-center-scale offerings consist of compute and networking solutions that can scale to tens of thousands of GPU-accelerated servers 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 applications.
NVIDIA has a platform strategy, bringing together hardware, systems, software, algorithms, libraries, and services to create unique value for the markets it serves. While the computing requirements of these end markets are diverse, the company addresses them with a unified underlying architecture leveraging its GPUs, networking, and software stacks. The programmable nature of the company’s architecture allows it 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 the company’s platforms strengthens its ecosystem and increases the value of its platform to its customers.
In 2023, the company introduced its first data center CPU, Grace, built for giant-scale AI and high-performance computing, or HPC. With a strong engineering culture, the company drives fast, yet harmonized, product and technology innovations in all dimensions of computing, including silicon, systems, networking, software, and algorithms. More than half of the company’s engineers work on software.
With support for more than 4,400 applications, NVIDIA computing enables some of the most promising areas of discovery, from climate prediction to materials science, and from wind tunnel simulation to genomics. Including GPUs and networking, NVIDIA powers over 75% of the supercomputers on the global TOP500 list, including 38 of the top 50 systems on the Green500 list.
Businesses
The company reports its business results in two segments.
The Compute & Networking segment includes the company’s Data Center accelerated computing platforms and AI solutions and software; networking; automotive platforms and autonomous and electric vehicle solutions; Jetson for robotics and other embedded platforms; and DGX Cloud computing services.
The Graphics segment includes 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; virtual GPU, or vGPU, software for cloud-based visual and virtual computing; automotive platforms for infotainment systems; and Omniverse Enterprise software for building and operating industrial AI and digital twin applications.
Markets
The company specializes in markets where its computing platforms can provide tremendous acceleration for applications. These platforms incorporate processors, interconnects, software, algorithms, systems, and services to deliver unique value. The company’s platforms address four large markets where its expertise is critical: Data Center, Gaming, Professional Visualization, and Automotive.
Data Center
The NVIDIA Data Center platform is focused on accelerating the most compute-intensive workloads, such as AI, data analytics, graphics, and scientific computing, delivering significantly better performance and power efficiency relative to conventional CPU-only approaches. It is deployed in cloud, hyperscale, on-premises, and edge data centers. The platform consists of compute and networking offerings typically delivered to customers as systems, subsystems, or modules, along with software and services.
The company’s compute offerings include supercomputing platforms and servers, bringing together its energy-efficient GPUs, CPUs, interconnects, and fully optimized AI and HPC software stacks. In addition, they include NVIDIA AI Enterprise software, its DGX Cloud service, and a growing body of acceleration libraries, APIs, SDKs, and domain-specific application frameworks.
The company’s networking offerings include end-to-end platforms for InfiniBand and Ethernet, consisting of network adapters, cables, DPUs, switch chips, and systems, as well as a full software stack. This has enabled the company to architect data center-scale computing platforms that can interconnect thousands of compute nodes with high-performance networking.
The company’s customers include the world’s leading public cloud and consumer internet companies, thousands of enterprises and startups, and public sector entities. The company works with industry leaders to help build or transform their applications and data center infrastructure. The company’s direct customers include original equipment manufacturers, or OEMs, original device manufacturers, or ODMs, system integrators, and distributors, with which it partners to help bring its products to market. The company also has partnerships in automotive, healthcare, financial services, manufacturing, retail, and technology, among others, to accelerate the adoption of AI.
At the foundation of the NVIDIA accelerated computing platform are its GPUs, which excel at parallel workloads, such as the training and inferencing of neural networks. They are available in the NVIDIA accelerated computing platform and in industry-standard servers from every major cloud provider and server maker. Beyond GPUs, the company’s data center platform expanded to include DPUs in fiscal year 2022 and CPUs in fiscal year 2024.
In addition to software delivered to customers as an integral part of the company’s data center computing platform, it offers paid licenses to NVIDIA AI Enterprise, a comprehensive suite of enterprise-grade AI software, and NVIDIA vGPU software for graphics-rich virtual desktops and workstations. The company also offers the NVIDIA DGX Cloud, a fully managed AI-training-as-a-service platform that includes cloud-based infrastructure and software for AI, customizable pretrained AI models, and access to NVIDIA experts.
In fiscal year 2025, the company launched the NVIDIA Blackwell architecture, a full set of data center-scale infrastructure that includes GPUs, CPUs, DPUs, interconnects, switch chips, systems, and networking adapters. Blackwell excels at processing cutting-edge generative AI and accelerated computing workloads with market-leading performance and efficiency. Offered in a number of configurations, it can address the needs of customers across industries and a diverse set of AI and accelerated computing use cases.
Gaming
The company’s gaming platforms leverage its GPUs and sophisticated software to enhance the gaming experience with smoother, higher-quality graphics. The company developed NVIDIA RTX to bring next-generation graphics and AI to games. NVIDIA RTX features ray tracing technology for real-time, cinematic-quality rendering. Ray tracing, which has long been used for special effects in the movie industry, is a computationally intensive technique that simulates the physical behavior of light to achieve greater realism in computer-generated scenes. NVIDIA RTX also features deep learning super sampling, or NVIDIA DLSS, the company’s AI technology that boosts frame rates while generating beautiful, sharp images for games. With an installed base of over 100 million AI-capable PCs, more than 700 RTX AI-enabled applications and games, and a robust suite of development tools, RTX is already the AI PC leader.
The company’s products for the gaming market include GeForce RTX and GeForce GTX GPUs for gaming desktop and laptop PCs, GeForce NOW cloud gaming for playing PC games on underpowered devices, as well as SoCs and development services for game consoles.
In fiscal year 2025, the company launched the NVIDIA Blackwell GeForce RTX 50 Series family of desktop and laptop GPUs. The Blackwell architecture introduced neural graphics, which combines AI models with traditional rendering to unlock a new era of graphics innovation. The RTX 50 Series also features the next generation of its DLSS technology powered for the first time by a transformer model architecture. Together, these technologies help deliver up to a 2x leap in performance and stunning visual realism for PC gamers, developers, and creatives.
Professional Visualization
The company serves the Professional Visualization market by working closely with independent software vendors, or ISVs, to optimize their offerings for NVIDIA GPUs. The company’s GPU computing platform enhances productivity and introduces new capabilities for critical workflows in many fields, such as design and manufacturing and digital content creation. Design and manufacturing encompass computer-aided design, architectural design, consumer-products manufacturing, medical instrumentation, and aerospace. Digital content creation includes professional video editing and post-production, special effects for films, and broadcast-television graphics. Additionally, the infusion of generative AI into an increasing number of applications is giving rise to the need for the enhanced AI processing capabilities of its RTX GPUs.
The NVIDIA RTX platform makes it possible to render film-quality, photorealistic objects and environments with physically accurate shadows, reflections, and refractions using ray tracing in real-time. Many leading 3D design and content creation applications developed by its ecosystem partners now support RTX, allowing professionals to accelerate and transform their workflows with NVIDIA RTX GPUs and software.
The company offers NVIDIA Omniverse as a development platform and operating system for building and running virtual world simulation applications, available as a software subscription for enterprise use and free for individual use. Industrial enterprises are adopting Omniverse’s 3D and simulation technologies to digitalize their complex physical assets, processes, and environments – building digital twins of factories, real-time 3D product configurators, testing and validating autonomous robots and vehicles, powered by NVIDIA accelerated computing infrastructure on-premises and in the cloud.
Automotive
The automotive segment consists of platform solutions for automated driving from the cloud to the car. Leveraging the company’s technology leadership in AI and building on its long-standing automotive relationships, the company is delivering a complete end-to-end solution for the AV market under the DRIVE Hyperion brand. The company has demonstrated multiple applications of AI within the car: AI can drive the car itself as a pilot in fully autonomous mode, or it can also be a co-pilot, assisting the human driver while creating a safer driving experience.
The company is working with several hundred partners in the automotive ecosystem, including automakers, truck makers, tier-one suppliers, sensor manufacturers, automotive research institutions, HD mapping companies, and startups, to develop and deploy AI systems for self-driving vehicles. The company’s unified AI computing architecture starts with training deep neural networks using its Data Center computing solutions, and then runs a full perception, fusion, planning, and control stack within the vehicle on the NVIDIA DRIVE Hyperion platform. DRIVE Hyperion consists of the high-performance, energy-efficient DRIVE AGX computing hardware running an in-vehicle operating system (DRIVE OS), a reference sensor set that supports full self-driving capability, as well as an open, modular DRIVE software platform for autonomous driving, mapping, and parking services, and intelligent in-vehicle experiences.
In addition, the company offers a scalable data center-based simulation solution based on NVIDIA Omniverse software to develop synthetic data for AI model training, as well as for testing and validating a self-driving platform. The company’s unique end-to-end, software-defined approach is designed for continuous innovation and continuous development, enabling cars to receive over-the-air updates to add new features and capabilities throughout the life of a vehicle.
Business Strategies
NVIDIA’s key strategies that shape its overall business approach include advancing the NVIDIA accelerated computing platform; extending the company’s technology and platform leadership in AI; extending its technology and platform leadership in computer graphics; advancing the leading autonomous vehicle platform; and leveraging its intellectual property, or IP.
Sales and Marketing
The company’s worldwide sales and marketing strategy is key to achieving its objective of providing markets with its high-performance and efficient computing platforms and software. The company’s sales and marketing teams, located across its global markets, work closely with customers and various industry ecosystems through its partner network. The company’s partner network incorporates global, regional, and specialized CSPs, OEMs, ODMs, ISVs, global system integrators, add-in board manufacturers, or AIBs, distributors, automotive manufacturers, and tier-1 automotive suppliers, and other ecosystem participants.
Members of the company’s sales team have technical expertise and product and industry knowledge. The company also employs a team of application engineers and solution architects to provide pre-sales assistance to its partner network in designing, testing, and qualifying system designs that incorporate its platforms. For example, the company’s solution architects work with CSPs to provide pre-sales assistance to enable its customers to optimize their hardware and software infrastructure for generative AI and LLM training and deployment.
To encourage the development of applications optimized for the company’s platforms and software, the company seeks to establish and maintain strong relationships in the software development community. Engineering and marketing personnel engage with key software developers to promote and discuss its platforms, as well as to ascertain individual product requirements and solve technical problems. The company’s developer program supports the development of AI frameworks, SDKs, and APIs for software applications and game titles that are optimized for its platforms. The company’s Deep Learning Institute provides in-person and online training for developers in industries and organizations around the world to build AI and accelerated computing applications that leverage its platforms.
Seasonality
The company’s computing platforms serve a diverse set of markets, such as data centers, gaming, professional visualization, and automotive. The company’s desktop gaming products typically see stronger revenue in the second half of its fiscal year (year ended January 26, 2025).
Manufacturing
The company utilizes foundries, such as Taiwan Semiconductor Manufacturing Company Limited, or TSMC, and Samsung Electronics Co., Ltd., or Samsung, to produce its semiconductor wafers. The company purchases memory from SK Hynix Inc., Micron Technology, Inc., and Samsung. The company utilizes CoWoS technology for semiconductor packaging. The company engages with independent subcontractors and contract manufacturers, such as Hon Hai Precision Industry Co., Ltd., Wistron Corporation, and Fabrinet, to perform assembly, testing, and packaging of its final products.
Competition
The company’s competitors include:
Suppliers and licensors of hardware and software for discrete and integrated GPUs, custom chips, and other accelerated computing solutions, including solutions offered for AI, such as Advanced Micro Devices, Inc., or AMD, Huawei Technologies Co. Ltd., or Huawei, and Intel Corporation, or Intel;
Large cloud services companies with internal teams designing hardware and software that incorporate accelerated or AI computing functionality as part of their internal solutions or platforms, such as Alibaba Group, Alphabet Inc., Amazon, Inc., or Amazon, Baidu, Inc., Huawei, and Microsoft Corporation, or Microsoft;
Suppliers of Arm-based CPUs and companies that incorporate hardware and software for CPUs as part of their internal solutions or platforms, such as Amazon, Huawei, and Microsoft;
Suppliers of hardware and software for SoC products that are used in servers or embedded into automobiles, autonomous machines, and gaming devices, such as Ambarella, Inc., AMD, Broadcom, Inc., or Broadcom, Intel, Qualcomm Incorporated, Renesas Electronics Corporation, and Samsung, or companies with internal teams designing SoC products for their own products and services, such as Tesla, Inc.; and
Networking products consisting of switches, network adapters (including DPUs), and cable solutions (including optical modules), such as AMD, Arista Networks, Broadcom, Cisco Systems, Inc., Hewlett Packard Enterprise Company, Huawei, Intel, Lumentum Holdings Inc., and Marvell Technology, Inc., as well as internal teams of system vendors and large cloud services companies.
History
NVIDIA Corporation was founded in 1993. The company was incorporated in California in 1993 and reincorporated in Delaware in 1998.
