United States Graphics Processing Unit (GPU) Market Report by Component, Type, Deployment, Application, States and Company Analysis 2026-2034

United States Graphics Processing Unit Market Size and Forecast

United States Graphics Processing Unit Market will grow from US$ 19.03 Billion in 2025 to US$ 136.07 Billion in 2034, at a Compound Annual Growth Rate (CAGR) of 24.43% from 2026 to 2034. The market is driven by increasing demand for artificial intelligence (AI), machine learning, cloud computing, gaming, and high-performance computing. Growing adoption of advanced GPUs in data centers, autonomous systems, and professional visualization is further supporting market expansion across the United States.

What is a Graphics Processing Unit and Its Uses & Popularity in the United States?

A Graphics Processing Unit (GPU) is a specialized semiconductor processor designed to perform large numbers of calculations simultaneously. Originally developed for rendering graphics and images, GPUs are now essential for artificial intelligence (AI), machine learning, gaming, data analytics, scientific computing, professional visualization, autonomous vehicles, and cryptocurrency-related computing. In the United States, GPUs have become particularly important for AI model training and inference because their parallel-processing architecture can accelerate workloads that are difficult to handle efficiently with conventional CPUs. The IEA notes that servers containing CPUs and specialized accelerators such as GPUs account for a major share of data-center electricity consumption, while U.S. data-center electricity demand is projected to increase substantially through 2030. GPU popularity is also supported by expanding cloud infrastructure and gaming demand. NVIDIA reported US$193.7 billion in data-center revenue and US$16.0 billion in gaming revenue for fiscal 2026, illustrating the scale of GPU-driven computing applications.

Data Center Construction Launches in USA

1. Meta Bowling Green Data Center – Ohio, 2025
   Meta announced its new 715,000-square-foot data center in Bowling Green, Ohio, in April 2025. The project represents an investment of more than US$800 million and is expected to employ more than 1,000 construction workers at peak. The facility will support Meta’s expanding digital and AI infrastructure.
2. Meta El Paso Data Center – Texas, 2025
   Meta broke ground on a new data center in El Paso, Texas, backed by a US$1.5 billion investment. The campus is designed to scale to approximately 1 GW and is expected to come online in 2028. Peak construction employment is projected at approximately 1,800 workers, demonstrating the scale of AI-oriented data center construction.
3. Oracle/OpenAI Stargate Data Center – Michigan, 2026
   Oracle, OpenAI, and partners began construction of the Stargate data center campus in Saline Township, Michigan, in June 2026. The project, known as “The Barn,” is planned for approximately 1 GW of capacity and is estimated at around US$10 billion. The first of three planned buildings measures approximately 550,000 square feet.
4. Iron Mountain RCH-1 Data Center Campus – Virginia, 2026
   Iron Mountain and Clark Construction broke ground on a new data center campus in Sandston, Virginia, in July 2026. The 66-acre development is planned to deliver more than 200 MW of total capacity and exceed 1.1 million square feet when fully developed. The campus is designed for hyperscale, neocloud, and AI workloads.
5. Microsoft Atlanta AI Data Center – Georgia, 2025
   Microsoft unveiled construction of a new data center in Atlanta, Georgia, in 2025 as part of its expansion of AI and cloud infrastructure. The facility is planned alongside Microsoft’s Wisconsin infrastructure to support large-scale AI computing and supercomputing workloads using advanced accelerator hardware.
6. Meta Monroe Data Center Campus – Louisiana, 2025
   Meta’s planned data center campus near Monroe, Louisiana, represents an investment exceeding US$10 billion. The custom-designed campus is planned at approximately 4 million square feet, with more than 5,000 construction workers expected at peak. The project is designed to support Meta’s expanding AI computing requirements.
7. Meta Jeffersonville Data Center Campus – Indiana
   Meta’s Jeffersonville, Indiana campus is among its U.S. data center developments supporting the company’s expansion of computing infrastructure. The project was awarded to Turner Construction and forms part of Meta’s broader U.S. campus-development program, alongside projects in Minnesota, Alabama, Wyoming, and South Carolina.
8. Meta Rosemont Data Center – Minnesota
   Meta selected Rosemont, Minnesota, for another major U.S. data center campus as part of its expanding infrastructure network. The development was awarded to Mortenson and is among a group of projects that Meta identified as representing approximately US$800 million each. The projects are intended to increase computing capacity for Meta’s global services and AI workloads.
9. Meta Montgomery Data Center – Alabama
   Meta’s Montgomery, Alabama, data center development is another major campus in the company’s U.S. expansion program. Hensel Phelps was selected for the project, which was included among Meta’s approximately US$800 million campus investments announced in 2024 and developed as part of its continuing data center construction pipeline.
10. U.S. Department of Energy AI/Data Center Sites – 2025
    The U.S. Department of Energy announced in April 2025 that it had identified 16 federal sites for potential data center and AI infrastructure development. The locations were selected because of existing energy infrastructure and the potential to accelerate permitting for additional generation. The initiative demonstrates the growing focus on combining data center construction with new energy infrastructure to address rapidly increasing AI power requirements.

Growth Drivers of the United States Graphics Processing Unit Market

Rapid Expansion of Artificial Intelligence and Generative AI

The accelerating adoption of artificial intelligence and generative AI is a major growth driver for the U.S. GPU market. Training and deploying large language models, image-generation systems, recommendation engines, autonomous applications, and AI agents require highly parallel computational capabilities, making GPUs critical infrastructure for modern AI workloads. NVIDIA reported US$193.7 billion in data-center revenue in fiscal 2026, compared with US$115.2 billion in fiscal 2025, reflecting strong demand for accelerated computing and AI platforms. The broader infrastructure investment supporting AI is also expanding rapidly. The IEA reported that capital expenditure by five major technology companies exceeded US$400 billion in 2025 and was expected to increase by another 75% in 2026. It also reported that electricity consumption by AI-focused data centers is projected to triple between 2025 and 2030. As U.S. technology companies, cloud providers, enterprises, and research institutions expand AI infrastructure, demand for high-performance GPUs is expected to remain closely linked to the growth of AI computing.

Expansion of U.S. Data Centers and Cloud Computing

Rapid development of data centers across the United States is creating substantial demand for GPUs used in cloud computing, accelerated computing, AI services, and high-performance workloads. The IEA projects that U.S. data-center electricity consumption will increase by approximately 240 TWh by 2030, representing around 130% growth from 2024 levels. Meanwhile, a 2026 Lawrence Berkeley National Laboratory report estimates that U.S. data centers could consume 11.8% of total U.S. electricity by 2030, with scenarios ranging from 9.5% to 15.3%. The growth of hyperscale and AI-oriented facilities is increasing requirements for specialized accelerated-computing hardware. GPUs are increasingly deployed alongside CPUs in servers to process parallel workloads and support AI training and inference. Cloud providers are consequently investing in GPU-enabled infrastructure that allows businesses to access high-performance computing without purchasing complete physical systems. This expanding cloud ecosystem supports GPU demand from technology companies, financial institutions, healthcare organizations, research laboratories, and other enterprise users.

Increasing Demand from Gaming, Professional Visualization, and High-Performance Computing

Gaming remains an important application for GPUs in the United States, while professional visualization, engineering, scientific research, simulation, and other high-performance computing workloads are expanding the addressable market. Modern GPUs provide high parallel-processing performance for advanced graphics, 3D rendering, simulation, video production, and computational workloads. NVIDIA reported US$16.0 billion in gaming revenue and US$3.2 billion in professional visualization revenue during fiscal 2026, demonstrating continued demand across these applications. Beyond gaming, GPU acceleration is increasingly used in research and enterprise environments where large datasets and complex calculations require significant computing power. Universities, laboratories, financial institutions, engineering companies, and creative professionals use GPUs for simulations, visualization, data processing, and AI development. The convergence of gaming, professional graphics, scientific computing, and AI is therefore broadening GPU applications. Continued development of higher-performance architectures, memory technologies, and software ecosystems can further increase adoption across U.S. consumer and enterprise markets.

Challenges of the United States Graphics Processing Unit Market

High Energy Consumption and Data-Center Infrastructure Constraints

High-performance GPUs can increase electricity and cooling requirements, creating infrastructure challenges for organizations deploying large GPU clusters. This issue is particularly important as AI workloads require increasingly dense computing infrastructure. The IEA reported that global data-center electricity demand increased 17% in 2025, while electricity consumption from AI-focused data centers grew even faster. In the United States, Lawrence Berkeley National Laboratory estimates that data centers could account for 11.8% of national electricity consumption by 2030, although its scenario range extends from 9.5% to 15.3%. These requirements can increase operating expenses through electricity, cooling, networking, and facility upgrades. Grid interconnection and power availability can also delay new data-center projects. The IEA identifies electricity infrastructure and equipment bottlenecks as constraints on data-center expansion. Consequently, GPU market expansion is increasingly connected to the availability of reliable power, advanced cooling technologies, suitable data-center capacity, and supporting infrastructure.

Semiconductor Supply Constraints and Export-Control Uncertainty

The U.S. GPU industry faces challenges related to advanced semiconductor manufacturing capacity, supply-chain complexity, and changing export-control requirements. Advanced GPUs depend on sophisticated semiconductor fabrication, packaging, memory, networking components, and other specialized technologies. NVIDIA has reported that its latest data-center products are subject to supply constraints and that the complexity of manufacturing large-scale data-center systems can create production and supply-demand management challenges. Export regulations add another layer of uncertainty. U.S. controls on advanced computing semiconductors can affect product distribution, customer access, supply chains, and compliance requirements. NVIDIA has stated that changing export-control rules can create additional compliance burdens and potentially affect demand and distribution. For U.S. GPU manufacturers and technology companies, maintaining sufficient manufacturing capacity while adapting to evolving semiconductor regulations remains an important market challenge.

Graphics Processing Unit Launches in the USA

• NVIDIA GeForce RTX 5090 — January 2025: NVIDIA launched the flagship Blackwell-based RTX 5090, featuring 92 billion transistors and 3,352 AI TOPS, with a starting price of $1,999.
• NVIDIA GeForce RTX 5080 — January 2025: The RTX 5080 launched alongside the RTX 5090 on January 2025, with a starting price of $999 and support for DLSS 4 and Multi Frame Generation.
• NVIDIA GeForce RTX 5070 Ti — February 2025: NVIDIA introduced the RTX 5070 Ti with 16GB GDDR7 memory and a starting price of $749, targeting high-performance gaming and content creation.
• NVIDIA GeForce RTX 5070 — March 2025: The RTX 5070 became available in March 2025, bringing Blackwell architecture, 12GB GDDR7 memory, DLSS 4, and AI-enhanced graphics to a broader market.
• NVIDIA GeForce RTX 5060 Ti — April 2025: NVIDIA launched the RTX 5060 Ti with 8GB and 16GB memory configurations, starting at $379 and $429, respectively.
• NVIDIA GeForce RTX 5060 — May 2025: The RTX 5060 expanded the Blackwell family into the mainstream segment with a starting price of $299, offering DLSS 4, ray tracing, and neural rendering.
• AMD Radeon RX 9070 XT — March 2025: AMD launched the Radeon RX 9070 XT as part of its RDNA 4 generation, featuring 16GB memory, enhanced ray-tracing accelerators, and AI accelerators.
• AMD Radeon RX 9070 — March 2025: The Radeon RX 9070 was launched alongside the RX 9070 XT, providing 16GB memory and RDNA 4-based graphics and AI capabilities for high-performance gaming.
• Intel Arc B580 — December 2024: Intel introduced the Arc B580 as part of its Battlemage-generation GPUs. The Limited Edition became available on December 2024, starting at $249, with AI and media-processing capabilities.
• Intel Arc B570 — January 2025: Intel’s Arc B570 became available on January 16, 2025, starting at $219. It targets mainstream gaming while supporting modern graphics features and AI workloads.

California Strong Technology and AI Ecosystem

California remains an important market for GPUs because of its concentration of semiconductor, software, AI, cloud-computing, and technology companies. Silicon Valley supports demand for high-performance GPUs used in AI model development, data analytics, simulation, and accelerated computing. The state’s broader computing infrastructure is also expanding as data-center electricity demand rises nationally. U.S. data-center servers already accounted for an estimated 7% of commercial-sector electricity consumption in 2025, highlighting the growing importance of accelerated computing infrastructure. California also benefits from major universities and research institutions using GPUs for artificial intelligence, scientific computing, engineering, and visualization. Gaming, animation, film production, and visual-effects industries further support professional and consumer GPU demand. At the same time, electricity availability, operating expenses, and infrastructure requirements can influence large-scale GPU deployments. California’s combination of technology companies, research capabilities, creative industries, and AI development therefore provides multiple demand channels for GPU manufacturers and system providers.

Texas Data Centers and Large-Scale Computing Drive Demand

Texas is becoming an important GPU market as data centers, AI infrastructure, cloud computing, and cryptocurrency-mining operations expand. The U.S. Energy Information Administration projected that electricity demand from large flexible-load customers in ERCOT would reach 54 billion kWh in 2025, nearly 60% higher than expected 2024 demand, with data centers and cryptocurrency facilities among the major contributors. EIA also expected ERCOT electricity demand to increase 14% in 2026, partly because large data centers and cryptocurrency-mining facilities come online. Texas has substantial power-generation capacity, with 168,317 MW of net summer capacity in 2024, ranking first among U.S. states.  Austin, Dallas, Houston, and other technology centers support GPU demand from enterprises, research institutions, cloud providers, and AI developers. However, rapidly increasing electricity demand can create grid and interconnection constraints. In September 2026, ERCOT reported a record 74.5 GW weekly average load, illustrating the pressure created by sustained computing and broader electricity demand.

New York Finance, Media, and AI Applications Support Adoption

New York’s GPU market is supported by the state’s concentration of financial services, technology companies, media organizations, universities, and research institutions. GPUs can accelerate computationally intensive applications such as financial modeling, data analytics, artificial intelligence, visualization, simulation, and risk analysis. New York’s media and entertainment ecosystem also creates demand for GPUs in video production, animation, rendering, and visual effects, while universities increasingly use accelerated computing for AI and data-science research. Electricity costs remain an important consideration for organizations operating intensive computing infrastructure. NYSERDA’s latest data show that statewide industrial electricity prices reached 10.2 cents/kWh in June 2026, compared with 9.2 cents/kWh in June 2025. Commercial electricity prices were 23.6 cents/kWh in June 2026, up from 22.0 cents/kWh a year earlier. These costs can influence the economics of large GPU clusters and data-center operations. Nevertheless, the state’s diversified technology, finance, research, and creative sectors create demand across both enterprise and professional GPU applications.

Florida Growing Technology, Healthcare, and Data-Center Applications

Florida’s GPU market is expanding through demand from artificial intelligence, healthcare, gaming, higher education, cloud computing, and data analytics. Universities and medical institutions can use GPUs for medical imaging, AI research, scientific simulation, and computational workloads, while gaming and digital-content users contribute to consumer and professional GPU demand. The state’s expanding data-center activity also creates opportunities for accelerated computing infrastructure. Nationally, EIA reports that data-center electricity consumption is a major contributor to rising U.S. electricity demand, with electricity demand increasing approximately 1.7% annually between 2020 and 2025, compared with only 0.1% annually from 2005 to 2019. Florida is also part of the U.S. regions experiencing increasing electricity requirements associated with computing infrastructure. GPU deployments, however, require reliable power and effective cooling, making energy availability and operating costs important considerations. Florida’s large consumer population, research institutions, technology businesses, and expanding digital infrastructure provide multiple avenues for GPU adoption across consumer, enterprise, and high-performance computing applications.

United States Graphics Processing Unit (GPU) Market Segments:

Component

• Hardware
• Software
• Services

Type

• Integrated GPU
• Discrete GPU
• Hybrid GPU

Deployment

• On-Premise
• Cloud

Application

• IT & Telecommunication
• Healthcare
• Media & Entertainment
• Others

States – Market breakup in 29 viewpoints:

• California
• Texas
• New York
• Florida
• Illinois
• Pennsylvania
• Ohio
• Georgia
• New Jersey
• Washington
• North Carolina
• Massachusetts
• Virginia
• Michigan
• Maryland
• Colorado
• Tennessee
• Indiana
• Arizona
• Minnesota
• Wisconsin
• Missouri
• Connecticut
• South Carolina
• Oregon
• Louisiana
• Alabama
• Kentucky
• Rest of United States

All companies have been covered from 5 viewpoints:

• Company Overview
• Key Persons
• Recent Development & Strategies
• SWOT Analysis
• Sales Analysis

Key Players Analysis

• Intel Corporation
• Advanced Micro Devices Inc.
• Nvidia Corporation
• Imagination Technologies Group
• Samsung Electronics Co. Ltd
• Arm Limited (Soft Bank Group)
• EVGA Corporation
• SAPPHIRE Technology Limited
• Qualcomm Technologies Inc.

Report Details: