According to our (Global Info Research) latest study, the global GPU for AI Servers market size was valued at US$ 21614 million in 2025 and is forecast to a readjusted size of US$ 108992 million by 2032 with a CAGR of 29.5% during review period.
GPU for AI Servers refers to high-performance parallel computing acceleration chips specially designed for AI training and inference scenarios in data centers. Different from consumer-grade graphics cards and general-purpose computing chips, it features high computing power, high-bandwidth memory, enterprise-level stability and cluster interconnection capabilities, serving as the core computing component of AI servers. It is mainly used in cloud training, large-scale inference, intelligent computing centers, government AI, large model development and other key scenarios. Through dedicated AI computing units, it efficiently processes matrix operations and neural network computations in deep learning, supporting large language models, multi-modal models, autonomous driving models, intelligent recommendation, video analysis and other AI services. Such GPUs support long-term stable operation, high-speed interconnection protocols and error correction mechanisms, meeting the requirements of high-density deployment and large-scale clusters in data centers. They are widely used in Internet, cloud computing, intelligent manufacturing, smart cities, scientific research and public services, acting as one of the core hardware for global AI infrastructure construction.In 2025, global sales of GPUs for AI servers reached approximately 2.063 million units, with an average price of 10,180 US dollars per unit and an industry gross margin of around 54%.
GPU for AI Servers is no longer just a compute component.It has become the core platform layer that defines the competitiveness of AI infrastructure. Future market leadership will depend less on peak chip performance alone and more on system-level coordination across memory bandwidth, advanced packaging, liquid-cooling readiness, multi-GPU interconnect, software ecosystem, and rack-scale delivery capability. Demand is also shifting from a training-led market toward a more balanced mix of training and inference, with inference expansion favoring solutions optimized for efficiency, latency, deployment density, and total cost of ownership rather than raw compute alone. At the same time, hyperscaler in-house chips and dedicated accelerators will divert part of incremental demand, but they are unlikely to fully replace general-purpose GPUs in the near term because GPUs still hold strong advantages in ecosystem maturity, compatibility, and developer productivity. Overall, GPU for AI Servers should remain the anchor category of AI infrastructure investment, while the real moat is moving beyond silicon toward supply-chain control, software-stack maturity, and full system integration capability.
This report is a detailed and comprehensive analysis for global GPU for AI Servers market. Both quantitative and qualitative analyses are presented by manufacturers, by region & country, by Type and by Application. As the market is constantly changing, this report explores the competition, supply and demand trends, as well as key factors that contribute to its changing demands across many markets. Company profiles and product examples of selected competitors, along with market share estimates of some of the selected leaders for the year 2025, are provided.
Key Features:
Global GPU for AI Servers market size and forecasts, in consumption value ($ Million), sales quantity (K Units), and average selling prices (K US$/Unit), 2021-2032
Global GPU for AI Servers market size and forecasts by region and country, in consumption value ($ Million), sales quantity (K Units), and average selling prices (K US$/Unit), 2021-2032
Global GPU for AI Servers market size and forecasts, by Type and by Application, in consumption value ($ Million), sales quantity (K Units), and average selling prices (K US$/Unit), 2021-2032
Global GPU for AI Servers market shares of main players, shipments in revenue ($ Million), sales quantity (K Units), and ASP (K US$/Unit), 2021-2026
The Primary Objectives in This Report Are:
To determine the size of the total market opportunity of global and key countries
To assess the growth potential for GPU for AI Servers
To forecast future growth in each product and end-use market
To assess competitive factors affecting the marketplace
This report profiles key players in the global GPU for AI Servers market based on the following parameters - company overview, sales quantity, revenue, price, gross margin, product portfolio, geographical presence, and key developments. Key companies covered as a part of this study include NVIDIA, AMD, Intel, MetaX, Denglin Technology, Shanghai Iluvatar CoreX, Hygon, Vastai Technologies, Moore Threads Smart Technology (Beijing) Co., Ltd., Shanghai Biren Technology Co., Ltd., etc.
This report also provides key insights about market drivers, restraints, opportunities, new product launches or approvals.
Market Segmentation
GPU for AI Servers market is split by Type and by Application. For the period 2021-2032, the growth among segments provides accurate calculations and forecasts for consumption value by Type, and by Application in terms of volume and value. This analysis can help you expand your business by targeting qualified niche markets.
Market segment by Type
≤16GB
16GB – 80GB
> 80GB
Market segment by Workload
Training GPU
Inference GPU
General-Purpose AI GPU
Market segment by Application
Large Model R&D and Training
Cloud AI Inference Services
Industry Intelligent Deployment
Others
Major players covered
NVIDIA
AMD
Intel
MetaX
Denglin Technology
Shanghai Iluvatar CoreX
Hygon
Vastai Technologies
Moore Threads Smart Technology (Beijing) Co., Ltd.
Shanghai Biren Technology Co., Ltd.
Market segment by region, regional analysis covers
North America (United States, Canada, and Mexico)
Europe (Germany, France, United Kingdom, Russia, Italy, and Rest of Europe)
Asia-Pacific (China, Japan, Korea, India, Southeast Asia, and Australia)
South America (Brazil, Argentina, Colombia, and Rest of South America)
Middle East & Africa (Saudi Arabia, UAE, Egypt, South Africa, and Rest of Middle East & Africa)
The content of the study subjects, includes a total of 15 chapters:
Chapter 1, to describe GPU for AI Servers product scope, market overview, market estimation caveats and base year.
Chapter 2, to profile the top manufacturers of GPU for AI Servers, with price, sales quantity, revenue, and global market share of GPU for AI Servers from 2021 to 2026.
Chapter 3, the GPU for AI Servers competitive situation, sales quantity, revenue, and global market share of top manufacturers are analyzed emphatically by landscape contrast.
Chapter 4, the GPU for AI Servers breakdown data are shown at the regional level, to show the sales quantity, consumption value, and growth by regions, from 2021 to 2032.
Chapter 5 and 6, to segment the sales by Type and by Application, with sales market share and growth rate by Type, by Application, from 2021 to 2032.
Chapter 7, 8, 9, 10 and 11, to break the sales data at the country level, with sales quantity, consumption value, and market share for key countries in the world, from 2021 to 2026.and GPU for AI Servers market forecast, by regions, by Type, and by Application, with sales and revenue, from 2027 to 2032.
Chapter 12, market dynamics, drivers, restraints, trends, and Porters Five Forces analysis.
Chapter 13, the key raw materials and key suppliers, and industry chain of GPU for AI Servers.
Chapter 14 and 15, to describe GPU for AI Servers sales channel, distributors, customers, research findings and conclusion.
Summary:
Get latest Market Research Reports on GPU for AI Servers. Industry analysis & Market Report on GPU for AI Servers is a syndicated market report, published as Global GPU for AI Servers Market 2026 by Manufacturers, Regions, Type and Application, Forecast to 2032. It is complete Research Study and Industry Analysis of GPU for AI Servers market, to understand, Market Demand, Growth, trends analysis and Factor Influencing market.