The global GPU server market is projected to grow from USD 171.47 billion in 2025 to USD 730.56 billion by 2030, at a CAGR of 33.6% according to a new report by MarketsandMarkets™. A GPU server is a special computing system designed to handle computing workloads, especially in machine learning, deep learning, and intensive functions. GPU servers support parallel computing, often include large amounts of high-bandwidth memory, fast storage, and advanced networking components, to efficiently handle tasks such as image identity, natural language processing, research, healthcare, and autonomous systems. The GPU server market is growing rapidly, inspired by the increase in data traffic and the need for high computing power, and the machine learning (ML) and intensive teaching algorithms, as businesses and industry increasingly depend on AI technologies for data analysis, automation, and decision making.
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Browse in-depth TOC on “GPU Server Market”
230 – Tables 73 – Figures 280 – Pages
GPU Server MarketScope:
By deployment, the on-premises segment is expected to witness the highestCAGR during the forecast period.
An on-premises platform means an infrastructure that completely powers services and applications within the physical space of an organization instead of relying on cloud hosting. Such a model guarantees that all data storage, management, and processing are on the local server, giving the organization full power over its operation. Recent developments in the on-premises GPU server market have focused on increasing efficiency, scalability, and integration capabilities. Companies are rapidly investing in resource allocation and GPU management orchestration tools, which help maximize their operational efficiency. Since organizations prioritize data security and compliance, the on-premises model is likely to receive traction in various industries, paving the way for this segment's continuous development in the GPU server market.
By function, the inference segment is likely to record the highest CAGR during the forecast period.
Inference Function describes the process of using a trained AI model on new, previously unseen data to create predictions, decide, or draw conclusions. This conclusion of the GPU server is important in customizing and accelerating the function, responding to the especially computational requirements essential for real-time, high-demonstration AI applications. Companies are pursuing GPU server design to give high performance, low delay, and better energy efficiency, which are important for the adaptation of all assignments. In March 2023, NVIDIA Corporation launched the four estimated platforms adapted to generative AI applications, especially in relation to estimates within data centers, marking significant progress in the GPU server market.
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By region, North America is expected to hold the largest share of the GPU server market in 2025.
North America will hold the most significant part of the overall GPU server industry in 2025. The market in this region is mainly inspired by the presence of major GPU server players in the region, including NVIDIA Corporation (US), DELL Inc. (US), Hewlett Packard Enterprise Development LP (US), and IBM (US). These players are focused on large-scale new product development and cooperation. For example, in May 2024, Dell Inc. (US) collaborated with NVIDIA Corporation (US) to expand the Dale PowerAdes XE9680L adoption with new servers, edge, workstation, solutions, and services. Dale PowerAdes XE9680L server that supports eight Nvidia Blackwell GPUs in a small form and enables liquid cooling for fast processing. In addition, Nvidia Corporation (US) launched the NVIDIA Blackwell platform, which includes chip-to-chip interconnect solutions for GPU, CPU, and GPU server applications. This new solution will be adopted to give a wide range of GPU servers by Cisco Systems, Inc. (US), Hewlet Packard Enterprise Development LP (US), Dell Inc., Lenovo (Hong Kong), and Super Micro Computer, Inc. (US).
Key Players
Key companies operating in the GPU server companies include NVIDIA Corporation (US), Dell Inc. (US), Hewlett Packard Enterprise Development LP (US), Lenovo (Hong Kong), Huawei Technologies Co., Ltd. (China), IBM (US), H3C Technologies Co., Ltd. (China), Cisco Systems, Inc. (US), Fujitsu (Japan), and INSPUR Co., Ltd. (China).
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