Top 50 Companies in Data Center GPU Market 2025: Strategic Overview And Future Trends (2024–2035)
RELEASE DATE: Sep 2025 Author: Spherical InsightsRequest Free Sample Speak to Analyst
Description
According to a research report published by Spherical Insights & Consulting, The Global Data Center GPU Market Size is projected to Grow from USD 18.87 Billion in 2024 to USD 342.94 Billion by 2035, at a CAGR of 30.17% during the forecast period 2025–2035. The market for data center GPUs is in greater demand as driven by the growing need for applications involving machine learning and artificial intelligence. For tasks like analysing massive datasets and training deep neural networks, these technologies need a lot of processing power. Graphics analysis units are especially well-suited for these kinds of workloads because of their parallel processing capabilities.
Introduction
A Data centre GPU (Graphics Processing Units) is are specialised accelerators that enable data centres to do complex computing tasks. The growing need for high-performance computing applications, including cloud services, machine learning, and artificial intelligence, is propelling the data centre GPU market in India. For these jobs, graphics processing units are favoured over conventional central processing units because of their superior parallel processing capabilities, which make them perfect for sophisticated computing and handling massive datasets. This expansion has been further boosted by the actions of the Indian government, such as the introduction of the IndiaAI Compute Portal and the AI Kosha platform. These platforms promote innovation and advancement in AI technology by giving researchers, companies, and developers access to large datasets and GPU resources. The government's dedication to boosting AI research and growing GPU infrastructure highlights the market's strategic significance for India's technological development. The government's dedication to boosting AI research and growing GPU infrastructure highlights the market's strategic significance for India's technological development.
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Data Center GPU Market Size & Statistics
- The Market Size for Data Center GPU Was Estimated to be worth USD 18.87 Billion in 2024.
- The Market Size is Going to Expand at a CAGR of 30.17% between 2025 and 2035.
- The Global Data Center GPU Market Size is anticipated to reach USD 342.94 Billion by 2035.
- North America is expected to generate the highest demand during the forecast period in the Data Center GPU Market
- Asia Pacific is expected to grow the fastest during the forecast period in the Data Center GPU Market.
Regional growth and demand
Asia Pacific is expected to grow the fastest during the forecast period in the data center GPU market. The market for data center GPUs is now growing in the Asia Pacific by implementing 5G technology and creating smart cities. Nations like China, Japan, and South Korea are spearheading this expansion. The demand for GPU-powered data centres is also rising as a result of the quick adoption of AI in industries including manufacturing, retail, and public infrastructure. China is a key player in the global data centre GPU market, as evidenced by its leadership in AI development and the expansion of regional cloud providers.
North America is expected to generate the highest demand during the forecast period in the data center GPU market. The data center GPU market with the quickest rate of growth throughout the study period is anticipated to be in North America. The quick uptake of AI and machine learning technology in industries like banking, healthcare, and driverless cars is what is causing this domination. To meet the demands of high-performance computing, major cloud service providers and industry behemoths like NVIDIA, Amazon, and Google are making significant investments in GPU infrastructure. The area leads the industry in part because of its strong technology ecosystem and large expenditures in AI infrastructure.
Top 10 trends in the Data Center GPU Market
- AI and Machine Learning Workloads
- Cloud-Based GPU Services
- Edge Computing Integration
- Advancements in GPU Architectures
- Specialized GPUs for Data Centers
- GPU Virtualization
- Integration with Quantum Computing
- Energy Efficiency and Sustainability
- Geopolitical Dynamics and Market Competition
- Hyperscale Data Center Deployments
1. AI and Machine Learning Workloads
Demand for data centre GPUs is being driven mostly by the growing use of machine learning and artificial intelligence applications. These GPUs are crucial for effectively managing the concurrent processing jobs needed for complicated AI model deployment and training. The need for GPUs in data centres is being driven mostly by sectors that rely on AI and ML technologies, such as healthcare, banking, and autonomous driving. This demand is further increased by the use of cloud services and the growth of AI capabilities in businesses, since cloud service providers are constantly improving their AI infrastructure with high-performance GPUs.
2. Cloud-Based GPU Services
GPU-as-a-Service, also known as cloud-based GPU services, provides scalable, on-demand access to powerful GPUs using cloud platforms. With this arrangement, companies may take advantage of strong processing capabilities without having to make a big upfront hardware investment. Industries that need to do complex computational processes, such as high-performance computing, machine learning, and artificial intelligence, benefit greatly from GPUaaS. Businesses may effectively manage complicated workloads, spur innovation, and preserve cost-effectiveness by implementing GPUaaS. GPUaaS solutions, which enable flexibility and worldwide accessibility to satisfy a variety of computational needs, are offered by major cloud providers such as Google Cloud, Microsoft Azure, and Amazon Web Services.
3. Edge Computing Integration
Data centre architectures are being revolutionised by edge computing integration, which lowers latency, improves real-time decision-making, and decentralises data processing to local nodes. Applications like driverless cars, industrial automation, and smart cities that demand real-time data analysis would benefit most from this strategy. Edge computing reduces the demand on centralised data centres by processing data closer to its source, hence easing bandwidth restrictions. Further speeding up the deployment of edge computing solutions are the expansion of 5G networks and the proliferation of Internet of Things devices. In order to ensure effective and scalable operations, this trend is propelling the development of specialised hardware and software to support distributed computing systems.
4. Advancements in GPU Architectures
The performance and effectiveness of data centre operations are being greatly improved by developments in GPU designs. A dual-die design with 104 billion transistors each coupled by a 10TB/s interconnect is one example of NVIDIA's Blackwell architecture. By tripling the number of transistors compared to its predecessor, Hopper, this arrangement enables up to 576 GPU processors on a single chip. Furthermore, Blackwell optimises AI inference operations by integrating a second-generation Transformer Engine that supports novel low-precision formats like MXFP4 and MXFP6. To increase scalability and performance, AMD's RDNA 5 architecture is also expected to use a chiplet-based design, possibly with 2.5D/3.5D packaging. In order to handle the increasing needs of AI and machine learning workloads in data centres, these advancements are essential.
5. Specialized GPUs for Data Centers
High-performance computing, machine learning, and artificial intelligence workloads are among the tasks that specialised GPUs for data centres are made to handle. When compared to general-purpose GPUs, these GPUs provide improved performance, efficiency, and scalability. Data centres can handle complicated workloads more effectively thanks to these specialised GPUs, which spur innovation and meet the expanding needs of contemporary computing.
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Stay informed with the latest industry insights and market trends to identify new opportunities and drive growth in the data center GPU market. To explore more in-depth trends, insights, and forecasts, please refer to our detailed report.
Top 19 Companies Leading the Data Center GPU Market
- IBM
- Advanced Micro Devices, Inc.
- INTEL CORPORATION
- NVIDIA Corporation
- Google Cloud
- Huawei Cloud Computing Technologies Co., Ltd.
- Qualcomm Technologies, Inc.
- MICRON TECHNOLOGY, INC.
- Imagination Technologies
- Samsung SDS
- Microsoft
- Amazon Web Services, Inc.
- Alibaba Cloud
- Oracle
- Tencent Cloud
- CoreWeave
- Lambda
- DigitalOcean
- Qualcomm Technologies, Inc.
- Others
1. IBM
Headquarters: Armonk, New York
IBM is a well-known worldwide technology and consulting firm with expertise in corporate software, blockchain, automation, cybersecurity, data analytics, hybrid cloud, and artificial intelligence. It serves sectors like healthcare, banking, manufacturing, retail, and telecommunications by offering services ranging from cloud computing and IT infrastructure to technology consulting and business process solutions.
2. Advanced Micro Devices, Inc.
Headquarters: California, USA
Leading the way in semiconductor design worldwide, Advanced Micro Devices, Inc. is well-known for its inventiveness in CPU, GPU, FPGA, AI accelerator, and adaptive SoC technologies. AMD caters to a variety of areas, including gaming, data centres, embedded devices, and supercomputing, with its high-performance products, which include Ryzen desktop and laptop processors, EPYC server CPUs, Radeon and Instinct GPUs, and FPGA/AI engine solutions. Applications in healthcare, aircraft, automotive, enterprise, cloud infrastructure, and scientific research are powered by its portfolio, which includes brands including Ryzen, Radeon, EPYC, Instinct, Versal, and Virtex.
3. INTEL CORPORATION
Headquarters: California, USA
Leading American multinational technology corporation Intel Corporation is well-known for creating and producing important semiconductor parts, such as networking accelerators, central processing units, graphics processing units, and silicon with an AI focus. With its product lines, which include Core processors, Xeon CPUs, Data Centre GPUs, and Agilex FPGAs, Intel drives a variety of applications, ranging from personal computing and data centres to IoT, AI, and connectivity platforms. Along with providing technology solutions for the edge, network, and automotive sectors, the company is a pioneer in fields including artificial intelligence, cloud computing, and next-generation infrastructure.
4. NVIDIA Corporation
Headquarters: California, USA
Leading American technology business NVIDIA Corporation specialises in system-on-chips, software platforms, and sophisticated graphics processing units for a variety of applications. Artificial intelligence, high-performance computing, edge computing, data centres and cloud computing, professional visualisation, gaming, and autonomous vehicles are just a few of the businesses that are powered by its technologies. CUDA and other components of NVIDIA's flagship software ecosystem are now crucial for speeding up scientific and AI tasks.
5. Google Cloud
Headquarters: California, USA
Google Cloud is a full range of cloud computing services built on the same sturdy framework that underpins Google's popular consumer platforms, including YouTube, Gmail, and Search. Its products cover big data, machine learning, networking, computing, storage, and the Internet of Things. Google Cloud Storage, BigQuery for scalable data warehousing, Compute Engine for virtual machines, and Kubernetes—the container orchestration technology that started with Google Cloud—are important tools. The platform supports industries like healthcare, finance, manufacturing, education, and government by empowering businesses to develop, test, and implement applications effectively and dependably.
Are you ready to discover more about the data center GPU market?
The report provides an in-depth analysis of the leading companies operating in the global data center GPU market. It includes a comparative assessment based on their product portfolios, business overviews, geographical footprint, strategic initiatives, market segment share, and SWOT analysis. Each company is profiled using a standardized format that includes:
Company Profiles
- IBM
- Business Overview
- Company Snapshot
- Products Overview
- Company Market Share Analysis
- Company Coverage Portfolio
- Financial Analysis
- Recent Developments
- Merger and Acquisitions
- SWOT Analysis
- Advanced Micro Devices, Inc.
- INTEL CORPORATION
- NVIDIA Corporation
- Google Cloud
- Huawei Cloud Computing Technologies Co., Ltd.
- Qualcomm Technologies, Inc.
- IBM
- MICRON TECHNOLOGY, INC.
- Others
Conclusion
The data center GPU market is accelerating due to the growing demand for high-performance computing across businesses, especially in the gaming, cloud gaming, healthcare, finance, and AI-driven sectors, is what is driving this upsurge. The need for GPUs is also rising due to cloud gaming, virtual reality, and entertainment applications. Nevertheless, limitations in the semiconductor supply chain, such as previous chip shortages, still make GPU deployment and availability difficult.
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