Data Center GPU Market worth $228.04 billion by 2030 - Exclusive Report by MarketsandMarkets™

DELRAY BEACH, Fla., May 15, 2025 /PRNewswire/ -- The global data center GPU market is projected to reach USD 119.97 billion in 2025 and USD 228.04 billion by 2030, registering a CAGR of 13.7% during the forecast period according to a new report by MarketsandMarkets™. The global data center GPU market is experiencing significant growth, driven by the rapid adoption of artificial intelligence (AI) and machine learning (ML) across industries, along with increasing demand for high-performance computing and cloud services. Enterprises utilize GPUs for deep learning, large language model training, and advanced data analytics, which require powerful parallel processing. The rise of generative AI, real-time inference, and recommendation systems is boosting the need for scalable GPU infrastructure. Additionally, investments in hyperscale data centers and government initiatives to enhance AI capabilities further fuel market expansion. Major cloud providers like Amazon Web Services, Google Cloud, and Microsoft Azure are improving their GPU offerings. Meanwhile, companies like NVIDIA and AMD are launching next-generation GPUs tailored for training and inference tasks, solidifying the market's growth trend.

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Data Center GPU Market Report Scope:

Enterprises are projected to register the highest CAGR in the end-user market during the forecast period.

The data center GPU market is anticipated to grow significantly within the BFSI, retail and e-commerce, healthcare, automotive, and media and entertainment sectors. This growth is driven by the need for high-performance computing to process large volumes of structured and unstructured data. In the BFSI sector, GPUs are used for fraud detection and risk modeling, while retail and e-commerce utilize them for customer behavior analysis and recommendations. The rise of AI chatbots and automation also boosts the demand for GPU infrastructure.

Digital transformation in these industries has increased investments in GPU-powered data centers for virtual services and scalable cloud solutions. In healthcare, GPUs enhances medical imaging and diagnostics, while the automotive sector relies on them for ADAS and autonomous driving training. Similarly, media and entertainment leverage GPUs for real-time rendering and video streaming. Thus, the convergence of AI, big data, and edge computing is expected to drive steady growth in GPU demand for enterprise data centers.

The inference segment is expected to hold the largest share of the market, by function, till 2030.

The inference segment is poised to hold the largest market share among data center GPUs due to the growing deployment of AI models across various industries. Inference enables AI models to process new information and make real-time predictions after training, which is crucial in sectors like e-commerce, BFSI, and healthcare. As organizations move from experimenting with AI to full deployment, the demand for GPU-accelerated inference workloads is rapidly increasing. The widespread adoption of AI technologies, such as chatbots and predictive analytics, requires low-latency, high-throughput inference that GPUs deliver effectively. This trend and the integration of AI inference into business operations further fuel demand. Inference workloads are often executed at the edge and in centralized data centers, enhancing analytics and decision-making. Thus, the inference segment is set to dominate the data center GPU market in the coming years.

The cloud segment is projected to lead the market by deployment, in 2030.

The cloud deployment segment is set to dominate the data center GPU market due to the growing demand for on-demand computing power for AI, machine learning, and big data workloads. Organizations are moving from on-premises infrastructure to cloud platforms to reduce costs, increase flexibility, and access advanced GPU technology without a large initial investment. Major providers like Amazon Web Services (AWS), Microsoft Azure, and Google Cloud are expanding their GPU offerings to support industries such as BFSI, healthcare, automotive, and media. Cloud deployment also accelerates innovation and is ideal for enterprises needing on-demand computing for AI applications and high-performance computing. Additionally, the cloud offers scalability and global accessibility, making it the most feasible model for deploying GPUs in data centers, ensuring it maintains the largest market share throughout the forecast period.

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Europe will offer the largest regional market for data center GPU.

Europe is projected to hold a significant share of the data center GPU industry, driven by strong government support for digitalization and AI adoption. Initiatives like the EU's Digital Strategy and Horizon Europe foster substantial investments in cloud infrastructure and high-performance computing. Countries like Germany, France, and the Netherlands have led the application of AI across industries such as automotive, healthcare, and manufacturing, which require GPU-accelerated data centers for real-time processing. The region is also experiencing a rise in data-centric services, including video streaming and e-commerce, which demand high-performance GPU resources. Major hyperscalers like AWS, Microsoft, and Google are expanding their data center operations to meet this demand while adhering to data sovereignty requirements. With a focus on power-efficient and sustainable data centers, Europe is positioning itself as a key market for GPU-based infrastructure in the near future.

Key companies operating in the data center GPU companies include NVIDIA Corporation (US), Advanced Micro Devices, Inc. (US), Intel Corporation (US), Google Cloud (US), Microsoft (US), Amazon Web Services, Inc. (US), IBM (US), Alibaba Cloud (Singapore), Oracle (US), Tencent Cloud (China), CoreWeave (US), Vast.ai (US), Lambda (US), DigitalOcean (US), and JarvisLabs.ai (India), among others.

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Related Reports: 

GPU as a Service Market by Service Model (IaaS, PaaS), GPU Type (High-end GPUs, Mid-range GPUs, Low-end GPUs), Deployment (Public Cloud, Private Cloud, Hybrid Cloud), Enterprise Type (Large Enterprises, SMEs) - Global Forecast to 2030

AI Infrastructure Market by Offerings (Compute (GPU, CPU, FPGA), Memory (DDR, HBM), Network (NIC/Network Adapters, Interconnect), Storage, Software), Function (Training, Inference), Deployment (On-premises, Cloud, Hybrid) – Global Forecast to 2030

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