The report "Data Center GPU Industry by Deployment (Cloud, On-premises), Function (Training, Inference), Application (Generative AI, Machine Learning, Natural Language Processing, Computer Vision), End User (CSP, Enterprises) & Region - Global Forecast to 2030" 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. 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.
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 market, 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
market 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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