세계의 GPUaaS(GPU-as-a-Service) 시장 예측(-2032년) : 서비스 모델별, 전개 방식별, GPU 종류별, 조직 규모별, 용도별, 최종사용자별, 지역별 분석

According to Stratistics MRC, the Global GPU-as-a-Service Market is accounted for $4.74 billion in 2025 and is expected to reach $22.50 billion by 2032 growing at a CAGR of 24.9% during the forecast period. GPU-as-a-Service (GPUaaS) refers to a cloud solution that supplies users with scalable GPU computing power whenever needed. Instead of investing in costly GPU infrastructure, companies can access virtualized GPUs for AI, ML, analytics, rendering, and graphics-intensive applications. The service allows pay-as-you-go usage, rapid resource deployment, and efficient performance scaling. By using GPUaaS, organizations reduce hardware expenses, improve computational speed, and support demanding workloads with flexible, reliable, and remotely accessible GPU resources delivered through cloud providers.

Market Dynamics:

Driver:

Rising demand for AI and machine learning

Traditional on-premise infrastructure cannot keep pace with the computational intensity required for modern AI models. GPUaaS offers flexible, on-demand access, reducing capital expenses and improving deployment speed. The spread of generative AI and large language models is further amplifying the need for cloud-based GPU resources. Organizations increasingly rely on high-performance GPUs to run deep learning, data analytics, and inferencing workloads at scale. As a result, rising AI and ML adoption is a primary force accelerating the expansion of the GPUaaS market.

Restraint:

Performance variability in multi-tenant environments

Shared infrastructure can lead to resource contention, impacting real-time or latency-sensitive workloads. This variability makes it difficult for enterprises to guarantee predictable execution for AI training or graphics-intensive tasks. Providers are investing in hardware isolation, advanced scheduling, and dedicated GPU instances, but these solutions increase operational complexity. Customers with mission-critical applications may still prefer on-premise GPU clusters for guaranteed stability.

Opportunity:

Growing demand from non-traditional sectors

Sectors such as retail, education, agriculture, and logistics are using GPUs for advanced analytics, simulation, and automation. Cloud-based GPUs are enabling new use cases including precision farming, virtual classrooms, and supply chain optimization. As digital transformation accelerates, these industries require scalable computing power without heavy infrastructure investment. The versatility of GPUaaS platforms makes them well-suited to support diverse workloads beyond conventional tech fields.

Threat:

Competition from alternative computing technologies

Solutions such as TPUs, custom AI accelerators, FPGAs, and specialized ASICs offer optimized performance for specific AI tasks. These alternatives can sometimes outperform GPUs in power efficiency or cost-effectiveness. Major cloud providers are increasingly developing their own proprietary chips, reducing reliance on GPUs. This shift could potentially limit the long-term dominance of GPU-based services. Consequently, the rise of competing architectures poses a notable threat to the GPUaaS market.

Covid-19 Impact:

The Covid-19 pandemic reshaped enterprise computing priorities and accelerated cloud adoption, boosting demand for GPUaaS. Remote work increased reliance on cloud resources for AI development, virtual desktops, and simulation workloads. Disruptions in hardware supply chains also pushed companies toward cloud-hosted GPUs instead of on-premise systems. At the same time, sectors like healthcare and e-commerce amplified their use of AI-driven analytics. Cloud-based GPU platforms enabled faster experimentation and model deployment during uncertain periods.

The public cloud segment is expected to be the largest during the forecast period

The public cloud segment is expected to account for the largest market share during the forecast period, due to its scalability and broad accessibility. Companies prefer public cloud environments to avoid high upfront investments in GPU hardware. Leading cloud providers offer a wide range of GPU instance types tailored for AI, gaming, and visualization workloads. Continuous improvements in cloud-native AI tools and orchestration frameworks further enhance public cloud adoption. The flexibility to expand or shrink GPU capacity based on workload needs strengthens this segment's leadership.

The healthcare & life sciences segment is expected to have the highest CAGR during the forecast period

Over the forecast period, the healthcare & life sciences segment is predicted to witness the highest growth rate, due to rising AI utilization in the sector. GPU-powered computing supports applications such as medical imaging, drug discovery, genomics, and predictive diagnostics. Cloud-based GPUs enable faster processing of large datasets, improving research outcomes and clinical decision-making. Increasing adoption of digital health tools and precision medicine also drives the need for advanced computational power. Collaboration between healthcare providers and cloud platforms is expanding rapidly.

Region with largest share:

During the forecast period, the North America region is expected to hold the largest market share, due to its strong cloud ecosystem and high adoption of AI technologies. Major GPU providers and cloud giants are headquartered in the region, strengthening its technological leadership. Enterprises across industries are rapidly integrating AI and HPC workloads supported by GPUaaS platforms. Favorable funding for AI research and digital transformation further accelerates adoption. The region also benefits from mature IT infrastructure and advanced data center capabilities.

Region with highest CAGR:

Over the forecast period, the Asia Pacific region is anticipated to exhibit the highest CAGR, driven by rapid digitization and expanding cloud adoption across emerging economies. Countries like China, India, and South Korea are investing heavily in AI innovation and GPU-powered computing. Startups and enterprises across sectors are using GPUaaS for automation, analytics, and real-time processing. Growing availability of affordable cloud services is further promoting usage. Government-backed programs supporting AI, smart cities, and digital infrastructure contribute to market acceleration.

Key players in the market

Some of the key players in GPU-as-a-Service Market include NVIDIA, Equinix M, Amazon W, OVHcloud, Microsoft, Vast.ai, Google Clo, Runpod, Alibaba Cl, Paperspace, Tencent C, Lambda La, IBM Cloud, CoreWeav, and Oracle Cl.

Key Developments:

In November 2025, IBM and the University of Dayton announced an agreement for the joint research and development of next-generation semiconductor technologies and materials. The collaboration aims to advance critical technologies for the age of AI including AI hardware, advanced packaging, and photonics.

In October 2025, Oracle announced collaboration with Microsoft to develop an integration blueprint to help manufacturers improve supply chain efficiency and responsiveness. The blueprint will enable organizations using Oracle Fusion Cloud Supply Chain & Manufacturing (SCM) to improve data-driven decision making and automate key supply chain processes by capturing live insights from factory equipment and sensors through Azure IoT Operations and Microsoft Fabric.

Service Models Covered:

• IaaS (GPU Instances)
• PaaS (AI/ML Platforms)
• SaaS (GPU-Accelerated Solutions)
• Managed GPU Services

Deployment Models Covered:

• Public Cloud
• Private Cloud
• Hybrid Cloud
• Edge GPUaaS

GPU Types Covered:

• Dedicated GPU
• Shared / Virtual GPU (vGPU)
• Data Center GPUs
• GPU Accelerators (HPC/AI GPUs)

Organization Sizes Covered:

• Small & Medium Enterprises (SMEs)
• Large Enterprises

Applications Covered:

• Deep Learning Training
• AI Inference
• Autonomous Systems & Robotics
• High-Performance Computing (HPC)
• Virtual Desktops (VDI)
• 3D Rendering & VFX
• Simulation & Modeling
• Cloud Gaming
• Data Science & Analytics

End Users Covered:

• IT & Telecom
• BFSI
• Healthcare & Life Sciences
• Automotive
• Government & Defense
• Media & Entertainment
• Education & Research
• Manufacturing
• Retail & E-commerce

Regions Covered:

• North America
  • US
  • Canada
  • Mexico
• Europe
  • Germany
  • UK
  • Italy
  • France
  • Spain
  • Rest of Europe
• Asia Pacific
  • Japan
  • China
  • India
  • Australia
  • New Zealand
  • South Korea
  • Rest of Asia Pacific
• South America
  • Argentina
  • Brazil
  • Chile
  • Rest of South America
• Middle East & Africa
  • Saudi Arabia
  • UAE
  • Qatar
  • South Africa
  • Rest of Middle East & Africa

What our report offers:

• Market share assessments for the regional and country-level segments
• Strategic recommendations for the new entrants
• Covers Market data for the years 2024, 2025, 2026, 2028, and 2032
• Market Trends (Drivers, Constraints, Opportunities, Threats, Challenges, Investment Opportunities, and recommendations)
• Strategic recommendations in key business segments based on the market estimations
• Competitive landscaping mapping the key common trends
• Company profiling with detailed strategies, financials, and recent developments
• Supply chain trends mapping the latest technological advancements

Free Customization Offerings:

All the customers of this report will be entitled to receive one of the following free customization options:

• Company Profiling
  • Comprehensive profiling of additional market players (up to 3)
  • SWOT Analysis of key players (up to 3)
• Regional Segmentation
  • Market estimations, Forecasts and CAGR of any prominent country as per the client's interest (Note: Depends on feasibility check)
• Competitive Benchmarking
  • Benchmarking of key players based on product portfolio, geographical presence, and strategic alliances

Table of Contents

1 Executive Summary

2 Preface

• 2.1 Abstract
• 2.2 Stake Holders
• 2.3 Research Scope
• 2.4 Research Methodology
  • 2.4.1 Data Mining
  • 2.4.2 Data Analysis
  • 2.4.3 Data Validation
  • 2.4.4 Research Approach
• 2.5 Research Sources
  • 2.5.1 Primary Research Sources
  • 2.5.2 Secondary Research Sources
  • 2.5.3 Assumptions

3 Market Trend Analysis

• 3.1 Introduction
• 3.2 Drivers
• 3.3 Restraints
• 3.4 Opportunities
• 3.5 Threats
• 3.6 Application Analysis
• 3.7 End User Analysis
• 3.8 Emerging Markets
• 3.9 Impact of Covid-19

4 Porters Five Force Analysis

• 4.1 Bargaining power of suppliers
• 4.2 Bargaining power of buyers
• 4.3 Threat of substitutes
• 4.4 Threat of new entrants
• 4.5 Competitive rivalry

5 Global GPU-as-a-Service Market, By Service Model

• 5.1 Introduction
• 5.2 IaaS (GPU Instances)
• 5.3 PaaS (AI/ML Platforms)
• 5.4 SaaS (GPU-Accelerated Solutions)
• 5.5 Managed GPU Services

6 Global GPU-as-a-Service Market, By Deployment Model

• 6.1 Introduction
• 6.2 Public Cloud
• 6.3 Private Cloud
• 6.4 Hybrid Cloud
• 6.5 Edge GPUaaS

7 Global GPU-as-a-Service Market, By GPU Type

• 7.1 Introduction
• 7.2 Dedicated GPU
• 7.3 Shared / Virtual GPU (vGPU)
• 7.4 Data Center GPUs
• 7.5 GPU Accelerators (HPC/AI GPUs)

8 Global GPU-as-a-Service Market, By Organization Size

• 8.1 Introduction
• 8.2 Small & Medium Enterprises (SMEs)
• 8.3 Large Enterprises

9 Global GPU-as-a-Service Market, By Application

• 9.1 Introduction
• 9.2 Deep Learning Training
• 9.3 AI Inference
• 9.4 Autonomous Systems & Robotics
• 9.5 High-Performance Computing (HPC)
• 9.6 Virtual Desktops (VDI)
• 9.7 3D Rendering & VFX
• 9.8 Simulation & Modeling
• 9.9 Cloud Gaming
• 9.10 Data Science & Analytics

10 Global GPU-as-a-Service Market, By End User

• 10.1 Introduction
• 10.2 IT & Telecom
• 10.3 BFSI
• 10.4 Healthcare & Life Sciences
• 10.5 Automotive
• 10.6 Government & Defense
• 10.7 Media & Entertainment
• 10.8 Education & Research
• 10.9 Manufacturing
• 10.10 Retail & E-commerce

11 Global GPU-as-a-Service Market, By Geography

• 11.1 Introduction
• 11.2 North America
  • 11.2.1 US
  • 11.2.2 Canada
  • 11.2.3 Mexico
• 11.3 Europe
  • 11.3.1 Germany
  • 11.3.2 UK
  • 11.3.3 Italy
  • 11.3.4 France
  • 11.3.5 Spain
  • 11.3.6 Rest of Europe
• 11.4 Asia Pacific
  • 11.4.1 Japan
  • 11.4.2 China
  • 11.4.3 India
  • 11.4.4 Australia
  • 11.4.5 New Zealand
  • 11.4.6 South Korea
  • 11.4.7 Rest of Asia Pacific
• 11.5 South America
  • 11.5.1 Argentina
  • 11.5.2 Brazil
  • 11.5.3 Chile
  • 11.5.4 Rest of South America
• 11.6 Middle East & Africa
  • 11.6.1 Saudi Arabia
  • 11.6.2 UAE
  • 11.6.3 Qatar
  • 11.6.4 South Africa
  • 11.6.5 Rest of Middle East & Africa

12 Key Developments

• 12.1 Agreements, Partnerships, Collaborations and Joint Ventures
• 12.2 Acquisitions & Mergers
• 12.3 New Product Launch
• 12.4 Expansions
• 12.5 Other Key Strategies

13 Company Profiling

• 13.1 NVIDIA
• 13.2 Equinix Metal
• 13.3 Amazon Web Services
• 13.4 OVHcloud
• 13.5 Microsoft Azure
• 13.6 Vast.ai
• 13.7 Google Cloud Platform
• 13.8 Runpod
• 13.9 Alibaba Cloud
• 13.10 Paperspace
• 13.11 Tencent Cloud
• 13.12 Lambda Labs
• 13.13 IBM Cloud
• 13.14 CoreWeave
• 13.15 Oracle Cloud