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市场调查报告书
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1889199

全球GPU即服务（GPUaaS）市场：未来预测（至2032年）－依服务模式、部署方式、GPU类型、组织规模、应用程式、最终用户和地区进行分析

GPU-as-a-Service Market Forecasts to 2032 - Global Analysis By Service Model (IaaS, PaaS, SaaS, and Managed GPU Services), Deployment Model, GPU Type, Organization Size, Application, End User and By Geography
出版日期: | 出版商: Stratistics Market Research Consulting | 英文 | 商品交期: 2-3个工作天内

价格

根据 Stratestix MRC 的数据，全球 GPU 即服务 (GPUaaS) 市场预计到 2025 年将达到 47.4 亿美元，到 2032 年将达到 225 亿美元，预测期内复合年增长率为 24.9%。

GPUaaS 是云端解决方案，可按需提供可扩充的 GPU 运算能力。企业无需投资昂贵的 GPU 基础设施，即可使用虚拟化 GPU 来运行 AI、机器学习、分析、渲染和图形密集型。该服务提供付费使用制的定价模式、快速的资源部署和高效的效能扩展。透过利用 GPUaaS，企业可以降低硬体成本、提高运算速度，并透过云端供应商提供的灵活、可靠且可远端存取的 GPU 资源来支援高负载工作。

对人工智慧和机器学习的需求不断增长

传统的本地部署基础设施无法满足现代人工智慧模型所需的运算负载。 GPUaaS 提供灵活的随选访问，从而降低资本支出并加快部署速度。生成式人工智慧和大型语言模式的广泛应用进一步推动了对云端基础GPU 资源的需求。企业越来越依赖高效能 GPU 来运行大规模深度学习、资料分析和推理工作负载。因此，人工智慧和机器学习的日益普及是加速 GPUaaS 市场成长的关键因素。

多租户环境下的效能差异

共用基础架构可能造成资源争用，影响即时性或延迟敏感型工作负载。这种不稳定性使得企业难以保证人工智慧训练和图形密集型任务的可预测执行。儘管供应商正在投资硬体隔离、进阶调度和专用 GPU 实例，但这些解决方案会增加维运复杂性。对于拥有关键任务型应用程式的客户而言，为了确保稳定性，他们可能仍然更倾向于使用本地部署的 GPU丛集。

来自非传统行业的需求不断增长

零售、教育、农业和物流等行业正在利用GPU进行进阶分析、模拟和自动化。云端基础GPU正在催生新的应用场景，包括精密农业、虚拟教室和供应链最佳化。随着数位转型加速，这些产业需要可扩展的运算能力，而无需进行大规模的基础设施投资。 GPUaaS平台的通用性使其非常适合支援传统技术领域以外的各种工作负载。

来自其他计算技术的竞争

TPU、客製化AI加速器、FPGA和专用ASIC等解决方案可提供针对特定AI任务最佳化的效能。这些替代技术在功耗和成本效益方面可以超越GPU。主要云端服务供应商正在加速开发自研晶片，以减少对GPU的依赖。这种转变可能会限制基于GPU的服务的长期优势。因此，竞争架构的兴起对GPUaaS市场构成了重大威胁。

新冠疫情的感染疾病：

新冠疫情重塑了企业运算的优先事项，加速了云端运算的普及，并推动了对GPU即服务（GPUaaS）的需求。远端办公的增加导致企业更加依赖云端资源进行人工智慧开发、虚拟桌面和模拟工作负载。硬体供应链的中断也促使企业转向云端託管GPU，而非本地部署系统。同时，医疗保健和电子商务等产业对人工智慧驱动的分析应用也显着增加。在充满不确定性的时期，云端基础的GPU平台能够帮助企业更快地进行实验和模型部署。

在预测期内，公共云端细分市场将占据最大的市场份额。

由于其扩充性和广泛的可访问性，预计在预测期内，公共云端领域将占据最大的市场份额。企业倾向选择公共云端环境，以避免在GPU硬体方面进行高额的初始投资。主流云端服务供应商提供各种针对人工智慧、游戏和视觉化工作负载最佳化的GPU实例类型。云端原生人工智慧工具和编配框架的持续改进进一步推动了公共云端的普及。根据工作负载需求弹性扩展或缩减GPU容量的能力进一步增强了这一领域的优势。

在预测期内，医疗保健和生命科学产业的复合年增长率将最高。

由于人工智慧的日益普及，医疗保健和生命科学领域预计将在预测期内呈现最高的成长率。基于GPU的运算能力为医学影像、药物研发、基因组学和预测诊断等应用提供了强大支援。云端基础GPU能够更快地处理大型资料集，有助于提升研究成果和临床决策水准。数位健康工具和精准医疗的日益普及也推动了对先进运算能力的需求。医疗服务提供者与云端平台之间的合作正在迅速扩展。

占比最大的地区：

预计北美将在预测期内占据最大的市场份额，这主要得益于其强大的云端生态系和人工智慧技术的高度普及。主要的GPU供应商和云端巨头都将总部设在该地区，进一步巩固了其技术领先地位。各行各业的公司都在快速整合由GPUaaS平台支援的人工智慧和高效能运算工作负载。对人工智慧研究和数位转型的有利资金筹措也进一步加速了其应用。此外，该地区还受益于成熟的IT基础设施和先进的资料中心能力。

年复合成长率最高的地区：

预计亚太地区在预测期内将实现最高的复合年增长率，这主要得益于新兴经济体快速的数位化和日益普及的云端运算。中国、印度和韩国等国正大力投资人工智慧创新和基于GPU的运算。各行各业的Start-Ups和大型企业都在利用GPU即服务（GPUaaS）进行自动化、分析和即时处理。价格合理的云端服务的日益普及进一步推动了GPU的采用。政府主导的人工智慧、智慧城市和数位基础设施项目也促进了市场加速发展。

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  • 公司简介
    • 对最多三家其他公司进行全面分析
    • 对主要企业进行SWOT分析（最多3家公司）
  • 区域分类
    • 根据客户兴趣对主要国家进行市场估算、预测和复合年增长率分析（註：基于可行性检查）
  • 竞争基准化分析
    • 基于产品系列、地域覆盖和策略联盟对主要企业基准化分析

目录

第一章执行摘要

第二章 引言

  • 概述
  • 相关利益者
  • 分析范围
  • 分析方法
  • 分析材料

第三章 市场趋势分析

  • 司机
  • 抑制因素
  • 机会
  • 威胁
  • 应用分析
  • 终端用户分析
  • 新兴市场
  • 新冠疫情的影响

第四章 波特五力分析

  • 供应商的议价能力
  • 买方议价能力
  • 替代产品的威胁
  • 新进入者的威胁
  • 竞争对手之间的竞争

5. 全球GPU即服务市场（依服务模式划分）

  • IaaS（GPU实例）
  • PaaS（人工智慧/机器学习平台）
  • SaaS（GPU加速解法）
  • 託管 GPU 服务

6. 全球GPU即服务市场以部署方式划分

  • 公共云端
  • 私有云端
  • 混合云端
  • 边缘 GPUaaS

7. 全球GPU即服务市场（依GPU类型划分）

  • 专用GPU
  • 共用/虚拟 GPU (vGPU)
  • 资料中心GPU
  • GPU加速器（高效能运算/人工智慧GPU）

8. 按企业规模分類的全球GPU即服务市场

  • 中小企业
  • 大公司

9. 全球GPU即服务市场（按应用划分）

  • 深度学习训练
  • 人工智慧推理
  • 自主系统、机器人
  • 高效能运算（HPC）
  • 虚拟桌面（VDI）
  • 3D渲染和视觉特效
  • 模拟与建模
  • 云端游戏
  • 资料科学与分析

10. 全球GPU即服务市场（依最终用户划分）

  • 资讯科技、通讯
  • BFSI
  • 医学与生命科​​学
  • 车
  • 政府。国防
  • 媒体与娱乐
  • 教育、研究
  • 製造业
  • 零售、电子商务

11. 全球GPU即服务市场（按地区划分）

  • 北美洲
    • 美国
    • 加拿大
    • 墨西哥
  • 欧洲
    • 德国
    • 英国
    • 义大利
    • 法国
    • 西班牙
    • 其他欧洲
  • 亚太地区
    • 日本
    • 中国
    • 印度
    • 澳洲
    • 纽西兰
    • 韩国
    • 亚太其他地区
  • 南美洲
    • 阿根廷
    • 巴西
    • 智利
    • 其他南美国家
  • 中东和非洲
    • 沙乌地阿拉伯
    • 阿拉伯聯合大公国
    • 卡达
    • 南非
    • 其他中东和非洲地区

第十二章：主要趋势

  • 合约、商业伙伴关係和合资企业
  • 企业合併（M&A）
  • 新产品上市
  • 业务拓展
  • 其他关键策略

第十三章：企业概况

  • NVIDIA
  • Equinix Metal
  • Amazon Web Services
  • OVHcloud
  • Microsoft Azure
  • Vast.ai
  • Google Cloud Platform
  • Runpod
  • Alibaba Cloud
  • Paperspace
  • Tencent Cloud
  • Lambda Labs
  • IBM Cloud
  • CoreWeave
  • Oracle Cloud
Product Code: SMRC32659

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

List of Tables

  • Table 1 Global GPU-as-a-Service Market Outlook, By Region (2024-2032) ($MN)
  • Table 2 Global GPU-as-a-Service Market Outlook, By Service Model (2024-2032) ($MN)
  • Table 3 Global GPU-as-a-Service Market Outlook, By IaaS (GPU Instances) (2024-2032) ($MN)
  • Table 4 Global GPU-as-a-Service Market Outlook, By PaaS (AI/ML Platforms) (2024-2032) ($MN)
  • Table 5 Global GPU-as-a-Service Market Outlook, By SaaS (GPU-Accelerated Solutions) (2024-2032) ($MN)
  • Table 6 Global GPU-as-a-Service Market Outlook, By Managed GPU Services (2024-2032) ($MN)
  • Table 7 Global GPU-as-a-Service Market Outlook, By Deployment Model (2024-2032) ($MN)
  • Table 8 Global GPU-as-a-Service Market Outlook, By Public Cloud (2024-2032) ($MN)
  • Table 9 Global GPU-as-a-Service Market Outlook, By Private Cloud (2024-2032) ($MN)
  • Table 10 Global GPU-as-a-Service Market Outlook, By Hybrid Cloud (2024-2032) ($MN)
  • Table 11 Global GPU-as-a-Service Market Outlook, By Edge GPUaaS (2024-2032) ($MN)
  • Table 12 Global GPU-as-a-Service Market Outlook, By GPU Type (2024-2032) ($MN)
  • Table 13 Global GPU-as-a-Service Market Outlook, By Dedicated GPU (2024-2032) ($MN)
  • Table 14 Global GPU-as-a-Service Market Outlook, By Shared / Virtual GPU (vGPU) (2024-2032) ($MN)
  • Table 15 Global GPU-as-a-Service Market Outlook, By Data Center GPUs (2024-2032) ($MN)
  • Table 16 Global GPU-as-a-Service Market Outlook, By GPU Accelerators (HPC/AI GPUs) (2024-2032) ($MN)
  • Table 17 Global GPU-as-a-Service Market Outlook, By Organization Size (2024-2032) ($MN)
  • Table 18 Global GPU-as-a-Service Market Outlook, By Small & Medium Enterprises (SMEs) (2024-2032) ($MN)
  • Table 19 Global GPU-as-a-Service Market Outlook, By Large Enterprises (2024-2032) ($MN)
  • Table 20 Global GPU-as-a-Service Market Outlook, By Application (2024-2032) ($MN)
  • Table 21 Global GPU-as-a-Service Market Outlook, By Deep Learning Training (2024-2032) ($MN)
  • Table 22 Global GPU-as-a-Service Market Outlook, By AI Inference (2024-2032) ($MN)
  • Table 23 Global GPU-as-a-Service Market Outlook, By Autonomous Systems & Robotics (2024-2032) ($MN)
  • Table 24 Global GPU-as-a-Service Market Outlook, By High-Performance Computing (HPC) (2024-2032) ($MN)
  • Table 25 Global GPU-as-a-Service Market Outlook, By Virtual Desktops (VDI) (2024-2032) ($MN)
  • Table 26 Global GPU-as-a-Service Market Outlook, By 3D Rendering & VFX (2024-2032) ($MN)
  • Table 27 Global GPU-as-a-Service Market Outlook, By Simulation & Modeling (2024-2032) ($MN)
  • Table 28 Global GPU-as-a-Service Market Outlook, By Cloud Gaming (2024-2032) ($MN)
  • Table 29 Global GPU-as-a-Service Market Outlook, By Data Science & Analytics (2024-2032) ($MN)
  • Table 30 Global GPU-as-a-Service Market Outlook, By End User (2024-2032) ($MN)
  • Table 31 Global GPU-as-a-Service Market Outlook, By IT & Telecom (2024-2032) ($MN)
  • Table 32 Global GPU-as-a-Service Market Outlook, By BFSI (2024-2032) ($MN)
  • Table 33 Global GPU-as-a-Service Market Outlook, By Healthcare & Life Sciences (2024-2032) ($MN)
  • Table 34 Global GPU-as-a-Service Market Outlook, By Automotive (2024-2032) ($MN)
  • Table 35 Global GPU-as-a-Service Market Outlook, By Government & Defense (2024-2032) ($MN)
  • Table 36 Global GPU-as-a-Service Market Outlook, By Media & Entertainment (2024-2032) ($MN)
  • Table 37 Global GPU-as-a-Service Market Outlook, By Education & Research (2024-2032) ($MN)
  • Table 38 Global GPU-as-a-Service Market Outlook, By Manufacturing (2024-2032) ($MN)
  • Table 39 Global GPU-as-a-Service Market Outlook, By Retail & E-commerce (2024-2032) ($MN)

Note: Tables for North America, Europe, APAC, South America, and Middle East & Africa Regions are also represented in the same manner as above.