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全球GPU即服務（GPUaaS）市場：未來預測（至2032年）－依服務模式、部署方式、GPU類型、組織規模、應用程式、最終用戶和地區進行分析

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個工作天內

價格

根據 Stratestix MRC 的數據，全球 GPU 即服務 (GPUaaS) 市場預計到 2025 年將達到 47.4 億美元，到 2032 年將達到 225 億美元，預測期內複合年成長率為 24.9%。

GPUaaS 是雲端解決方案，可按需提供可擴充的 GPU 運算能力。企業無需投資昂貴的 GPU 基礎設施，即可使用虛擬化 GPU 來運行 AI、機器學習、分析、渲染和圖形密集型。該服務提供付費使用制的定價模式、快速的資源部署和高效的效能擴展。透過利用 GPUaaS，企業可以降低硬體成本、提高運算速度，並透過雲端供應商提供的靈活、可靠且可遠端存取的 GPU 資源來支援高負載工作。

對人工智慧和機器學習的需求不斷成長

傳統的本地部署基礎設施無法滿足現代人工智慧模型所需的運算負載。 GPUaaS 提供靈活的隨選訪問，從而降低資本支出並加快部署速度。生成式人工智慧和大型語言模式的廣泛應用進一步推動了對雲端基礎GPU 資源的需求。企業越來越依賴高效能 GPU 來運行大規模深度學習、資料分析和推理工作負載。因此，人工智慧和機器學習的日益普及是加速 GPUaaS 市場成長的關鍵因素。

多租戶環境下的效能差異

共用基礎架構可能造成資源爭用，影響即時性或延遲敏感型工作負載。這種不穩定性使得企業難以保證人工智慧訓練和圖形密集型任務的可預測執行。儘管供應商正在投資硬體隔離、進階調度和專用 GPU 實例，但這些解決方案會增加維運複雜性。對於擁有關鍵任務型應用程式的客戶而言，為了確保穩定性，他們可能仍然更傾向於使用本地部署的 GPU叢集。

來自非傳統行業的需求不斷成長

零售、教育、農業和物流等行業正在利用GPU進行進階分析、模擬和自動化。雲端基礎GPU正在催生新的應用場景，包括精密農業、虛擬教室和供應鏈最佳化。隨著數位轉型加速，這些產業需要可擴展的運算能力，而無需進行大規模的基礎設施投資。 GPUaaS平台的通用性使其非常適合支援傳統技術領域以外的各種工作負載。

來自其他計算技術的競爭

TPU、客製化AI加速器、FPGA和專用ASIC等解決方案可提供針對特定AI任務最佳化的效能。這些替代技術在功耗和成本效益方面可以超越GPU。主要雲端服務供應商正在加速開發自研晶片，以減少對GPU的依賴。這種轉變可能會限制基於GPU的服務的長期優勢。因此，競爭架構的興起對GPUaaS市場構成了重大威脅。

新冠疫情的感染疾病：

新冠疫情重塑了企業運算的優先事項，加速了雲端運算的普及，並推動了對GPU即服務（GPUaaS）的需求。遠端辦公的增加導致企業更加依賴雲端資源進行人工智慧開發、虛擬桌面和模擬工作負載。硬體供應鏈的中斷也促使企業轉向雲端託管GPU，而非本地部署系統。同時，醫療保健和電子商務等產業對人工智慧驅動的分析應用也顯著增加。在充滿不確定性的時期，雲端基礎的GPU平台能夠幫助企業更快地進行實驗和模型部署。

在預測期內，公共雲端細分市場將佔據最大的市場佔有率。

由於其擴充性和廣泛的可訪問性，預計在預測期內，公共雲端領域將佔據最大的市場佔有率。企業傾向選擇公共雲端環境，以避免在GPU硬體方面進行高額的初始投資。主流雲端服務供應商提供各種針對人工智慧、遊戲和視覺化工作負載最佳化的GPU實例類型。雲端原生人工智慧工具和編配框架的持續改進進一步推動了公共雲端的普及。根據工作負載需求彈性擴展或縮減GPU容量的能力進一步增強了這一領域的優勢。

在預測期內，醫療保健和生命科學產業的複合年成長率將最高。

由於人工智慧的日益普及，醫療保健和生命科學領域預計將在預測期內呈現最高的成長率。基於GPU的運算能力為醫學影像、藥物研發、基因組學和預測診斷等應用提供了強大支援。雲端基礎GPU能夠更快地處理大型資料集，有助於提升研究成果和臨床決策水準。數位健康工具和精準醫療的日益普及也推動了對先進運算能力的需求。醫療服務提供者與雲端平台之間的合作正在迅速擴展。

佔比最大的地區：

預計北美將在預測期內佔據最大的市場佔有率，這主要得益於其強大的雲端生態系和人工智慧技術的高度普及。主要的GPU供應商和雲端巨頭都將總部設在該地區，進一步鞏固了其技術領先地位。各行各業的公司都在快速整合由GPUaaS平台支援的人工智慧和高效能運算工作負載。對人工智慧研究和數位轉型的有利資金籌措也進一步加速了其應用。此外，該地區還受益於成熟的IT基礎設施和先進的資料中心能力。

年複合成長率最高的地區：

預計亞太地區在預測期內將實現最高的複合年成長率，這主要得益於新興經濟體快速的數位化和日益普及的雲端運算。中國、印度和韓國等國正大力投資人工智慧創新和基於GPU的運算。各行各業的Start-Ups和大型企業都在利用GPU即服務（GPUaaS）進行自動化、分析和即時處理。價格合理的雲端服務的日益普及進一步推動了GPU的採用。政府主導的人工智慧、智慧城市和數位基礎設施項目也促進了市場加速發展。

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目錄

第1章執行摘要

第2章 引言

  • 概述
  • 相關利益者
  • 分析範圍
  • 分析方法
  • 分析材料

第3章 市場趨勢分析

  • 促進要素
  • 抑制因素
  • 機會
  • 威脅
  • 應用分析
  • 終端用戶分析
  • 新興市場
  • 新冠疫情的影響

第4章 波特五力分析

  • 供應商的議價能力
  • 買方議價能力
  • 替代產品的威脅
  • 新進入者的威脅
  • 競爭對手之間的競爭

5. 全球GPU即服務市場（依服務模式分類）

  • IaaS（GPU實例）
  • PaaS（人工智慧/機器學習平台）
  • SaaS（GPU加速解法）
  • 託管 GPU 服務

6. 全球GPU即服務市場以部署方式分類

  • 公共雲端
  • 私有雲端
  • 混合雲端
  • 邊緣 GPUaaS

7. 全球GPU即服務市場（依GPU類型分類）

  • 專用GPU
  • 共用/虛擬 GPU (vGPU)
  • 資料中心GPU
  • GPU加速器（高效能運算/人工智慧GPU）

8. 按企業規模分類的全球GPU即服務市場

  • 中小企業
  • 主要企業

9. 全球GPU即服務市場（按應用分類）

  • 深度學習訓練
  • 人工智慧推理
  • 自主系統、機器人
  • 高效能運算（HPC）
  • 虛擬桌面（VDI）
  • 3D渲染和視覺特效
  • 模擬與建模
  • 雲端遊戲
  • 資料科學與分析

10. 全球GPU即服務市場（依最終用戶分類）

  • 資訊科技、通訊
  • BFSI
  • 醫學與生命科​​學
  • 車
  • 政府。國防
  • 媒體與娛樂
  • 教育、研究
  • 製造業
  • 零售、電子商務

11. 全球GPU即服務市場（按地區分類）

  • 北美洲
    • 美國
    • 加拿大
    • 墨西哥
  • 歐洲
    • 德國
    • 英國
    • 義大利
    • 法國
    • 西班牙
    • 其他歐洲
  • 亞太地區
    • 日本
    • 中國
    • 印度
    • 澳洲
    • 紐西蘭
    • 韓國
    • 亞太其他地區
  • 南美洲
    • 阿根廷
    • 巴西
    • 智利
    • 其他南美國家
  • 中東和非洲
    • 沙烏地阿拉伯
    • 阿拉伯聯合大公國
    • 卡達
    • 南非
    • 其他中東和非洲地區

第12章：主要趨勢

  • 合約、商業夥伴關係和合資企業
  • 企業合併（M&A）
  • 新產品上市
  • 業務拓展
  • 其他關鍵策略

第13章：企業概況

  • 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.