GPU 렌탈 시장 : 점유율 분석, 업계 동향 및 통계, 성장 예측(2026-2031년)

According to Mordor Intelligence, the GPU rental market size is expected to increase from USD 34.62 billion in 2025 to USD 52.04 billion in 2026 and reach USD 198.74 billion by 2031, growing at a CAGR of 30.73% over 2026-2031.

This report is Segmented by Deployment Type (Shared Public GPU Cloud, More), Service Model (GPU Infrastructure As A Service, and More), Application (High-Performance Computing and Scientific Computing, and More), Enterprise Size (Start-Ups and Small and Medium Enterprises, and More), End-User (Healthcare and Life Sciences, BFSI, and More), and Geography. The Market Forecasts are Provided in Terms of Value (USD).

Global GPU Rental Market Trends and Insights

Rising Generative AI And LLM Training Demand

The GPU rental market is seeing stronger baseline demand as generative AI moves from pilot work into regular production use across more teams and products. RunPod said in June 2026 that its platform had reached 1 million developers, indicating how broad the base of compute users has become for rented GPU access. KDDI launched on-demand access to NVIDIA GB200 NVL72 systems in April 2026, and SoftBank added NVIDIA GB200 NVL72 beta rental in March 2026, which shows that providers are adding new capacity around current AI development needs. NVIDIA also invested USD 2 billion in Nebius in March 2026 and tied that partnership to more than 5 GW of NVIDIA computing by 2030, which signals confidence in sustained downstream infrastructure demand. These developments matter because the GPU rental market benefits when inference, fine-tuning, and model deployment all require ongoing access instead of one-time bursts. Providers that secured supply relationships early are therefore in a stronger position to hold utilization as generative AI adoption scales further.

Shift From CapEx to Pay-Per-Use GPU Access

The GPU rental market continues to benefit from users who want compute without a large upfront hardware commitment. KDDI stated that its GPU cloud launched with no upfront investment requirement, which directly supports the case for on-demand access over owned infrastructure for many workloads. This model suits projects where traffic, model size, and commercial timing can change quickly after launch. It also gives users a practical way to move to newer systems without waiting for owned assets to be fully utilized or retired. RunPod's 1 million developer milestone reinforces that a large share of the GPU rental market now includes teams that prefer flexible access over fixed procurement cycles. Even when larger firms later build dedicated environments, rental often remains part of the operating model for testing, overflow demand, and new application rollout.

HBM and Advanced Packaging Supply Constraints

The GPU rental market still depends on the pace at which the newest systems can be brought into service. KDDI launched NVIDIA GB200 NVL72 access in April 2026, SoftBank added GB200 NVL72 beta rental in March 2026, and Nebius mapped a multi-year buildout with NVIDIA across future computing platforms, which shows how growth is tied to timely hardware availability. When several operators target the same generation of systems simultaneously, procurement strength becomes a competitive filter. That tends to favor providers with deeper supplier ties, stronger financing, or earlier reservation windows. Smaller platforms can still compete, but they may expand more slowly when access to current hardware tightens. In the GPU rental market, this does not stop demand, but it can delay capacity additions and widen the gap between the largest providers and the rest of the field.

Other drivers and restraints analyzed in the detailed report include:

1. Fractional GPU Orchestration and Multi-Tenant Scheduling
2. Sovereign AI And Regulated Workload Adoption
3. Data Sovereignty and Cross-Border Compliance Risk

For complete list of drivers and restraints, kindly check the Table Of Contents.

Segment Analysis

Shared public GPU cloud held 48.13% of the GPU rental market share in 2025, making it the largest deployment mode because it offers broad reach, pooled capacity, and easier handling of burst demand. Private or sovereign-hosted GPU cloud is projected to expand at a 31.58% CAGR through 2031, reflecting stronger demand from buyers that want dedicated resources and tighter control over data location. In the GPU rental market, shared environments still set the baseline because they spread infrastructure across many users and reduce the burden of internal capacity planning. That advantage remains important for development teams that need quick provisioning and the flexibility to scale usage up or down as models move through testing and deployment.

The growth pattern is shifting, though, because sovereign and private models are becoming more practical to operate. In 2026, Canonical said NVIDIA donated the GPU DRA driver to CNCF, which helps private Kubernetes clusters use more standardized GPU scheduling and allocation methods. IBM Research also continued work on transparent, elastic provisioning for multi-tenant cloud services, which supports better use of dedicated environments without sacrificing as much operational efficiency. KDDI's launch in Japan and Deutsche Telekom's industrial AI cloud in Germany show that domestic operators are building controlled GPU environments around local enterprise and public requirements. This means the GPU rental market is no longer defined only by public cloud scale, it is also being shaped by who can provide controlled access with local accountability.

GPU Infrastructure as a Service accounted for 58.32% of service model revenue in 2025, indicating that direct access to compute remained the preferred route for many engineering teams. Serverless and container GPU services are projected to grow at a 32.17% CAGR through 2031, which reflects demand for simpler deployment paths and less hands-on infrastructure work. This shift matters because more users now want to focus on application logic, model serving, and workflow performance rather than cluster setup. In the GPU rental market, this lowers the skills barrier and broadens the addressable customer base to smaller development teams and product groups.

The service model stack is also tightening faster than it did in earlier cloud cycles. RunPod's 1 million developer milestone suggests that developer-focused platforms are already operating at meaningful scale inside the GPU rental market. Vast.ai's June 2026 product update added NVIDIA B200 and B300 Blackwell Ultra GPUs, indicating that platform operators are pairing easier access models with newer hardware generations rather than limiting advanced systems to larger contracts. Managed environments still serve users who need more support, but the direction of travel is clear. As service abstraction improves, more of the GPU rental industry can compete on developer experience and speed to production rather than solely on raw hardware access.

Complete Report Scope:

• By Deployment Type
  • Shared Public GPU Cloud
  • Dedicated / Bare-Metal GPU Cloud
  • Private or Sovereign Hosted GPU Cloud
• By Service Model
  • GPU Infrastructure as a Service
  • Managed GPU Platform as a Service
  • Serverless / Container GPU Services
• By Application
  • Artificial Intelligence and Machine Learning
  • High-Performance Computing and Scientific Computing
  • Rendering, VFX, Cloud Gaming, and 3D Visualization
  • Other Applications
• By Enterprise Size
  • Start-ups and Small and Medium Enterprises
  • Large Enterprises
  • Government, Academic, and Research Institutions
• By End-User Industry
  • IT, Cloud, and Communications
  • BFSI
  • Automotive and Mobility
  • Healthcare and Life Sciences
  • Media and Entertainment
  • Government, Defense, Education, and Research
  • Other End-User Industries
• By Geography
  • North America
    • United States
    • Canada
    • Mexico
  • Europe
    • Germany
    • United Kingdom
    • France
    • Italy
    • Rest of Europe
  • Asia-Pacific
    • China
    • Japan
    • South Korea
    • India
    • Southeast Asia
    • Rest of Asia-Pacific
  • South America
  • Middle East and Africa

Geography Analysis

North America held 51.25% of the GPU rental market share in 2025, making it the largest regional base for both demand and supply. The region benefits from the concentration of hyperscalers, AI labs, and developer platforms that already operate at meaningful scale in commercial AI. RunPod in June 2026, which had passed 1 million developers, supports the view that the North American GPU rental market remains deeply tied to active product development and deployment communities. Canada added a second layer of regional demand through its Sovereign AI Compute Strategy, which committed up to USD 1.7 billion across compute access and public infrastructure.

Europe is ranked behind North America, but its role in the GPU rental market is becoming more strategic as compliance and data residency carry greater weight in procurement decisions. The EU AI Act increased the need for documented governance and local oversight in certain AI uses, which supports demand for regionally controlled infrastructure. Deutsche Telekom launched Germany's first industrial AI cloud in Munich in early 2026, featuring nearly 10,000 NVIDIA Blackwell GPUs and up to 0.5 ExaFLOPS of compute, demonstrating that Europe is building meaningful domestic capacity rather than relying solely on external providers. This gives the European GPU rental market a stronger sovereign and enterprise compliance profile, especially for users that want local accountability and regional service coverage.

Asia-Pacific is projected to grow at a 32.54% CAGR through 2031, which makes it the fastest-growing region in the GPU rental market size. Japan is already showing that momentum through direct service launches. KDDI launched GPU cloud capacity in April 2026 with NVIDIA GB200 NVL72 access, and SoftBank added NVIDIA GB200 NVL72 beta rental in March 2026, both on Japan-hosted infrastructure. These moves suggest that domestic availability, local support, and regulated sector alignment are becoming central buying factors across the region. Asia-Pacific therefore appears positioned for faster expansion because it combines commercial AI demand with rising national interest in local compute control. South America and the Middle East and Africa remain earlier-stage parts of the GPU rental market, but the same sovereign and localization themes could support their next phase of capacity buildout.

1. Lambda, Inc.
2. Runpod Inc.
3. Vast.ai, Inc.
4. Crusoe Energy Systems LLC
5. Fluidstack Ltd.
6. Nebius B.V.
7. Scaleway SAS
8. OVH Groupe SA
9. Akamai Technologies, Inc.
10. DigitalOcean, LLC
11. Oracle Corporation
12. Alibaba Cloud Computing Co., Ltd.
13. Google LLC
14. Microsoft Corporation
15. Amazon Web Services, Inc.
16. IBM Corporation

Additional Benefits:

• The market estimate (ME) sheet in Excel format
• 3 months of analyst support

TABLE OF CONTENTS

1 INTRODUCTION

• 1.1 Study Assumptions and Market Definition
• 1.2 Scope of the Study

2 RESEARCH METHODOLOGY

3 EXECUTIVE SUMMARY

4 MARKET LANDSCAPE

• 4.1 Market Overview
• 4.2 Market Drivers
  • 4.2.1 Rising Generative AI and LLM Training Demand
  • 4.2.2 Shift From CapEx to Pay-Per-Use GPU Access
  • 4.2.3 Fractional GPU Orchestration and Multi-Tenant Scheduling
  • 4.2.4 Sovereign AI and Regulated Workload Adoption
  • 4.2.5 Cloud Gaming and Real-Time Rendering Expansion
  • 4.2.6 Liquid-Cooled High-Density GPU Pod Deployment
• 4.3 Market Restraints
  • 4.3.1 HBM and Advanced Packaging Supply Constraints
  • 4.3.2 Data Sovereignty and Cross-Border Compliance Risk
  • 4.3.3 Power Tariff Pressure and Carbon Reporting Burden
  • 4.3.4 GPU Spot Capacity Volatility and Margin Compression
• 4.4 Industry Value Chain Analysis
• 4.5 Technological Outlook
• 4.6 Impact of Macroeconomic Factors on the Market
• 4.7 Porter's Five Forces Analysis
  • 4.7.1 Bargaining Power of Suppliers
  • 4.7.2 Bargaining Power of Buyers
  • 4.7.3 Threat of New Entrants
  • 4.7.4 Threat of Substitutes
  • 4.7.5 Industry Rivalry

5 MARKET SIZE AND GROWTH FORECASTS (VALUE)

• 5.1 By Deployment Type
  • 5.1.1 Shared Public GPU Cloud
  • 5.1.2 Dedicated / Bare-Metal GPU Cloud
  • 5.1.3 Private or Sovereign Hosted GPU Cloud
• 5.2 By Service Model
  • 5.2.1 GPU Infrastructure as a Service
  • 5.2.2 Managed GPU Platform as a Service
  • 5.2.3 Serverless / Container GPU Services
• 5.3 By Application
  • 5.3.1 Artificial Intelligence and Machine Learning
  • 5.3.2 High-Performance Computing and Scientific Computing
  • 5.3.3 Rendering, VFX, Cloud Gaming, and 3D Visualization
  • 5.3.4 Other Applications
• 5.4 By Enterprise Size
  • 5.4.1 Start-ups and Small and Medium Enterprises
  • 5.4.2 Large Enterprises
  • 5.4.3 Government, Academic, and Research Institutions
• 5.5 By End-User Industry
  • 5.5.1 IT, Cloud, and Communications
  • 5.5.2 BFSI
  • 5.5.3 Automotive and Mobility
  • 5.5.4 Healthcare and Life Sciences
  • 5.5.5 Media and Entertainment
  • 5.5.6 Government, Defense, Education, and Research
  • 5.5.7 Other End-User Industries
• 5.6 By Geography
  • 5.6.1 North America
    • 5.6.1.1 United States
    • 5.6.1.2 Canada
    • 5.6.1.3 Mexico
  • 5.6.2 Europe
    • 5.6.2.1 Germany
    • 5.6.2.2 United Kingdom
    • 5.6.2.3 France
    • 5.6.2.4 Italy
    • 5.6.2.5 Rest of Europe
  • 5.6.3 Asia-Pacific
    • 5.6.3.1 China
    • 5.6.3.2 Japan
    • 5.6.3.3 South Korea
    • 5.6.3.4 India
    • 5.6.3.5 Southeast Asia
    • 5.6.3.6 Rest of Asia-Pacific
  • 5.6.4 South America
  • 5.6.5 Middle East and Africa

6 COMPETITIVE LANDSCAPE

• 6.1 Market Concentration
• 6.2 Strategic Moves
• 6.3 Vendor Positioning Analysis
• 6.4 Company Profiles (includes Global Level Overview, Market Level Overview, Core Segments, Financials as available, Strategic Information, Market Rank/Share, Products and Services, Recent Developments)
  • 6.4.1 Lambda, Inc.
  • 6.4.2 Runpod Inc.
  • 6.4.3 Vast.ai, Inc.
  • 6.4.4 Crusoe Energy Systems LLC
  • 6.4.5 Fluidstack Ltd.
  • 6.4.6 Nebius B.V.
  • 6.4.7 Scaleway SAS
  • 6.4.8 OVH Groupe SA
  • 6.4.9 Akamai Technologies, Inc.
  • 6.4.10 DigitalOcean, LLC
  • 6.4.11 Oracle Corporation
  • 6.4.12 Alibaba Cloud Computing Co., Ltd.
  • 6.4.13 Google LLC
  • 6.4.14 Microsoft Corporation
  • 6.4.15 Amazon Web Services, Inc.
  • 6.4.16 IBM Corporation

7 MARKET OPPORTUNITIES AND FUTURE OUTLOOK

• 7.1 White-Space and Unmet-Need Assessment