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

According to Mordor Intelligence, the asia-Pacific data center GPU market size is projected to expand from USD 17.89 billion in 2025 and USD 22.15 billion in 2026 to USD 47.14 billion by 2031, registering a 16.3% CAGR between 2026 and 2031.

This report is Segmented by Deployment Type (Cloud Data Centers, and More), GPU Type (Training GPUs and Inference GPUs), Interconnect (PCIe-Based GPUs and High-Bandwidth Interconnect GPUs), Workload Type (AI and ML, HPC, and More), End-User (Hyperscalers/CSPs, Enterprises, and More), and by Country (China, Japan, South Korea, India, and More). The Market Forecasts are Provided in Value (USD).

Asia-Pacific Data Center GPU Market Trends and Insights

Surge in AI Training Workloads in Hyperscale Cloud Data Centers

Hyperscale providers are rolling out clusters with more than 100,000 accelerators to support trillion-parameter model training. Microsoft and OpenAI's landmark USD 100 billion Stargate project, though U.S.-based, set the bar for regional players racing to reach comparable scale. Tencent Cloud expanded its fleet in 2025 to meet skyrocketing demand from domestic LLM developers, and Baidu's Wenxin platform added continuous batches of H100 cards to keep sub-second response for 200 million daily users. Regional capital-expenditure outlays are on pace to claim a significant share of the global USD 527 billion hyperscaler budget in 2026 as cloud operators position Asia-Pacific as the world's largest AI compute hub. Cloud-delivered GPU-as-a-Service products shorten launch cycles but concentrate pricing power in a handful of vendors, pressuring smaller rivals unable to secure volume contracts.

Rise of Sovereign AI Clouds Demanding In-Region GPU Clusters

Governments now require sensitive AI workloads to run on domestic infrastructure. Japan's Digital Agency, working with Fujitsu and Microsoft, committed JPY 1.6 trillion (USD 10.3 billion) in 2024 to build sovereign cloud zones. India's Semiconductor Mission 2.0 allocated USD 10.8 billion the same year, aiming to reduce reliance on imported GPUs by 40% before 2030. China issued directives in 2025 mandating that government AI inference migrate to Ascend GPUs by 2027, guaranteeing thousands of annual domestic shipments. Such parallel architectures double infrastructure outlays because providers must maintain dedicated pools for sovereign and commercial tenants, diluting economies of scale.

Export Control Regulations Limiting Access to Latest GPUs

Washington's October 2023 rules block H200-class GPU sales to China, capping performance ceilings at H100 equivalents. Tariffs of 25% imposed in 2025 further inflate acquisition prices. ByteDance and Alibaba responded by booking 600,000 Huawei Ascend 910C units for 2025, yet each chip delivers only 60-70% of the H100 transformer's throughput, prompting over-provisioning. License processing delays of six to twelve months amplify planning uncertainty for universities and research labs.

Other drivers and restraints analyzed in the detailed report include:

1. Government Incentives for Domestic AI Semiconductor Manufacturing in the Asia-Pacific
2. Expansion of Edge Data Centers for 5G and IoT Traffic
3. High Capital Expenditure for GPU-Based Infrastructure

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

Segment Analysis

Cloud venues accounted for 63.45% of the Asia-Pacific data center GPU market share in 2025, reflecting hyperscalers' unmatched buying power and multitenancy economics. Edge sites, however, post a 17.88% CAGR through 2031, spurred by 5G densification that requires sub-10-millisecond response loops. The Asia-Pacific data center GPU market size tied to private enterprise data centers also expands, as banks and pharmaceutical firms internalize inference to meet data residency.

Centralized cloud clusters reach utilization above 85%, enabling price leadership, while edge rollouts monetize new latency-sensitive services such as AR wayfinding and smart-factory controls. Enterprises can keep on-prem clusters smaller while maintaining full policy control, an attractive option for confidential workloads and regions subject to stricter privacy laws.

Inference accelerators captured 58.77% of the Asia-Pacific data center GPU market share in 2025 and will grow at a 17.24% CAGR through 2031 as workloads migrate from model research to production. Training GPUs remain indispensable for frontier models, yet their share declines as every trained model fuels millions of inference calls.

NVIDIA's L4 and L40S, AMD's MI300X, and Huawei's Ascend 310 offer lower power draw and price points than H100 training silicon. The Asia-Pacific data center GPU market for inference continues to grow, thanks to INT8 and INT4 quantization, enabling older boards to remain competitive while driving down watts per token.

List of Companies Covered in this Report:

1. Nvidia Corporation
2. Advanced Micro Devices Inc.
3. Intel Corporation
4. Huawei Technologies Co. Ltd.
5. Tencent Cloud
6. Baidu Inc.
7. Amazon Web Services Inc.
8. Microsoft Corporation
9. Google LLC
10. Samsung Electronics Co. Ltd.
11. Inspur Group
12. Giga Computing Technology Co. Ltd.
13. Super Micro Computer Inc.
14. Lenovo Group Limited
15. NEC Corporation
16. H3C Technologies Co. Ltd.
17. Fujitsu Limited

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 Surge in AI Training Workloads in Hyperscale Cloud Data Centers
  • 4.2.2 Expansion of Edge Data Centers for 5G and IoT Traffic
  • 4.2.3 Government Incentives for Domestic AI Semiconductor Manufacturing in Asia-Pacific
  • 4.2.4 Adoption of Liquid Cooling Enabling Higher GPU Rack Density
  • 4.2.5 Rise of Sovereign AI Clouds Demanding In-Region GPU Clusters
  • 4.2.6 Corporate Sustainability Targets Driving GPU Consolidation for Energy Efficiency
• 4.3 Market Restraints
  • 4.3.1 Ongoing Supply Chain Constraints for Advanced GPU Packaging
  • 4.3.2 High Capital Expenditure for GPU-Based Infrastructure
  • 4.3.3 Export Control Regulations Limiting Access to Latest GPUs
  • 4.3.4 Skill Gap in Optimizing GPU Workloads Among Enterprise IT Teams
• 4.4 Industry Value Chain Analysis
• 4.5 Regulatory Landscape
• 4.6 Technological Outlook
• 4.7 Impact of Macroeconomic Factors on the Market
• 4.8 Porter's Five Forces Analysis
  • 4.8.1 Threat of New Entrants
  • 4.8.2 Bargaining Power of Suppliers
  • 4.8.3 Bargaining Power of Buyers
  • 4.8.4 Threat of Substitutes
  • 4.8.5 Industry Rivalry

5 MARKET SIZE AND GROWTH FORECASTS (VALUE)

• 5.1 By Deployment Type
  • 5.1.1 Cloud Data Centers
  • 5.1.2 Enterprise / Private Data Centers
  • 5.1.3 Edge Data Centers
• 5.2 By GPU Type
  • 5.2.1 Training GPUs
  • 5.2.2 Inference GPUs
• 5.3 By Interconnect
  • 5.3.1 PCIe-Based GPUs
  • 5.3.2 High-Bandwidth Interconnect GPUs
• 5.4 By Workload Type
  • 5.4.1 Artificial Intelligence (AI) and Machine Learning (ML)
  • 5.4.2 High-Performance Computing (HPC) (non-AI scientific computing)
  • 5.4.3 Data Analytics (database acceleration, query processing)
  • 5.4.4 Graphics and Visualization (VDI, rendering, digital twins)
• 5.5 By End-User
  • 5.5.1 Hyperscalers / Cloud Service Providers
  • 5.5.2 Enterprises
  • 5.5.3 Government and Research Institutions
• 5.6 By Country
  • 5.6.1 China
  • 5.6.2 Japan
  • 5.6.3 South Korea
  • 5.6.4 India
  • 5.6.5 Southeast Asia
  • 5.6.6 Rest of Asia-Pacific

6 COMPETITIVE LANDSCAPE

• 6.1 Market Concentration
• 6.2 Strategic Moves
• 6.3 Market Share 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 Nvidia Corporation
  • 6.4.2 Advanced Micro Devices Inc.
  • 6.4.3 Intel Corporation
  • 6.4.4 Huawei Technologies Co. Ltd.
  • 6.4.5 Tencent Cloud
  • 6.4.6 Baidu Inc.
  • 6.4.7 Amazon Web Services Inc.
  • 6.4.8 Microsoft Corporation
  • 6.4.9 Google LLC
  • 6.4.10 Samsung Electronics Co. Ltd.
  • 6.4.11 Inspur Group
  • 6.4.12 Giga Computing Technology Co. Ltd.
  • 6.4.13 Super Micro Computer Inc.
  • 6.4.14 Lenovo Group Limited
  • 6.4.15 NEC Corporation
  • 6.4.16 H3C Technologies Co. Ltd.
  • 6.4.17 Fujitsu Limited

7 MARKET OPPORTUNITIES AND FUTURE OUTLOOK

• 7.1 White-Space and Unmet-Need Assessment