GPU 메모리 : 시장 점유율 분석, 업계 동향과 통계, 성장 예측(2026-2031년)

According to Mordor Intelligence, the GPU memory market size is expected to increase from USD 10.18 billion in 2025 to USD 12.40 billion in 2026 and reach USD 32.15 billion by 2031, growing at a CAGR of 20.90% over 2026-2031.

This report is Segmented by Memory Type (HBM, GDDR, and More), Memory Capacity (Up To 8 GB, 8 GB To 16 GB, 16 GB To 32 GB, 32 GB To 64 GB, and Above 64 GB), Application (Professional Visualization and Content Creation, Edge AI and Embedded Acceleration, High-Performance Computing, Cloud GPU and Data Center Acceleration, and More), and Geography. The Market Forecasts are Provided in Terms of Value (USD).

Global GPU Memory Market Trends and Insights

AI Training Cluster Expansion Increasing HBM Consumption

AI infrastructure buildouts have turned HBM from a premium memory option into one of the main supply gates for the GPU memory market. NVIDIA specified 192 GB of HBM3E for each Blackwell B200 GPU, and the GB300 Blackwell Ultra raises that requirement to 288 GB per GPU, which sharply lifts memory content per accelerator generation. NVIDIA also stated that a single GB200 NVL72 rack carries more than 13.4 TB of HBM3E, which shows why procurement has shifted from chip-level decisions to rack-level commitments. This change means the GPU memory market grows not only because more accelerators are shipped, but also because each deployment now absorbs far more memory than earlier system designs. The near-term effect is tighter supply utilization, since additional wafer starts alone do not solve limits in stacking, packaging, and qualification across the GPU memory market.

NVIDIA Blackwell and Successor Platform Rollouts Increasing Qualification Demand

Platform transitions are now one of the strongest timing factors in the GPU memory market because memory suppliers need to qualify each new generation before large customer volumes begin. Bloomberg reported in June 2026 that Samsung, SK hynix, and Micron all cleared HBM4 certification for NVIDIA Vera Rubin, making qualification the gateway to the next supply cycle. SK hynix then deepened that position with a multi-year technology partnership with NVIDIA covering HBM4, Vera Rubin systems, RTX Spark-powered PCs, and Jetson Thor robotics platforms. These platform rollouts force suppliers to support overlapping roadmaps for HBM3E, HBM4, and next-generation derivatives at the same time, which raises development pressure across the GPU memory market. The practical result is that early certification often matters as much as manufacturing scale, because qualified volume is what customers can deploy without delay.

Qualified Supplier Concentration Limiting Volume Flexibility

Supplier concentration remains one of the clearest constraints on the GPU memory market because only a very small group of manufacturers can deliver qualified HBM at scale. Bloomberg confirmed in 2026 that Samsung, SK hynix, and Micron were the three memory makers certified for NVIDIA's HBM4 cycle, which underlines how limited the qualified supplier base remains. Seoul Economic Daily reported that global large technology companies even proposed direct funding for SK hynix production lines and equipment, which shows how difficult it is to secure incremental supply through normal purchasing channels. This concentration reduces volume flexibility across the GPU memory market because new customers cannot quickly diversify to alternative sources when demand rises faster than planned capacity. It also means procurement timing is increasingly set by allocation agreements and qualification access, not only by end demand or GPU wafer availability.

Other drivers and restraints analyzed in the detailed report include:

1. Cloud Gaming and AI Workstation Upgrades Increasing GDDR7 Adoption
2. Advanced Packaging Capacity Buildout Unlocking New GPU Memory Supply
3. Yield Sensitivity In 3D Stacking and TSV Processing

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

Segment Analysis

HBM held 42.11% of the GPU memory market share in 2025, making it the largest memory type, and this part of the GPU memory market size is projected to rise at a 21.52% CAGR through 2031. HBM keeps that lead because large AI training and inference systems now depend on high bandwidth, dense packaging, and rising memory-per-GPU specifications across each platform cycle. NVIDIA's current data center roadmap already shows how fast requirements are increasing, with Blackwell and successor systems moving to much higher HBM loads per accelerator and per rack. Bloomberg also confirmed that Samsung, SK hynix, and Micron all qualified for NVIDIA's HBM4 cycle in 2026, which supports the next phase of HBM revenue expansion.

The growth profile of HBM is also reinforced by active supplier roadmaps in 2026, with Samsung and SK hynix moving 12-layer HBM4E and related next-generation products toward customer deployment. SK hynix stated that its June 2026 HBM4E sample shipments reached 48 GB per stack, which supports the move toward much larger memory footprints in future AI accelerators. GDDR remains the main complement to HBM in the GPU memory market because it supports lower-cost inference, gaming, visualization, and workstation deployments where system economics matter more than maximum bandwidth. Rambus and NVIDIA both showed that GDDR7 is now moving into mainstream product lines, which gives the market a broad second growth base outside HBM-heavy server clusters. Other memory types still matter, but their role remains more selective and is tied to architectures that trade peak bandwidth for lower cost or higher capacity per dollar.

Complete Report Scope:

• By Memory Type
  • HBM
  • GDDR
  • Other GPU Memory Types
• By Memory Capacity
  • Up to 8 GB
  • 8 GB to 16 GB
  • 16 GB to 32 GB
  • 32 GB to 64 GB
  • Above 64 GB
• By Application
  • Professional Visualization and Content Creation
  • AI Training and Inference
  • High-Performance Computing
  • Cloud GPU and Data Center Acceleration
  • Gaming and Consumer Graphics
  • Edge AI and Embedded Acceleration
• 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

Asia-Pacific accounted for 48.34% of the GPU memory market share in 2025, which made it the largest regional base for both supply and revenue. The region holds that position because South Korea anchors HBM manufacturing through Samsung and SK hynix, while Taiwan remains central to advanced packaging that is required for HBM deployment in AI accelerators. Korea JoongAng Daily reported that Samsung and SK hynix are scaling HBM-related production, which reinforces Asia-Pacific's role as the core production center for the GPU memory market. Japan adds depth through semiconductor equipment, testing systems, and memory research support, which strengthens the regional ecosystem around manufacturing continuity. India and Southeast Asia are also becoming more relevant to the GPU memory market as cloud operators expand data center footprints in Singapore, Malaysia, and Indonesia.

North America remains the main demand center in the GPU memory market because the largest AI infrastructure programs are still concentrated among U.S. cloud and platform companies. Mordor Intelligence stated that large-scale training and data center GPU deployments in North America continue to shape hardware procurement patterns, which directly supports memory demand across HBM and GDDR categories. The region also benefits from supply-chain diversification efforts, since U.S.-linked memory capacity is increasingly valued by customers that want a broader geographic sourcing base. This keeps North America important to the GPU memory market even though the heaviest manufacturing concentration remains in Asia-Pacific.

Europe is becoming a more meaningful consumption geography for the GPU memory market as hyperscalers and enterprises add AI-ready capacity under stricter governance and compliance needs. AWS committed EUR 33.7 billion (USD 35.7 billion), to expand GPU capacity in Spain through 2033, and Google announced EUR 5.5 billion (USD 5.83 billion), for GPU and TPU buildout in Hanau and Frankfurt in December 2025. The EU AI Act is also supporting demand for private cloud and on-premise AI infrastructure, which lifts enterprise hardware demand that depends on advanced memory content. South America and Middle East and Africa remain smaller in current scale, but the GPU memory market has room to deepen there as sovereign AI projects and digital infrastructure programs advance through the forecast period.

1. Samsung Electronics Co., Ltd.
2. SK hynix Inc.
3. Micron Technology, Inc.
4. NVIDIA Corporation
5. Advanced Micro Devices, Inc.
6. Intel Corporation
7. Broadcom Inc.
8. Marvell Technology, Inc.
9. Taiwan Semiconductor Manufacturing Company Limited
10. Amkor Technology, Inc.
11. ASE Technology Holding Co., Ltd.
12. Powertech Technology Inc.
13. United Microelectronics Corporation
14. Cadence Design Systems, Inc.
15. Synopsys, Inc.
16. Rambus Inc.
17. Applied Materials, Inc.
18. GlobalFoundries Inc.
19. Chipbond Technology Corporation
20. JCET Group Co., Ltd.
21. Siliconware Precision Industries Co., Ltd.

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 Impact of Macroeconomic Factors on the Market
• 4.3 Market Drivers
  • 4.3.1 AI Training Cluster Expansion Increasing HBM Consumption
  • 4.3.2 NVIDIA Blackwell and Successor Platform Rollouts Increasing Qualification Demand
  • 4.3.3 Cloud Gaming and AI Workstation Upgrades Increasing GDDR7 Adoption
  • 4.3.4 Advanced Packaging Capacity Buildout Unlocking New GPU Memory Supply
  • 4.3.5 OEM Preference for Higher Bandwidth Per Watt in Data Center GPUs
  • 4.3.6 Rising Demand for High-Capacity Modules in Inference Accelerators
• 4.4 Market Restraints
  • 4.4.1 Qualified Supplier Concentration Limiting Volume Flexibility
  • 4.4.2 Yield Sensitivity in 3D Stacking and TSV Processing
  • 4.4.3 Allocation Tension Between HBM and GDDR Wafer Starts
  • 4.4.4 Thermal and Power-Delivery Limits in Compact GPU Platforms
• 4.5 Industry Value Chain Analysis
• 4.6 Regulatory Landscape
• 4.7 Technological Outlook
• 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 Competitive Rivalry

5 MARKET SIZE AND GROWTH FORECASTS

• 5.1 By Memory Type
  • 5.1.1 HBM
  • 5.1.2 GDDR
  • 5.1.3 Other GPU Memory Types
• 5.2 By Memory Capacity
  • 5.2.1 Up to 8 GB
  • 5.2.2 8 GB to 16 GB
  • 5.2.3 16 GB to 32 GB
  • 5.2.4 32 GB to 64 GB
  • 5.2.5 Above 64 GB
• 5.3 By Application
  • 5.3.1 Professional Visualization and Content Creation
  • 5.3.2 AI Training and Inference
  • 5.3.3 High-Performance Computing
  • 5.3.4 Cloud GPU and Data Center Acceleration
  • 5.3.5 Gaming and Consumer Graphics
  • 5.3.6 Edge AI and Embedded Acceleration
• 5.4 By Geography
  • 5.4.1 North America
    • 5.4.1.1 United States
    • 5.4.1.2 Canada
    • 5.4.1.3 Mexico
  • 5.4.2 Europe
    • 5.4.2.1 Germany
    • 5.4.2.2 United Kingdom
    • 5.4.2.3 France
    • 5.4.2.4 Italy
    • 5.4.2.5 Rest of Europe
  • 5.4.3 Asia Pacific
    • 5.4.3.1 China
    • 5.4.3.2 Japan
    • 5.4.3.3 South Korea
    • 5.4.3.4 India
    • 5.4.3.5 Southeast Asia
    • 5.4.3.6 Rest of Asia-Pacific
  • 5.4.4 South America
  • 5.4.5 Middle East and Africa

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 Samsung Electronics Co., Ltd.
  • 6.4.2 SK hynix Inc.
  • 6.4.3 Micron Technology, Inc.
  • 6.4.4 NVIDIA Corporation
  • 6.4.5 Advanced Micro Devices, Inc.
  • 6.4.6 Intel Corporation
  • 6.4.7 Broadcom Inc.
  • 6.4.8 Marvell Technology, Inc.
  • 6.4.9 Taiwan Semiconductor Manufacturing Company Limited
  • 6.4.10 Amkor Technology, Inc.
  • 6.4.11 ASE Technology Holding Co., Ltd.
  • 6.4.12 Powertech Technology Inc.
  • 6.4.13 United Microelectronics Corporation
  • 6.4.14 Cadence Design Systems, Inc.
  • 6.4.15 Synopsys, Inc.
  • 6.4.16 Rambus Inc.
  • 6.4.17 Applied Materials, Inc.
  • 6.4.18 GlobalFoundries Inc.
  • 6.4.19 Chipbond Technology Corporation
  • 6.4.20 JCET Group Co., Ltd.
  • 6.4.21 Siliconware Precision Industries Co., Ltd.

7 MARKET OPPORTUNITIES AND FUTURE OUTLOOK

• 7.1 White-Space and Unmet-Need Assessment