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

According to Mordor Intelligence, the next-generation HBM market size was valued at USD 0.15 billion in 2025 and is projected to reach USD 6.33 billion by 2031, at a CAGR of 86.57% during 2026-2031.

This report is Segmented by Technology (HBM2, HBM2E, HBM3, HBM3E, and HBM4), Memory Capacity Per Stack (4 GB, 8 GB, 16 GB, 24 GB, and 32 GB and Above), Processor Interface (GPU, CPU, AI Accelerator and ASIC, FPGA, and More), Application (AI and Data Center Servers, and More), End Use Industry (Cloud Service Providers, and More), and Geography. The Market Forecasts are Provided in Terms of Value (USD).

Global Next-Generation HBM Market Trends and Insights

AI Server Proliferation and GPU Attach Rates

Every major AI platform now carries a larger HBM load per processor than the previous one, indicating the next-generation HBM market is growing faster than accelerator unit demand alone. NVIDIA disclosed that Vera Rubin NVL72 uses 20.7 TB of HBM4 and 1,580 TB/s of memory bandwidth across 72 GPUs, demonstrating how quickly system-level memory intensity is rising. SK Hynix also reported that its HBM business more than doubled year over year in FY2025, confirming that AI server deployments are already translating into significant expansion in very large memory revenue. The next-generation HBM market is therefore being pulled forward by both new server installations and richer memory configurations within each installed rack. That pattern is reinforced by the move toward rack-scale AI systems, where the economic value of the platform depends on sustained memory throughput rather than raw compute density alone. As a result, suppliers that can ramp qualified volume quickly are in a stronger position than those that simply have product availability on paper.

HBM4 Adoption In Next-Generation AI Accelerators

HBM4 is driving the next-generation HBM market by combining a significant increase in bandwidth with architectural changes that enable tighter optimization for upcoming AI platforms. Micron stated that its HBM4 36 GB 12-high product delivered more than 2.8 TB/s of bandwidth and over 20% better power efficiency than HBM3E, while entering high-volume production in early 2026. Samsung also began mass production shipments of HBM4 in February 2026 and later said cumulative HBM4 sales reached USD 1 billion within 130 days, pointing to an unusually fast commercial ramp for a new memory generation. The move to HBM4 also raises technical demands, as the I/O count per die doubles compared with earlier generations, making stack yield, base-die integration, and package-level validation more difficult. In practice, that complexity limits broad participation and keeps the next-generation HBM market centered on suppliers that can pair DRAM process strength with packaging discipline. It also raises the value of custom HBM programs, which are becoming a direct differentiator in top-tier AI accelerator launches.

Limited CoWoS and SoIC Advanced-Packaging Capacity

The largest near-term restraint on the next-generation HBM market remains the availability of advanced packaging, as qualified memory stacks still need scarce integration slots before they can ship in accelerator products. TSMC has indicated that more advanced packaging transitions, such as CoPoS, have been delayed by engineering challenges tied to glass interposer uniformity and warpage control, which keeps pressure on current packaging flows for longer. This means even well-yielding HBM output can be held back by a second bottleneck at the integration stage, especially for high-stack products that already require tighter process control. The restraint is more severe when customers need the newest configurations, because HBM4 and HBM4E products place additional demands on thermal handling, bump integrity, and package validation. Suppliers are responding with higher backend investment, but the next-generation HBM market still faces a lag between announced packaging capacity and dependable, qualified throughput. That lag keeps allocation tight, supports premium pricing, and limits how quickly supply can match the demand profile of leading AI platforms.

Other drivers and restraints analyzed in the detailed report include:

1. Advanced Packaging Capacity Expansion
2. Sovereign AI and Local Memory Localization Incentives
3. Export Controls on Advanced AI Accelerators And HBM-Linked Supply Chains

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

Segment Analysis

HBM3E held 51.84% of the technology segment in 2025, while HBM4 is projected to expand at 87.58% CAGR through 2031. HBM3E remains important in the next-generation HBM market because it already supports meaningful deployment across current AI infrastructure and gives customers a qualified bridge while HBM4 volume ramps. NVIDIA's current and near-term platform cadence has helped keep HBM3E relevant, since hyperscalers continue to deploy existing accelerator systems even as they prepare for the next memory generation. HBM4, however, is changing the pace of this category by offering much higher bandwidth, greater flexibility for customized designs, and stronger alignment with upcoming rack-scale AI systems. Micron said its HBM4 36 GB 12-high product exceeded 2.8 TB/s and improved power efficiency by more than 20% compared with HBM3E, which explains why customers are moving quickly to qualify the new node.

The next-generation HBM market also shows that technology leadership is no longer defined only by DRAM density or speed, because base-die design and foundry coordination now matter much more than they did in earlier memory cycles. Samsung stated that its HBM4 uses a 4-nm base die and later shipped HBM4E 12-high samples with up to 16 Gbps per pin and 3.6 TB/s bandwidth, showing how quickly the technology ladder is tightening. SK Hynix followed with HBM4E samples in June 2026 and highlighted custom HBM as a strategic priority, which signals that the next-generation HBM market is moving toward customer-specific optimization rather than simple standard part competition. Older generations such as HBM2, HBM2E, and HBM3 still have room in networking and legacy HPC uses, where cost and qualification history can matter more than absolute bandwidth. Even so, the transition path makes entry harder for new participants, because suppliers now need credible strength in memory process technology, advanced packaging, and base-die coordination at the same time.

The 24 GB tier led with 47.12% share in 2025, while 32 GB and above is projected to grow at 87.51% CAGR through 2031. The 24 GB tier sits at the center of the installed base in the next-generation HBM market because it matches the configuration used in many current AI systems and gives customers a known balance between performance, yield, and deployable volume. That installed base will not disappear quickly, as existing server fleets and procurement cycles continue to support strong demand for qualified HBM3E stacks in this capacity range. The growth center has already moved higher, however, because newer AI systems need more memory per accelerator and more bandwidth per training cluster than earlier platforms required. Micron said it shipped HBM4 48 GB 16-high samples to multiple customers in Q1 2026, indicating how quickly the product roadmap is moving beyond the current mainstream tier.

This shift matters because the next-generation HBM market for higher-capacity stacks is growing with each platform generation, and the new floor for AI-relevant memory content is steadily rising. As stack height increases, the technical burden also rises because die thinning, alignment, and thermal control become more sensitive, which can reduce effective finished-unit output even when wafer availability appears healthy. IEEE and related packaging analysis in the source draft highlighted that through-silicon-via complexity and high-stack assembly losses become more serious as more layers are added to a single package. Smaller tiers such as 4 GB, 8 GB, and 16 GB remain relevant in networking devices, edge inference hardware, and legacy compute nodes where bandwidth per dollar still shapes purchasing decisions. Still, the long-term direction of the next-generation HBM market is clear, because premium capacity tiers are becoming commercial volume products rather than isolated high-end options.

Complete Report Scope:

• By Technology
  • HBM2
  • HBM2E
  • HBM3
  • HBM3E
  • HBM4
• By Memory Capacity per Stack
  • 4 GB
  • 8 GB
  • 16 GB
  • 24 GB
  • 32 GB and Above
• By Processor Interface
  • GPU
  • CPU
  • AI Accelerator and ASIC
  • FPGA
  • Other Processor Interfaces
• By Application
  • AI and Data Center Servers
  • Networking
  • High-Performance Computing
  • Consumer Electronics
  • Automotive and Transportation
  • Other Applications
• By End Use Industry
  • Cloud Service Providers
  • Enterprise Data Centers
  • Telecommunications Operators
  • Automotive OEMs
  • Other End Use Industries
• By Geography
  • North America
    • United States
    • Canada
    • Mexico
  • Europe
    • Germany
    • United Kingdom
    • France
    • Italy
    • Rest of Europe
  • Asia-Pacific
    • China
    • Japan
    • South Korea
    • Taiwan
    • India
    • Rest of Asia-Pacific
  • South America
  • Middle East and Africa

Geography Analysis

Asia-Pacific held 71.04% of the next-generation HBM market share in 2025. The region leads because South Korea concentrates commercial HBM production at SK Hynix and Samsung Electronics, while Taiwan remains central to advanced packaging and integration. SK Hynix reported FY2025 revenue of KRW 97,146.7 billion (USD 70.2 billion), using the IRS 2025 yearly average exchange rate provided in the source draft, and said HBM revenue more than doubled year over year. South Korea strengthened that position in June 2026 with a national investment plan that included four new memory fabs, an HBM packaging hub, and major funding for AI data centers. The South Korean AI Framework Act, effective January 22, 2026, added a policy layer to support domestic AI infrastructure and reinforce the country's appeal as a destination for long-term memory investment.

North America is projected to grow at 87.38% CAGR through 2031, making it the fastest-expanding regional block in the next-generation HBM market. Demand is concentrated in the United States because the largest hyperscaler and accelerator buyers are based there, and that keeps procurement power close to the leading AI platform owners. Micron, the only U.S.-based HBM producer, secured CHIPS Act grants of up to USD 6.4 billion for DRAM fab construction in Idaho and New York, while also advancing domestic HBM-related capability. SK Hynix is also building advanced packaging facilities in Indiana, which deepens North American participation beyond demand concentration alone. Europe remains a secondary demand region, led by automotive compute needs in Germany and by broader hardware policy interest in markets such as the United Kingdom.

South America and the Middle East and Africa are still early-stage regions in the next-generation HBM market, but both are gaining relevance through AI infrastructure build-outs rather than through local memory production. South America is driven mainly by cloud and enterprise data center expansion, which increases imported accelerator demand as regional AI workloads grow. The Middle East and Africa are being supported by sovereign AI and large data center ambitions, especially where governments are backing compute capacity at scale. Neither region is likely to establish indigenous HBM production during 2026-2031, so their demand outlook remains closely tied to global supply allocation, export compliance, and price discipline among the established producers.

1. SK Hynix Inc.
2. Samsung Electronics Co., Ltd.
3. Micron Technology, Inc.
4. NVIDIA Corporation
5. Taiwan Semiconductor Manufacturing Company Limited
6. Advanced Micro Devices, Inc.
7. Intel Corporation
8. Broadcom Inc.
9. Marvell Technology, Inc.
10. Applied Materials, Inc.
11. ASML Holding N.V.
12. TSMC
13. Amkor Technology, Inc.
14. ASE Technology Holding Co., Ltd.
15. Powertech Technology Inc.
16. United Microelectronics Corporation
17. Cadence Design Systems, Inc.
18. Synopsys, Inc.
19. Rambus Inc.
20. JCET Group 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 Market Drivers
  • 4.2.1 AI Server Proliferation and GPU Attach Rates
  • 4.2.2 HBM4 Adoption in Next-Generation AI Accelerators
  • 4.2.3 Advanced Packaging Capacity Expansion
  • 4.2.4 Sovereign AI and Local Memory Localization Incentives
  • 4.2.5 Edge AI Inference in Automotive ADAS
  • 4.2.6 Photonics-Ready HBM Roadmaps
• 4.3 Market Restraints
  • 4.3.1 Limited CoWoS and SoIC Advanced-Packaging Capacity
  • 4.3.2 TSV Yield Losses in High-Stack Designs
  • 4.3.3 Export Controls on Advanced AI Accelerators and HBM-Linked Supply Chains
  • 4.3.4 Thermal Density Limits in Ultra-High-Bandwidth Devices
• 4.4 Industry Value Chain Analysis
• 4.5 Impact of Macroeconomic Factors on the Market
• 4.6 Regulatory Landscape
• 4.7 Technological Outlook
• 4.8 Porter's Five Forces Analysis
  • 4.8.1 Bargaining Power of Buyers
  • 4.8.2 Bargaining Power of Suppliers
  • 4.8.3 Threat of New Entrants
  • 4.8.4 Threat of Substitutes
  • 4.8.5 Intensity of Competitive Rivalry

5 MARKET SIZE AND GROWTH FORECASTS (VALUE)

• 5.1 By Technology
  • 5.1.1 HBM2
  • 5.1.2 HBM2E
  • 5.1.3 HBM3
  • 5.1.4 HBM3E
  • 5.1.5 HBM4
• 5.2 By Memory Capacity per Stack
  • 5.2.1 4 GB
  • 5.2.2 8 GB
  • 5.2.3 16 GB
  • 5.2.4 24 GB
  • 5.2.5 32 GB and Above
• 5.3 By Processor Interface
  • 5.3.1 GPU
  • 5.3.2 CPU
  • 5.3.3 AI Accelerator and ASIC
  • 5.3.4 FPGA
  • 5.3.5 Other Processor Interfaces
• 5.4 By Application
  • 5.4.1 AI and Data Center Servers
  • 5.4.2 Networking
  • 5.4.3 High-Performance Computing
  • 5.4.4 Consumer Electronics
  • 5.4.5 Automotive and Transportation
  • 5.4.6 Other Applications
• 5.5 By End Use Industry
  • 5.5.1 Cloud Service Providers
  • 5.5.2 Enterprise Data Centers
  • 5.5.3 Telecommunications Operators
  • 5.5.4 Automotive OEMs
  • 5.5.5 Other End Use 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 Taiwan
    • 5.6.3.5 India
    • 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 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 SK Hynix Inc.
  • 6.4.2 Samsung Electronics Co., Ltd.
  • 6.4.3 Micron Technology, Inc.
  • 6.4.4 NVIDIA Corporation
  • 6.4.5 Taiwan Semiconductor Manufacturing Company Limited
  • 6.4.6 Advanced Micro Devices, Inc.
  • 6.4.7 Intel Corporation
  • 6.4.8 Broadcom Inc.
  • 6.4.9 Marvell Technology, Inc.
  • 6.4.10 Applied Materials, Inc.
  • 6.4.11 ASML Holding N.V.
  • 6.4.12 TSMC
  • 6.4.13 Amkor Technology, Inc.
  • 6.4.14 ASE Technology Holding Co., Ltd.
  • 6.4.15 Powertech Technology Inc.
  • 6.4.16 United Microelectronics Corporation
  • 6.4.17 Cadence Design Systems, Inc.
  • 6.4.18 Synopsys, Inc.
  • 6.4.19 Rambus Inc.
  • 6.4.20 JCET Group Co., Ltd.

7 MARKET OPPORTUNITIES AND FUTURE OUTLOOK

• 7.1 White-Space and Unmet-Need Assessment