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United States High-Bandwidth Memory (HBM) Market - Size, Share, Industry Trends, and Growth Forecasts (2026-2031) | AI Demand Fuels 27.98% CAGR to USD 4.91 Billion

globenewswire.com
NVDA NVIDIA's Vera Rubin platform entering production and its role in AI factories and next-gen computing systems, along with its supply chain scale, indicate strong demand and positive outlook for its AI-related products. MU Micron's entry into high-volume HBM4 production for NVIDIA's Vera Rubin and its planned investments in US facilities highlight its significant role and growth potential in the booming HBM market. AMD AMD's reported strong data center revenue indicates sustained demand for its HBM-equipped accelerator platforms, benefiting from the growth in AI and high-performance computing. TXN Texas Instruments is mentioned as an ecosystem player, but the article does not provide specific sentiment or performance details related to their involvement in the HBM market. QCOM Qualcomm is listed as an ecosystem player, but the article does not offer specific details on its current or future performance within the HBM market. INTC Intel is mentioned as an ecosystem player, but the article does not provide specific sentiment or performance details related to their involvement in the HBM market. AMAT Applied Materials is listed as an ecosystem player, but the article does not provide specific sentiment or performance details regarding its role in the HBM market. SNPS Synopsys is mentioned as an ecosystem player, but the article does not provide specific sentiment or performance details related to their involvement in the HBM market. CDNS Cadence Design Systems is listed as an ecosystem player, but the article does not offer specific sentiment or performance details regarding its role in the HBM market. RMBS Rambus is mentioned as an ecosystem player, but the article does not provide specific sentiment or performance details related to their involvement in the HBM market. MRVL Marvell Technology is mentioned as an ecosystem player, but the article does not provide specific sentiment or performance details related to their involvement in the HBM market.

United States High-Bandwidth Memory (HBM) Market - Size, Share, Industry Trends, and Growth Forecasts (2026-2031) | AI Demand Fuels 27.98% CAGR to USD 4.91 Billion Dublin, Oct. 06, 2026 (GLOBE NEWSWIRE) -- "United States HBM - Market Share Analysis, Industry Trends & Statistics, Growth Forecasts (2026-2031)" has been added to ResearchAndMarkets.com's offering.

The United States HBM market was valued at USD 1.09 billion in 2025 and is expected to grow from USD 1.43 billion in 2026 to USD 4.91 billion by 2031. This represents a CAGR of 27.98% during the 2026-2031 forecast period. Growth is being driven by rising memory requirements for AI training, inference, high-performance computing, advanced graphics, and hyperscale data center infrastructure.

AI Training and Inference Increase HBM Demand

High-bandwidth memory demand per accelerator is increasing faster than accelerator shipments because each new computing platform requires more stacks, greater capacity, and higher bandwidth. NVIDIA's Vera Rubin platform entered full production in May 2026, reinforcing the importance of memory performance in the development of agentic AI factories and next-generation computing systems.

Memory suppliers are scaling production to support these requirements. Samsung's commercial HBM4 achieved transfer speeds of 11.7 Gbps and bandwidth of up to 3.3 TB/s per stack. Micron also entered high-volume HBM4 production for Vera Rubin. Meanwhile, AMD reported USD 16.6 billion in data center revenue for 2025, indicating sustained demand for HBM-equipped accelerator platforms.

AI training clusters remain major consumers of memory, while inference infrastructure is creating a more consistent source of demand as user traffic and AI services expand. As a result, the United States HBM market is benefiting from both new data center installations and recurring platform refresh cycles.

Hyperscale Data Center Expansion Supports Market Growth

Large-scale AI data center construction across the United States continues to pull HBM supply forward. Accelerator deployment schedules increasingly depend on the availability of qualified memory and advanced packaging capacity. NVIDIA reported that Vera Rubin entered production with seven new chips supported by more than 350 supply chain partners across 30 countries, demonstrating the scale of the ecosystem preparing for deployment.

Samsung began mass production of commercial HBM4 in February 2026, followed by Micron's move into high-volume HBM4 production in March 2026. These developments align with expanding customer programs and the transition from pilot AI clusters to production environments. Broader accelerator adoption is also diversifying HBM demand beyond a single platform or purchasing cycle, creating a more durable growth outlook.

Advanced Packaging Capacity Remains a Key Constraint

Advanced packaging capacity continues to limit near-term market expansion. Frontier AI accelerators depend on a relatively narrow group of qualified integration processes, creating potential scheduling pressure when packaging availability does not align with product launches.

Domestic investments are expected to strengthen the United States semiconductor supply chain, but much of the capacity remains under development. SK hynix's Indiana facility is expected to begin mass production in the second half of 2028. Micron's planned investments in Idaho, New York, and Virginia also represent multi-year expansion programs rather than immediate additions to available capacity.

Each new HBM generation requires packaging validation, manufacturing process optimization, and improved yields in addition to greater wafer output. High yield-loss risk in multi-die, high-stack HBM manufacturing may therefore continue to affect production schedules. CHIPS Act support, reshoring incentives, chiplet architectures, and additional domestic investment are expected to improve long-term supply resilience.

HBM3E Leads While HBM4E Gains Momentum

HBM3E accounted for 71.32% of the United States HBM market in 2025, supported by large procurement programs for Blackwell-based systems. Its bandwidth and capacity made it the primary memory choice for high-volume AI accelerator deployments. HBM2E and HBM3 retained demand in legacy high-performance computing and professional visualization systems with longer qualification cycles.

HBM4E and later-generation HBM products are projected to record a CAGR of 28.94% through 2031. Customers are prioritizing higher throughput, greater stack capacity, and improved power efficiency within constrained package footprints. Samsung reported that its commercial HBM4 provides up to 3.3 TB/s of bandwidth and 40% better power efficiency than HBM3E. The company also began shipping HBM4E samples in May 2026, offering bandwidth of up to 3.6 TB/s and capacity of 48 GB.

SK hynix completed HBM4 development in September 2025, while Micron's high-volume HBM4 production confirms that the next market cycle has moved into commercial execution. Future growth will depend heavily on how quickly suppliers can scale qualified HBM4 and HBM4E products across major accelerator programs.

Advanced Technology Nodes Strengthen Market Performance

Advanced nodes below 1Z represented 49.94% of the United States HBM market in 2025 and are forecast to grow at a CAGR of 28.69% through 2031. These nodes support the transition to HBM4 and HBM4E by improving bandwidth, power efficiency, and package integration.

SK hynix uses its 1b nm process and Advanced MR-MUF technology for HBM4, while Samsung combines a 4 nm logic base die with a 1c DRAM process. Micron's commercial HBM4 production further demonstrates that below 1Z technology has become central to current supply. Although 1X, 1Y, and 1Z nodes remain relevant for defense, research, and other long-lifecycle systems, market growth is increasingly concentrated in advanced processes designed for AI accelerators and high-bandwidth computing platforms.

Key Topics Covered

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 Accelerating AI Training and Inference Memory Intensity

4.2.2 Hyperscale GPU Cluster Expansion in United States Data Centers

4.2.3 HBM Adoption in Advanced Packaging and Chiplet Architectures

4.2.4 Domestic Memory Supply Chain Reshoring Incentives and CHIPS Act Support

4.2.5 HBM Demand Pull From Sovereign AI, Defense, and Secure Compute Programs

4.2.6 HBM Qualification for Next-Generation Accelerators and Custom Silicon

4.3 Market Restraints

4.3.1 Advanced Packaging Capacity Constraints Across CoWoS and Similar Flows

4.3.2 High Yield Loss Risk in Multi-Die, High-Stack HBM Manufacturing

4.3.3 Thermal Management Limits in High Power Density AI Systems

4.3.4 Heavy Concentration of Qualified Supply and Long Qualification Cycles

4.4 Supply Chain Analysis

4.5 Regulatory Landscape

4.6 Technological Outlook

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 Intensity of Competitive Rivalry

5 MARKET SIZE AND GROWTH FORECASTS (VALUE)

5.1 By HBM Type

5.1.1 HBM2E and Earlier Generations

5.1.2 HBM3

5.1.3 HBM3E

5.1.4 HBM4

5.1.5 HBM4E and Later-Generation HBM

5.2 By Technology Node

5.2.1 1X And Above Legacy Nodes

5.2.2 1Y Node

5.2.3 1Z Node

5.2.4 Advanced Nodes Below 1Z

5.3 By Packaging Type

5.3.1 2.5D Interposer-Based Packaging

5.3.2 3D Stacking

5.3.3 Fan-Out Advanced Packaging

5.4 By End Use Industry

5.4.1 Cloud Service Providers and Hyperscalers

5.4.2 Internet Platforms and AI Model Developers

5.4.3 Government, Defense, Research, and Academic Institutions

5.4.4 Enterprise Data Centers

5.4.5 Telecommunications Operators and Network Equipment Providers

5.4.6 Other Enterprise Verticals

5.5 By Application

5.5.1 AI Model Training

5.5.2 AI Model Inference

5.5.3 HPC and Scientific Computing

5.5.4 Professional Graphics, Rendering, and Visualization

5.5.5 Network and Telecom Processing

5.5.6 Other High-Bandwidth Compute Workloads

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, Products and Services, Recent Developments)

6.4.1 SK Hynix Inc.

6.4.2 Samsung Electronics Co., Ltd.

6.4.3 Micron Technology, Inc.

6.5 Other Ecosystem Players

6.5.1 NVIDIA Corporation

6.5.2 Advanced Micro Devices, Inc.

6.5.3 Intel Corporation

6.5.4 Broadcom Inc.

6.5.5 Marvell Technology, Inc.

6.5.6 Taiwan Semiconductor Manufacturing Company Limited

6.5.7 Amkor Technology, Inc.

6.5.8 ASE Technology Holding Co., Ltd.

6.5.9 Powertech Technology Inc.

6.5.10 Siliconware Precision Industries Co., Ltd.

6.5.11 GlobalFoundries Inc.

6.5.12 Applied Materials, Inc.

6.5.13 Cadence Design Systems, Inc.

6.5.14 Synopsys, Inc.

6.5.15 Rambus Inc.

6.5.16 Qualcomm Incorporated

6.5.17 Texas Instruments Incorporated

7 MARKET OPPORTUNITIES AND FUTURE OUTLOOK

7.1 White-Space and Unmet-Need Assessment

For more information about this report visit https://www.researchandmarkets.com/r/d1wsp3

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