HBM Supply Crunch Deepens: DRAM Wafer Production and Advanced Packaging/Test Emerge as Dual Bottlenecks Amid Samsung, SK Hynix, Micron Rivalry

July 19, 2026

Industry Analysis International

Overview

High Bandwidth Memory (HBM), central to AI, faces dual bottlenecks in both DRAM wafer manufacturing and advanced packaging/test capacity. HBM achieves high bandwidth and energy efficiency through 3D stacking, TSVs, microbumps, and advanced packaging, but the complexity of these processes constrains supply. Samsung is actively developing HBM4, projecting significant sales growth in 2026, and focusing on customer qualification and yield recovery amidst fierce competition with SK Hynix and Micron.

In Depth

Key Findings

High Bandwidth Memory (HBM), a core component in Artificial Intelligence (AI) technology, is facing severe supply bottlenecks not only in DRAM wafer production but also in subsequent advanced packaging and testing capabilities. This dual constraint is the primary factor preventing the industry from meeting the surging HBM demand in the AI era.

Technical and Clinical Details

HBM employs 3D stacking technology, where multiple DRAM dies are vertically stacked and interconnected through Through-Silicon Vias (TSVs). This architecture enables significantly wider data bus widths and shorter signal paths, delivering dramatically higher bandwidth and superior energy efficiency compared to conventional DRAM solutions. The process necessitates wafer thinning, TSV formation, microbump bonding, and advanced packaging techniques like CoWoS (Chip-on-Wafer-on-Substrate). Each of these steps is highly complex and demands extreme precision, making yield assurance challenging and production costs high. Samsung is actively developing HBM4, the next generation of HBM, and anticipates a substantial increase in HBM-related sales in 2026. The company is focused on accelerating customer qualification and improving yield recovery, engaging in fierce competition with key rivals like SK Hynix and Micron for leadership in the AI memory market.

Background and Industry Context

The increasing scale of AI models and the explosive growth in data processing volumes demand unprecedented bandwidth and capacity from the memory integrated into AI chips, requirements that conventional Double Data Rate (DDR) memory cannot satisfy. HBM was developed to meet these demands and is widely adopted in NVIDIA’s GPUs and AMD’s AI accelerators. However, HBM manufacturing processes are far more complex than traditional memory production. Specifically, advanced packaging steps such as TSV formation and microbump bonding require specialized expertise, dedicated equipment, and long lead times. Consequently, while DRAM manufacturers continue to invest heavily to boost HBM production, packaging capacity constraints remain a primary factor limiting overall supply.

Strategic Significance and Outlook

The HBM supply bottleneck will continue to significantly impact the pace of AI chip market entry and AI infrastructure expansion for several years. Major HBM suppliers—Samsung, SK Hynix, and Micron—must accelerate technological innovation and capacity expansion to overcome these constraints. Particularly, rapid customer qualification and stable yield are decisive factors for gaining market share. AI chip manufacturers must forge robust partnerships with HBM suppliers to ensure a stable supply. The evolution of HBM technology and the expansion of its supply capacity will be a critical key to driving the performance improvement and widespread adoption of next-generation AI computing.

Source: https://www.biyapay.com/en/blogdetail/4403-what-are-hbm-concept-stocks-samsung-sk-hynix-micro

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