HBM: The "Golden Memory" under the AI Computing Bottleneck, Market Size Surges 58% and Investment Logic for 2026

On June 22, 2026, South Korea's capital market witnessed a historic moment—SK Hynix (000660.KS) saw its stock price rise to 2.95 million won during trading, bringing its market capitalization to 208.1 trillion won, surpassing Samsung Electronics (005930.KS) at 207.3 trillion won for the first time, breaking Samsung's 26-year reign as the top South Korean company by market cap. Behind this milestone lies a power reorganization in the memory chip industry driven by generative AI. And the core protagonist of this restructuring is HBM (High Bandwidth Memory).

Over the past two years, almost all discussions about AI computing power have revolved around GPUs. Nvidia's chips are in short supply, and TSMC's advanced process capacity is fully booked—these stories have been told repeatedly. But beneath the GPU spotlight, a more hidden yet more critical bottleneck is quietly tightening—HBM. Without sufficient high-bandwidth memory, even the most powerful computing chips can only idle.

In 2026, HBM is evolving from a niche segment of the semiconductor industry into a strategically scarce resource that determines the expansion speed of AI infrastructure. This article systematically breaks down why HBM has become the "golden memory" of the AI era from four dimensions: technical principles, market logic, competitive landscape, and investment targets.

HBM Technical Principles: The 3D Stacking Revolution to Break the "Memory Wall"

To understand why HBM is so important, we must first return to a fundamental issue: in modern computing architectures, the speed gap between processors and memory is widening. CPU or GPU computing speed doubles every 18 to 24 months, but memory bandwidth improvements lag far behind. This contradiction is known as the "Memory Wall"—no matter how powerful the computing power, if data cannot be delivered in time, the chip can only idle and wait.

HBM was born to solve this bottleneck. It is a high-performance memory architecture that vertically stacks multiple DRAM chips and uses Through Silicon Via (TSV) technology to achieve high-speed interconnects between chips. Simply put, traditional memory lays DRAM chips flat on a circuit board, with data transmitted through a limited number of pins; HBM vertically packages DRAM chips like "stacking acrobats" and transmits data through thousands of fine channels simultaneously, achieving bandwidth far exceeding traditional DDR memory.

HBM's unique design gives it unprecedented bandwidth density. Taking the latest HBM4 as an example, the official specification released by JEDEC in April 2025 shows that HBM4's interface width has doubled to 2,048 bits, with single-stack bandwidth reaching 2 TB per second. Samsung's mass-produced HBM4 uses a 12-layer stacking scheme, with a single-stack base capacity of 36 GB, pin transfer rate of 13 Gbps, and total single-stack bandwidth of up to 3.3 TB/s.

It is this "high bandwidth + low power consumption" characteristic that makes HBM an irreplaceable core component in AI training and inference scenarios. Large language models often have hundreds of billions of parameters, and each forward and backward propagation requires massive data exchange between the processor and memory—only HBM can provide sufficient bandwidth to support this process.

Market Explosion: A Leap from $13.4 Billion to $54.6 Billion

The expansion speed of the HBM market is redefining the growth curve of the entire memory chip industry.

According to Stratistics MRC, the global HBM market size is expected to reach $13.4 billion in 2026 and grow at a compound annual growth rate (CAGR) of 34.1% during the forecast period, potentially reaching $141 billion by 2034. Another set of data from SEMI is even more aggressive—Feng Li, President of SEMI China, pointed out at SEMICON China 2026 that the HBM market size will grow 58% to $54.6 billion in 2026, accounting for nearly 40% of the DRAM market.

The two data sets have different scopes, but they point to the same conclusion: HBM is expanding at a rate far exceeding traditional semiconductor categories. The World Semiconductor Trade Statistics (WSTS) predicts that the global semiconductor market will reach $975 billion in 2026. Meanwhile, memory will grow approximately 250% year-over-year in 2026, with the market size surpassing $800 billion. HBM is the fastest-growing and highest-margin segment within the memory sector.

The core driver of this growth comes from the continuous expansion of AI infrastructure. Global AI infrastructure spending will reach $450 billion in 2026, with inference computing accounting for over 70% for the first time. AI models are evolving from the training phase to inference and agentic AI, meaning demand for high-performance memory is not slowing down but instead continuing to expand.

Supply-Demand Imbalance: Sold-Out Capacity and Structural Gaps

Alongside the rising market size is an increasingly severe supply-demand imbalance.

Although the three major manufacturers—Samsung, SK Hynix, and Micron—have allocated 70% of new or adjustable capacity to HBM, the HBM capacity gap remains as high as 50% to 60%. In 2025, the HBM gap rate was 45%, and in 2026 it remains at a high 43.5%. Institutional calculations show that in 2026, the global DRAM supply-demand gap is approximately 7%, and the HBM gap is about 6%, with the tightness continuing to intensify; by 2027, the DRAM and HBM gaps will expand to 9%.

More notably, all HBM capacity from the three major manufacturers in 2026 was locked in by downstream customers for the entire year, and many core customers have even locked capacity through 2028. Micron's management confirmed in its fiscal third-quarter 2026 earnings report that the company can only meet about 50% to 66% of actual customer demand. Goldman Sachs expects that memory supply shortages will persist until 2028.

This supply-demand imbalance is not a short-term spike but is driven by multiple structural forces. On the demand side, the ever-expanding parameter scale of AI models and the rise of inference demand provide rigid support; on the supply side, the complexity of TSV processes, the yield ramp-up of advanced packaging, and equipment delivery cycle constraints mean that new capacity will not be released until at least 2028 to 2029. International investment banks generally believe that the HBM supply shortage is an industry trend lasting at least three years.

Triad Battle: SK Hynix, Samsung, and Micron's Power Game

The competitive landscape of the HBM market is forming an oligopoly centered on SK Hynix, Samsung Electronics, and Micron Technology.

SK Hynix is the current absolute leader in the HBM market. According to TrendForce data, in 2026, SK Hynix accounts for about 50% of global HBM production bit share, Samsung about 28%, and Micron about 22%. Counterpoint Research's forecast is more detailed, estimating that SK Hynix will have about a 54% share in the HBM4 market in 2026, Samsung 28%, and Micron about 18%. This leading position is directly reflected in the capital markets—SK Hynix reported Q1 2026 revenue of 52.58 trillion won, up 198% year-over-year and 60% quarter-over-quarter, exceeding 50 trillion won for the first time in a single quarter. UBS forecasts SK Hynix's total revenue in 2026 at 355.1 trillion won, with operating profit of 286 trillion won.

Samsung, after experiencing setbacks in HBM3E certification and supply timing, is now mounting a strong counterattack with HBM4. On February 12, 2026, Samsung completed the global launch of HBM4 at its Tianan campus in Chungcheongnam-do and began mass production shipments. In just about four months, cumulative sales exceeded $1 billion, making Samsung the first manufacturer in the global memory industry to reach this milestone. If the end of June is taken as the statistical node, cumulative HBM4 sales are expected to exceed $1.2 billion. Samsung plans to increase monthly production capacity of its 1c DRAM process node to approximately 150k wafers by the end of 2026, to be used for HBM4 mass production.

Although Micron's share is relatively small, its growth rate is astonishing. In its fiscal third quarter of 2026 (ending May 31), Micron reported revenue of $41.46 billion, up 346% year-over-year, with gross margin of 84.9% and adjusted earnings per share of $25.11, up 1,215% year-over-year. Micron's HBM4 12-layer product ramp-up speed is twice that of the HBM3E 12-layer version, and the company has cumulatively delivered over $1 billion in HBM4 revenue. Micron management estimates that HBM supply-demand tightness will persist beyond 2027.

In the overall DRAM market, Samsung still maintains a comprehensive advantage. In Q1 2026, Samsung's DRAM revenue reached $37.32 billion, up 93.4% quarter-over-quarter, with a market share of 38.5% ranking first; SK Hynix had revenue of $27.98 billion, up 62.5% quarter-over-quarter, with a market share of 28.8%. This comparison clearly shows that SK Hynix's market cap surpassing is not based on overwhelming dominance in the overall DRAM market, but rather on the valuation premium derived from its absolute dominance in the high-profit HBM niche.

Investment Opportunities in the HBM Supply Chain

The HBM supercycle is cascading down the industrial chain, creating differentiated opportunities for investment targets in various segments.

First Tier: The Three Major Memory Manufacturers. SK Hynix, Samsung Electronics, and Micron Technology, leveraging technology monopolies and capacity scarcity, capture the vast majority of excess profits in the supply chain, with gross margins exceeding 70% or even 80%. These three companies are the most direct and core beneficiaries of the HBM boom.

Second Tier: Advanced Packaging and Testing. HBM capacity expansion directly drives demand for advanced packaging. In the A-share market, packaging and testing leaders such as JCET, Tongfu Microelectronics, and Huatian Technology are attracting market capital. Additionally, semiconductor equipment companies like North Huachuang (Naura) and AMEC (Advanced Micro-Fabrication Equipment) benefit from the upward capital expenditure cycle driven by global memory expansion.

Third Tier: Domestic Memory Chip and Materials Companies. Against the backdrop of sustained global DRAM and NAND supply tightness, domestic memory chip manufacturers have a window for import substitution. Companies like GigaDevice, Beijing StarTimes, XTX Technology (Dongxin), and Puyuan (Puran) are drawing market attention. Since June, A-share computing hardware concept stocks have risen an average of 19.05%.

Fourth Tier: HBM Equipment and Materials. Including HBM equipment (Wanrun, Hongsu), packaging and testing (Powertech, KYEC), and AI servers (Quanta, Wistron, Wiwynn), among other sub-segments.

Mapping to the Crypto Industry: Indirect Links Between HBM and Digital Assets

For those working in or investing in the crypto industry, HBM's boom cycle is also worth noting—although HBM and crypto assets are in different tracks, there is a clear logical transmission chain between the two.

First, the expansion of AI computing infrastructure directly drives demand for GPUs, which are the largest purchasers of HBM. Nvidia, as the world's largest HBM buyer, its chip production and shipment pace directly affect HBM supply-demand balance. The crypto mining industry, as one of the important downstream markets for GPUs, is also indirectly affected by this supply chain dynamic—when AI computing demand crowds out GPU capacity, the cost and difficulty of acquiring crypto mining hardware increase.

Second, the stock performance of the HBM trio has become a barometer for measuring the heat of AI infrastructure investment. In June 2026, Gate officially launched real stock trading functionality, allowing users to directly trade stocks and ETFs from major securities markets such as Micron, Samsung Electronics, and SK Hynix using USDT on the platform. This means crypto investors can directly participate in investment opportunities from the HBM supercycle through this channel.

As of June 26, 2026, Bitcoin is quoted at approximately $59,592, down over 52% from its all-time high of $126,223 in October 2025. Ethereum has similarly weakened to around $1,510. Against the backdrop of overall pressure in the crypto market, the independent boom cycle of the HBM supply chain provides investors with a cross-asset allocation perspective—the structural shortage and excess profits of traditional semiconductor hardware form a certain degree of hedging relationship with the cyclical fluctuations of crypto assets.

Conclusion: HBM Is Not a Bubble, It's the Laws of Physics

The heat around HBM is not a theme artificially created by capital markets. Its underlying logic is built on three unavoidable physical and industrial realities: the exponential growth in AI model parameter counts imposes rigid demand for memory bandwidth; the complexity of TSV 3D stacking processes naturally slows capacity release; and only three companies globally—SK Hynix, Samsung, and Micron—have the ability to mass-produce HBM.

This is not a story that can be replicated indefinitely. The wafer capacity required to produce HBM is about 3 to 4 times that of traditional DRAM. The construction cost of a 2nm fab has already exceeded $25 billion. These numbers represent real physical constraints and capital barriers—they form the strongest moat on the HBM supply side and determine that this "golden age of memory" will not be short-lived.

The conclusion from multiple investment banks, including Goldman Sachs, is highly consistent: this "memory drought" is by no means a short-term spike; the structural shortage of HBM supply will last at least until 2028. For investors, understanding HBM is not just about grasping an investment track, but also about understanding the operating logic of the underlying infrastructure in the AI era—at the pinnacle of computing power, what is most scarce is often not the computing power itself, but the "data pipeline" that feeds it.

FAQ

1. What is the difference between HBM and traditional memory?

HBM uses TSV (Through Silicon Via) technology to vertically stack multiple DRAM chips, achieving bandwidth density far exceeding traditional DDR memory. Traditional memory uses a planar layout with limited data transmission channels; HBM's interface width can reach 2,048 bits, with single-stack bandwidth exceeding 2 TB/s. HBM is primarily for bandwidth-intensive scenarios like AI training and high-performance computing, while traditional memory is more suitable for general computing and consumer electronics.

2. Why is HBM capacity so tight?

Three main reasons: First, the wafer capacity required to produce HBM is about 3 to 4 times that of traditional DRAM; second, the yield ramp-up for TSV processes and advanced packaging is slow, and equipment delivery cycles are long; third, only three companies globally have mass production capabilities, and all 2026 capacity is already sold out. The combination of these three constraints means that new capacity will not be released until at least 2028 to 2029.

3. Which stocks are related to HBM?

Three major memory manufacturers: SK Hynix (000660.KS), Samsung Electronics (005930.KS), Micron Technology (MU.O). A-share HBM concepts cover advanced packaging (JCET, Tongfu Microelectronics, Huatian Technology), semiconductor equipment (Naura, AMEC), memory chips (GigaDevice, Beijing StarTimes), and other segments.

4. How long can HBM's high margins last?

The gross margins of the three major manufacturers have already exceeded 70% or even 80%. Micron management estimates that HBM supply-demand tightness will persist beyond 2027. Goldman Sachs expects supply shortages to continue until 2028. As long as AI infrastructure capital expenditure does not slow down, the high-margin cycle of HBM is expected to continue.

5. How can crypto investors participate in the HBM trend?

Gate has launched real stock trading functionality, allowing users to directly trade stocks and ETFs such as Micron, Samsung Electronics, and SK Hynix using USDT. Additionally, HBM supply-demand changes will propagate through the GPU supply chain to crypto mining equipment, providing indirect reference signals for cross-asset allocation.