June 30, 2026: Bitcoin trades in a narrow range near the $60,000 mark, while Ethereum holds steady around $1,600. Despite the crypto market’s consolidation, a more decisive structural trend is emerging beneath the surface—AI infrastructure’s foundational hardware is undergoing a profound power shift.
Over the past decade, memory chips were considered "cyclical commodities" within the semiconductor industry—demand fluctuated with the inventory cycles of PCs and smartphones, and prices swung sharply based on supply and demand. However, this framework is being upended by the exponential growth in AI computing power. From large language model training to AI inference, from agent-based workflows to autonomous driving, massive data flows are driving relentless demand for high-bandwidth, low-latency, high-capacity memory. Storage has evolved from a "supporting component" to a "core cost driver."
At the heart of this transformation is AI Memory—next-generation storage solutions led by HBM (High Bandwidth Memory). No longer a mere accessory to CPUs or GPUs, AI Memory has become the critical bottleneck that determines whether AI computing power can be fully unleashed. Understanding why AI Memory is becoming the new core of AI infrastructure is not only essential for grasping semiconductor industry trends, but also points to a more practical question: In this memory supercycle, which assets are worth watching? And how can investors participate in global equity opportunities through platforms like Gate?
Computing Power Surges, Memory Lags: The Hard Numbers Behind the AI Storage Gap
The expansion of AI computing power is outpacing memory supply in unprecedented ways. According to the latest forecasts from CINNO Research, global AI server shipments are projected to reach roughly 3.7 million units in 2026, up 51.3% year-over-year. TrendForce expects annual AI server shipment growth to exceed 28% in 2026. Regardless of the data source, double-digit annual growth in AI server shipments is now a highly certain industry trend.
But the most telling data lies in changes to "per-server memory capacity." Gartner notes that a single AI server uses 8 to 10 times more DRAM than a traditional server, and over three times as much NAND flash. CINNO Research further estimates that, in terms of GB capacity, DDR memory demand for AI servers will jump 105% year-over-year in 2026, while HBM demand will soar 110%—both categories are set for explosive, doubling growth.
This demand surge is only half the story. The real structural support for the memory "supercycle" comes from rigid constraints on the supply side. HBM chips are about twice the physical size of standard DDR chips, consuming more wafer area. SEMI China data shows that the HBM market is expected to grow 58% to $54.6 billion in 2026, accounting for nearly 40% of the DRAM market. Even with Samsung, SK Hynix, and Micron allocating 70% of new or flexible capacity to HBM, the supply gap remains a staggering 50% to 60%.
As of Q1 2026, all HBM capacity from the three major manufacturers has been sold out. Micron’s management publicly confirmed they can only meet about 50% to 66% of actual customer demand. NVIDIA CEO Jensen Huang made it clear: the global HBM shortage "is not a short-term market fluctuation, but a structural industry dilemma that will persist for years."
From "Cyclical Commodity" to "Strategic Asset": Rethinking Memory Chip Valuation
The traditional investment logic for memory chips was built on "cyclical supply and demand fluctuations"—expansion, oversupply, price drops, production cuts, shortages, price hikes, and so on. But the current AI-driven upcycle in memory is fundamentally different from historical precedents in several key ways.
Difference 1: Demand Drivers Shift from Consumer Electronics to AI Infrastructure. In the past, smartphones and PCs were the biggest sources of DRAM and NAND demand. CINNO Research data shows that smartphones’ share of DRAM demand will plunge from 43% in 2024 to 23% in 2027. Meanwhile, AI servers’ share of total global DRAM shipments will surpass 40% in 2026, climb to 49% in 2027, and break 50% in 2028. Servers are replacing smartphones as the primary driver of memory demand.
Difference 2: Supply Expansion Faces Multiple Rigid Constraints. Unlike previous cycles where manufacturers could quickly ramp up capacity by building new lines, HBM expansion is bottlenecked by capital investment, advanced packaging processes, and lengthy fab construction cycles. SK Hynix is building the Cheongju M15X fab and establishing a dedicated HBM technology division, but it will take years for this capacity to come online. With supply responses lagging, a persistent supply-demand gap is highly likely in the medium to long term.
Difference 3: Pricing Power Shifts from Buyers to Sellers. In traditional memory cycles, downstream OEMs had strong bargaining power, often pushing memory makers into price wars during oversupply. This time, however, tight supply of high-end products, customers vying for long-term supply guarantees, and manufacturers controlling low-end expansion have all strengthened suppliers’ pricing power. JPMorgan projects the blended average selling price of HBM will rise 32% year-over-year in 2027, hitting a historic high.
Micron’s Earnings: The Strongest Proof of the Memory Supercycle
If the above logic is still "theoretical," Micron Technology’s Q3 FY2026 earnings have moved it into the "proven" category.
For the quarter ending May 28, 2026, Micron posted revenue of $41.46 billion, up 346% year-over-year and 74% quarter-over-quarter, marking its fifth consecutive record-breaking quarter. This figure easily beat market expectations of $35.84 billion. The company expects Q4 revenue to reach $49 to $51 billion.
More notably, profitability surged. Micron’s gross margin for the quarter rose to 85%, with operating margin at 81%. DRAM operations posted an 81% operating margin, while NAND operations reached 78%. These profitability levels far exceed the norm for traditional memory cycles—historically, DRAM and NAND were seen as highly commoditized, with volatile prices and rapid margin compression when supply-demand dynamics reversed.
Micron also revealed that cumulative HBM4 sales have reached about $1 billion. The company’s entire 2026 HBM capacity is already fully booked. In terms of stock performance, in the early hours of June 30 (Beijing time), Micron rose 1.14% to $1,145.28. Although the stock dipped as much as 9.6% intraday on DRAM antitrust lawsuit news, late-day buying reversed the decline and shares closed higher—this price action underscores the market’s confidence in the long-term memory story, undeterred by short-term noise.
From Industry Trends to Investment Mapping: Which Stocks Deserve Attention?
The structural rally in AI Memory isn’t just about a few individual stocks—it’s a full value chain re-rating from upstream wafer manufacturing to downstream data centers. Key areas to watch include:
HBM Market Leaders. SK Hynix leads the HBM market, with a 62% share of shipments in Q2 2025 and 57% of revenue in Q3. Goldman Sachs expects SK Hynix to maintain its dominance in HBM3 and HBM3E at least through 2026, with overall HBM market share above 50%. UBS predicts SK Hynix could capture about 70% of the HBM4 market for NVIDIA’s next-gen "Rubin" platform. Micron is also rapidly catching up, with HBM4 now in mass production and supply.
AI Server and Data Center Value Chain. CINNO Research projects global AI server shipments will approach 5 million units by 2028. The ongoing expansion in AI server shipments directly boosts demand for DRAM, NAND, HBM, and enterprise SSDs. By 2026, eSSD is expected to surpass smartphones as the largest application for NAND Flash.
Semiconductor Equipment and Advanced Packaging. HBM capacity expansion relies on breakthroughs in advanced packaging. SK Hynix is deepening its partnership with TSMC in this area. Fab expansions directly benefit semiconductor equipment manufacturers.
Gate Stock Trading: How to Access Global Memory and AI Infrastructure Investments
For investors looking to participate directly in these structural opportunities, Gate’s stock trading service offers a low-barrier, highly efficient entry point.
In June 2026, Gate launched US stock trading (June 1), Hong Kong stocks (June 11), and Korean stocks (June 22). On June 23, Gate upgraded stock trading to 24/7 availability, covering pre-market, regular hours, after-hours, overnight, and weekend periods.
For AI Memory-related stocks, Gate already covers core assets like NVIDIA (NVDA), Micron Technology (MU), SK Hynix (000660), and Samsung Electronics (005930). All trades settle in USDT, with no need for bank transfers or currency conversion. Users can simply transfer USDT from their spot or unified account to their stock account to place trades.
It’s important to note that 24/7 trading does not guarantee 24/7 liquidity. Liquidity may be relatively low during overnight and weekend sessions, with wider bid-ask spreads and increased price volatility. Price gaps may also occur across trading sessions due to accumulated market news. US, Hong Kong, and Korean stocks each follow different trading calendars and market rules—investors should fully understand the risks and make informed decisions.
Conclusion
2026 is shaping up to be one of the most defining years in memory chip industry history. The global memory chip market is expected to reach about $975 billion, up roughly 3.2 times year-over-year. Memory chip revenue is set to jump 250%, surpassing $800 billion. Bank of America Securities has called 2026 a semiconductor "supercycle" on par with the boom of the 1990s.
The essence of this supercycle isn’t just a simple supply-demand mismatch—it’s a systemic overhaul of foundational hardware driven by the AI computing revolution. AI Memory—high-bandwidth, high-capacity solutions like HBM—is moving from the sidelines to center stage, becoming the key variable that will determine whether AI computing power can keep expanding.
For investors, understanding the significance of this structural shift may be far more important than chasing short-term price swings. Memory chip valuation logic is migrating from "cyclical commodity" to "strategic asset," and this transition may last far longer than the market currently anticipates.
FAQ
Q1: What’s the difference between HBM and traditional DRAM? Why does AI need HBM?
HBM (High Bandwidth Memory) uses 3D stacking technology to vertically integrate multiple DRAM chips, dramatically increasing data bandwidth while reducing power consumption. Traditional DRAM can’t meet the bandwidth and efficiency demands of large-scale parallel computing in AI training and inference. HBM’s high bandwidth makes it the ideal companion memory for GPUs and AI accelerators, providing a critical path to overcoming the "memory wall" bottleneck.
Q2: What’s the projected size of the memory chip market in 2026?
Multiple agencies have issued different forecasts. Counterpoint Research expects the global memory chip market to reach about $975 billion in 2026. TrendForce projects combined DRAM and NAND output at $889.3 billion. WSTS forecasts memory to grow about 250% year-over-year in 2026, with the market surpassing $800 billion. While methodologies differ, all estimates point to a range between $800 billion and $1 trillion.
Q3: How big is the HBM supply gap? How long will it last?
According to SEMI China, even with the three major manufacturers allocating 70% of new capacity to HBM, the supply gap remains at 50% to 60%. As of Q1 2026, all HBM capacity from the big three is sold out. JPMorgan expects the supply-demand gap to persist through 2028. Jensen Huang says this is not a short-term fluctuation, but a multi-year structural industry challenge.
Q4: Which AI storage-related stocks can I trade on Gate?
Gate’s stock trading covers US, Hong Kong, and Korean markets. AI storage-related stocks include: US—NVIDIA (NVDA), Micron Technology (MU); Korea—SK Hynix (000660), Samsung Electronics (005930). While there are no pure memory chip plays in Hong Kong, tech giants like Tencent Holdings (00700) are major downstream buyers of HBM. Gate supports 24/7 trading, settled in USDT.
Q5: How does AI server shipment growth specifically drive memory demand?
CINNO Research data shows that, in 2026, DDR memory demand for AI servers will jump 105% year-over-year, with HBM demand up 110%. AI servers’ share of total DRAM demand will surpass 40% in 2026 and is expected to break 50% by 2028. Not only are AI server shipments rising, but the memory installed per server is also increasing—creating a dual boost in both "volume" and "quality."
