Mid-June 2026 marks an exceptionally rare moment for the global memory chip industry. SanDisk (SNDK) shares nearly hit the $2,000 mark during intraday trading on June 12, with year-to-date gains surging past 734%. Yet, the market is far from a one-way rally. On June 16, SNDK closed down 5.52% at $1,991.55, with intraday volatility reaching 9.45%—swinging sharply between a low of $1,980.16 and a high of $2,167.33. On the same day, Micron Technology (MU) dropped 6.18%, with trading volume hitting $47.104 billion. The diverging performance within the memory chip sector highlights the deep market debate over the logic driving AI memory demand.
To truly grasp the nature of this cycle, it’s essential to first clarify the distinct roles of NAND and HBM within the AI ecosystem. This isn’t just a technical issue—it’s a core variable shaping supply and demand dynamics, pricing mechanisms, and investment strategies.
Three-Tier Memory Architecture in AI Systems
Memory in AI computing systems isn’t a monolithic layer. Technically, HBM, DRAM, and NAND each serve fundamentally different functions.
HBM (High Bandwidth Memory) sits directly alongside AI accelerators (GPU/TPU), acting as the critical "real-time data channel" that feeds data rapidly to compute chips during AI training. DRAM manages the system’s live operating status, conversation memory, and intermediate computation results. Enterprise-grade SSDs based on NAND flash provide persistent storage for massive datasets, embedded model parameters, retrieval indexes, logs, and checkpoints.
This layered architecture determines the order and elasticity with which each memory product benefits from expanding AI demand. HBM gains from the exponential growth in model parameter sizes—Morgan Stanley data shows HBM capacity rising from about 10TB in 2020 to roughly 18PB in 2026, a multi-order-of-magnitude increase. NAND’s surge, meanwhile, is driven by expanding needs during the AI inference phase: as large AI models move from training to widespread deployment, inference workloads see explosive growth in context storage (KV cache) requirements.
Supply-Demand Gap: Structural Differences Behind the Numbers
In 2026, the global memory market faces its most severe supply shortage in nearly 15 years. However, the supply-demand gap varies significantly across segments.
According to SemiAnalysis, DRAM supply will fall short of demand by about 7% in 2026, with an HBM gap of roughly 6%—expected to widen to 9% in 2027. Industry research further projects supply shortfalls for DRAM, NAND flash, and HBM at 4.9%, 4.2%, and 5.1% respectively in 2026, all at their highest levels since 2011.
Structural constraints on the supply side deserve special attention. Morgan Stanley analyst Joseph Moore noted in an early June report that the main barrier to expanding memory chip supply isn’t a lack of capital investment, but hard physical limits—insufficient cleanroom capacity and restricted supply of EUV lithography machines. Moore stated plainly, "There’s no quick fix for memory shortages," predicting that supply constraints could persist for two to three years or even longer.
NAND faces similar supply-side constraints. Enterprise SSDs have become the key driver of NAND demand growth, with overall NAND demand projected to rise 18% in both 2026 and 2027. However, wafer input is expected to shrink by 5% in 2026 and grow only 3% in 2027. SanDisk’s joint venture partner Kioxia has only slightly adjusted its long-term bit growth forecast from 20% to 22%, while capital expenditures remain low. The significant gap between demand and supply growth forms the fundamental support for continued NAND price increases.
Pricing Mechanism: From Cyclical Commodity to Strategic Asset
Another defining feature of this memory cycle is a fundamental shift in pricing mechanisms.
Traditionally, memory chip prices have been dictated by spot market supply and demand, resulting in pronounced cyclical volatility. In this cycle, however, major cloud service providers are increasingly securing capacity through long-term supply agreements and prepayments. Morgan Stanley notes that long-term contracts could account for 70% or more of total supply over the next three to five years. This shift means DRAM-related stocks "may be re-rated to at least 8–10x earnings, compared to the current 5x, offering significant upside potential."
The impact of this pricing shift varies between NAND and HBM. HBM, as the core bottleneck for AI training, sees its price elasticity mainly constrained by advanced packaging capacity. NAND pricing, meanwhile, is shaped by both enterprise SSD demand and disciplined supply management. Bernstein points out that data center clients have become the main buyers across all memory segments, and their price sensitivity is much lower than traditional consumer buyers. This dynamic supports stronger and more sustained pricing power than in previous cycles.
Institutional Perspective: Morgan Stanley’s Target Price Upgrade and Tepper’s Positioning Logic
On June 3, Morgan Stanley sharply raised its target price for SanDisk from $1,100 to $1,750, and doubled Micron’s target from $520 to $1,050. The firm also raised its earnings forecasts for SanDisk by 12% for FY2026 and 24% for FY2027. Despite both stocks having gained roughly 564% and 242% respectively since the start of the year, Morgan Stanley believes their valuations remain below the implied 10x earnings for FY2027, leaving ample room for further expansion.
Top hedge funds echo this view. Billionaire investor David Tepper’s Appaloosa Management disclosed in its Q1 2026 13F filing a new position of about 281,250 shares in SanDisk. Even after SNDK’s roughly 535% gain in 2026, Tepper chose to initiate a stake at these levels. Appaloosa’s Q1 portfolio was valued at about $6.9 billion, with notable concentration—the top five holdings accounted for over 48% of the total. Capital has shifted away from traditional consumer and China-related stocks, moving toward AI infrastructure, power, and memory chips. This pivot aligns directionally with the industry logic behind the memory chip supercycle.
Market Validation: Dual Feedback from Earnings and Share Prices
SanDisk’s fundamentals are validating this logic. The company’s Q3 revenue reached $5.95 billion, up 97% quarter-over-quarter, with data center revenue soaring 233%. Q4 guidance projects revenue between $7.75 and $8.25 billion, with expected non-GAAP diluted EPS of $30–33. SanDisk also disclosed three signed NBM (NAND-based memory) long-term agreements, with two more added in Q4.
Rising prices continue to reinforce the supply-demand thesis. TrendForce data shows generic DRAM contract prices jumped 93–98% quarter-over-quarter in Q1 2026, while NAND contract prices rose 85–90%. Morgan Stanley estimates DRAM prices surged 40% in the March–May quarter, with another 15% increase expected in June–August; Q3 2026 DRAM prices are projected to rise a further 20–30%.
From Memory Sector to Trading Terminal: Gate’s Stock Trading Strategy
For investors tracking the memory chip supercycle, efficient participation in the US equity market is crucial. In June 2026, Gate officially launched real stock trading functionality, entering a strategic partnership with Alpaca—a fully licensed US Broker-Dealer and clearing firm. Users can invest in over 10,000 stocks and ETFs listed on the NYSE and NASDAQ directly using USDT liquidity from their Gate accounts.
Gate’s stock trading offers three core advantages:
Ultra-low fractional share threshold. Investors can start with as little as 0.01 shares, meaning just $1 is enough to begin trading US equities. For high-priced stocks like SanDisk, which are near $2,000 per share, fractional shares dramatically lower the entry barrier for retail investors.
Direct USDT settlement. Users skip the cumbersome process of "selling crypto → withdrawing fiat → cross-border remittance → broker funding." Trades settle directly in USDT, eliminating the biggest friction point for crypto investors entering the US stock market.
Regulatory compliance. All trades are executed by Alpaca, under full US regulatory oversight. Dividend income and corporate actions are automatically credited to Gate accounts.
Gate also launched Hong Kong stock trading in June, covering over 1,500 HKEX-listed equities. Users can manage both crypto and stock assets in a unified interface. This positions Gate as a multi-asset investment hub, bridging crypto assets and traditional financial markets through a single entry point.
Conclusion
The fundamental difference between NAND and HBM in the AI demand equation stems from their distinct roles within AI computing architecture—HBM addresses extreme bandwidth needs during training, while NAND serves as an expandable memory layer for large-scale inference deployments. These differences shape their respective supply-demand dynamics, pricing mechanisms, and benefit cycles.
The 2026 supercycle in memory chips is a structural transformation driven by the AI technology revolution, not just a short-term supply-demand fluctuation. Physical constraints on the supply side, the shift to long-term contractual pricing, and sustained institutional capital inflows together form the core logic supporting this cycle.
For investors, understanding the differentiated logic between NAND and HBM is key to making effective allocation decisions within the memory chip sector. Gate’s stock trading feature offers crypto ecosystem users a low-barrier, high-efficiency channel to participate in the US memory chip rally—enabling direct USDT trades in SNDK and other memory leaders. This may well be the shortest path connecting AI industry trends with personal investment decisions.
