Gate Research frames the storage industry as a sector undergoing a structural change in the AI era. In the past, storage was often treated as a highly cyclical business, with corporate earnings largely tied to supply-demand swings and pricing elasticity. The report argues that this framework is no longer sufficient on its own. As large-model training and inference scale up, storage is moving from a supporting component in general-purpose hardware to a key resource inside AI computing infrastructure.
Large models require stronger GPUs and interconnects, but they also require storage systems with higher bandwidth, larger capacity and lower latency. This applies both to HBM on the GPU side and to DDR5 and enterprise SSDs on the server side. For cloud vendors and data center customers, storage is no longer only a cost item. It has become a variable that affects model training efficiency, inference throughput and overall deployment cost.
Micron as a representative AI storage case
Gate Research uses Micron Technology, Inc. (NASDAQ: MU) as a case study. Micron was founded in 1978 and is headquartered in Boise, Idaho. It is a global supplier of semiconductor memory and storage solutions, designing, manufacturing and selling DRAM, NAND Flash, NOR Flash, high-bandwidth memory HBM, SSDs and storage products for data centers, mobile devices, automotive, industrial and consumer electronics markets.
The report stresses that the use of Micron as a research case is not intended to focus the article on a single stock. Instead, Micron reflects the evolution of the AI storage track through its product range, customer structure, earnings sensitivity and market pricing. In the global memory chip industry, Micron stands alongside Samsung Electronics and SK Hynix as one of the main DRAM suppliers, and it is also an important participant in the global NAND market.
According to Gate market data, as of June 3, 2026, Micron’s stock traded at $1,056. Based on approximately 1.1 billion diluted shares outstanding, the company’s total market capitalization was about $1.17 trillion. Over the past year, Micron’s stock showed a volatile upward trend before accelerating into a breakout. The price started from around $110, rose steadily to above $400 as expectations for AI storage demand strengthened, then entered another major advance after a period of adjustment, driven by HBM and AI data center demand. From May to June, the stock climbed sharply and reached a high of $1,076. Compared with its one-year low, it rose by more than eight times, and its cumulative gain over the year exceeded 800%.
Micron’s business structure currently serves four main application areas. The first is data center and cloud computing, including AI servers, enterprise servers and networking equipment. The second is mobile devices, including smartphones and tablets. The third is storage, including enterprise and client SSDs. The fourth is embedded business, including automotive, industrial and consumer electronics applications. As AI data center capital expenditure expands, data center-related storage demand is becoming Micron’s fastest-growing and most profit-sensitive business direction.
Record FY2026 Q2 results and margin expansion
Gate Research says Micron’s market capitalization breakthrough was not simply the result of a traditional storage-cycle rebound. It was driven by the market’s repricing of the company’s strategic value inside the AI infrastructure supply chain. Micron’s FY2026 Q2 results showed record revenue, gross margin, EPS and free cash flow, validating an earnings turning point driven by AI demand, tight industry supply and upgrades toward high-end storage products.
In traditional computing architecture, memory chips were usually viewed as supporting parts outside CPUs and GPUs, with industry pricing mainly determined by cyclical supply and demand. In the AI era, especially after large-model training and inference continued to scale, memory bandwidth, capacity and energy efficiency became key bottlenecks for AI system performance. In its FY2026 Q2 earnings release, Micron stated that its record Q2 performance reflected “the strategic value of memory in the AI era.” CEO Sanjay Mehrotra said that in the AI era, memory has become a strategic asset for customers.
Micron’s FY2026 Q2 revenue reached $23.86 billion, rising sharply from $13.64 billion in the previous quarter and significantly above $8.05 billion in the same period last year. Non-GAAP net income reached $14.02 billion, Non-GAAP EPS was $12.20, operating cash flow reached $11.90 billion, and adjusted free cash flow was $6.90 billion. Profit quality improved at the same time. FY2026 Q2 Non-GAAP gross margin reached 74.9%, compared with 56.8% in the previous quarter and 37.9% in the same period last year. Non-GAAP operating margin reached 69.0%, compared with 47.0% in the previous quarter and 24.9% in the same period last year.
This shows that Micron’s earnings were not only lifted by revenue growth. The company also achieved a jump in profitability through improvements in product pricing, product mix and cost efficiency. For a storage company, a move in gross margin from the 30%-40% range to above 70% indicates that industry supply-demand conditions and the company’s product mix have changed markedly.
By business unit, Micron’s FY2026 Q2 growth was highly concentrated in AI and data center-related areas. Cloud Memory Business Unit revenue reached $7.749 billion, with a gross margin of 74% and an operating margin of 66%. Core Data Center Business Unit revenue reached $5.687 billion, with a gross margin of 74% and an operating margin of 67%. The combined revenue of these two units exceeded $13.4 billion, making them the company’s most important growth engines.
The product categories from which Micron benefited most clearly were HBM and high-end DRAM. HBM is a key memory product for AI GPUs and accelerators. It features high bandwidth, high capacity and high energy efficiency, while its price per GB and gross margin are both higher than ordinary DRAM. UBS expects Micron’s HBM ASP to increase by about 50% year on year in 2027 and to drive continued HBM revenue expansion. As AI chip platforms iterate and demand for HBM capacity and bandwidth rises, Micron is positioned to raise the revenue contribution of HBM3E, subsequent HBM products and related advanced packaging capabilities.
Supply constraints and long-term agreements
Micron’s strong FY2026 Q2 performance also came from tight industry supply. The report states that results were driven by a strong demand environment, tight industry supply and company execution. Some institutions expect DRAM undersupply to last until at least the second quarter of 2028 and NAND undersupply to continue until the fourth quarter of 2027. In a constrained supply environment, DRAM and NAND prices have ongoing support, allowing Micron’s revenue and margins to remain at elevated levels.
Gate Research also points out that this cycle differs from past memory cycles. Historically, storage manufacturers often expanded production quickly after prices rose, eventually leading to oversupply and price declines. In the current environment, demand for high-end memory in AI servers is growing rapidly, while HBM capacity expansion is constrained by technology, yield, advanced packaging and customer certification cycles. As a result, supply release is not easy to accelerate enough to catch demand.
LTA stands for Long-Term Agreement. In the semiconductor memory industry, an LTA usually refers to a supply arrangement agreed in advance between a supplier and core customers for a future period, including purchase volume, delivery schedule, product specifications and, in some cases, a pricing framework. In the past, procurement agreements in the storage industry were more often structured as “volume locked, price not locked.” Customers committed to certain purchase volumes in advance, giving suppliers some demand visibility, but prices still moved quickly with DRAM and NAND market supply-demand conditions. When the industry entered a downturn, sharp price declines still directly hit the revenue and profit of storage manufacturers such as Micron, Samsung and SK Hynix.
In the report, LTA is another key logic behind Micron’s valuation rerating. Newer LTAs not only lock in purchase volume but also partially lock in price, with terms reaching three to five years. For Micron, LTAs improve revenue visibility, reduce price volatility and strengthen cross-cycle profitability. For cloud vendors and AI customers, LTAs secure future memory supply and partially lock costs, helping them avoid passively bearing higher prices when supply is tight. If LTAs are implemented at scale, Micron’s business model shifts from that of a traditional cyclical commodity company toward a semiconductor supplier with long-term orders, more stable cash flow and stronger customer stickiness.
Micron’s FY2026 Q2 adjusted free cash flow reached $6.9 billion, and its board approved a 30% increase in the quarterly dividend. This shows that profitability improved sharply while cash flow quality also strengthened. In capital markets, stable and high free cash flow usually supports higher valuations. Micron’s past valuation was lower mainly because the market was concerned that its earnings were not sustainable. Now, if AI demand, LTAs and the upgrade of the HBM product mix jointly reduce cyclical volatility, Micron has room to move closer to the valuation framework of core AI semiconductor assets rather than that of a traditional memory-cycle stock.
Gate stock access and product structure
The report also discusses Gate’s stock service. Unlike common stock tokenization or RWA mapping models, Gate’s stock service emphasizes market access and a compliant trading system. Through connections with compliant brokers, Gate provides users with stock and ETF trading services. These are not on-chain mapped assets and are not tokenized stock derivatives. Users can buy, hold and sell stock assets through their Gate accounts, while positions, profit and loss, fund flows and corporate action information can be viewed and managed in one account.
In terms of asset coverage, Gate stocks currently support more than 10,000 stocks and ETF assets, covering major securities trading markets and liquidity networks including NYSE, Nasdaq, NYSE Arca, NYSE American and BATS. Gate stocks currently support intraday trading and will gradually expand to 24/7 trading, providing global users with a more flexible entry point for U.S. stock asset allocation.
Within Gate TradFi, stock-related trading tools can be divided into three categories. Using MU-related trading products as an example, Gate stock spot trading is independent from the traditional CFD system. Stock trading does not involve funding rates found in perpetual contracts, and it is also different from CFD products that may include holding costs such as swap fees or overnight fees. Therefore, it is more suitable for users who want to allocate to U.S. stock assets over the long term. By contrast, perpetual contracts and CFDs are more oriented toward trading tools and are suitable for directional trading or risk management around short- and medium-term price movements in Micron.
Relying on a unified crypto asset account system, Gate further connects digital asset trading with stock investment scenarios. After completing KYC and meeting access requirements in their region, users can enter the stock section through the TradFi area of the Gate App, view market quotes, and participate in trading after transferring stablecoins through the trading page or asset page. This extends the use case of USDT from crypto asset trading to global stock asset allocation.
Gate Research concludes that the storage track can no longer be understood solely through the old “price-cycle stock” framework. A more suitable approach is to view it as a semiconductor sub-sector in which cyclical attributes remain, while the weight of structural upgrades continues to rise. Micron provides a clear sample for observing this transition. At the same time, LTAs can help stabilize part of revenue, but the locked-price ratio, execution period and customer commitments still carry uncertainty, and they cannot fully eliminate industry volatility. Micron’s share price and market capitalization have already risen sharply, and the market has high expectations for the AI storage supercycle and valuation rerating. If results fail to meet expectations, share price volatility could intensify.
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