Gate Research: Market Cap of the Big Three Storage Giants Collectively Exceeds One Trillion

Summary

• The total market capitalization of the global memory and storage sector has experienced explosive growth, with the three giants Samsung Electronics, SK Hynix, and Micron Technology each surpassing the trillion-dollar mark.

• The continued growth in demand for AI large model training and inference is significantly driving up the demand intensity and value of storage products like High Bandwidth Memory (HBM), DDR5, and enterprise SSDs in data centers.

• Micron Technology has recently entered the trillion-dollar market cap club, becoming one of the most closely watched revaluation targets in the AI storage supply chain. According to StockAnalysis data, as of June 3, 2026, Micron's market cap stood at approximately $1.17 trillion.

• The core driver of this rally in the storage sector is not a traditional DRAM cycle rebound, but rather the market beginning to reprice the structural value inherent in AI servers, HBM, Long-Term Agreements (LTAs), and the supply-demand tightness in the storage industry.

• Gate has officially launched stock trading, allowing users to trade stocks and ETFs from major securities markets directly on the platform using USDT. The stock contracts section now offers perpetual contracts, supporting USDT settlement and 1-20x leverage for two-way trading. Gate has also launched leveraged ETF tokens, providing investors with long exposure to stocks.

• Micron's trillion-dollar market cap is not the result of a single earnings cycle but a reflection of the combined effects of AI storage value revaluation, HBM product upgrades, long-term agreement mechanisms, and improved industry supply-demand dynamics.

1. AI-Driven Memory & Storage Sector

In the past, the memory and storage industry was often viewed as a quintessential cyclical sector, with corporate profitability highly dependent on supply-demand fluctuations and price elasticity. However, in the AI era, memory is evolving from a mere supporting component in general-purpose hardware to a critical resource in computing infrastructure.

Large model training and inference require not only more powerful GPUs and interconnect capabilities but also memory and storage systems with higher bandwidth, greater capacity, and lower latency. Whether it's HBM on the GPU side or DDR5 and enterprise SSDs on the server side, their importance is significantly increasing. For cloud vendors and data center customers, storage is no longer just a cost item but a key variable affecting model training efficiency, inference throughput, and overall deployment costs.

The change brought about by the expansion of AI applications is not just an increase in the shipment volume of memory chips, but more importantly, a rise in the proportion of high-end products. HBM offers higher bandwidth, greater integration, and higher added value compared to standard DRAM; enterprise SSDs also benefit from increased data center workloads. As product mixes shift towards high-performance solutions, the revenue structure, profit margins, and valuation frameworks of leading manufacturers are likely to change.

Unlike the traditional historical logic of "price increase leading to capacity expansion," the supply release of high-end storage products like HBM is relatively limited due to constraints in manufacturing processes, yield rates, advanced packaging, and customer qualification cycles. Concurrently, key clients increasingly prefer to secure capacity and partial pricing through long-term supply agreements. This gives leading companies greater revenue visibility and pricing power than in the past, making this cycle's boom exhibit more distinct structural characteristics.

Micron Technology, Inc. (NASDAQ: MU), founded in 1978 and headquartered in Boise, Idaho, USA, is a leading global provider of semiconductor memory and storage solutions. The company designs, manufactures, and sells DRAM, NAND Flash, NOR Flash, HBM, SSDs, and storage products for data centers, mobile devices, automotive, industrial, and consumer electronics. Using Micron as a case study is not intended to focus the article on a single stock, but because Micron's product portfolio, customer structure, earnings elasticity, and market pricing quite typically reflect the evolutionary direction of the AI storage track.

2. Micron Technology

In the global memory chip industry, Micron, along with Samsung Electronics and SK Hynix, is a major DRAM supplier and a significant player in the global NAND market. As demand for large model training and inference continues to grow, AI servers are rapidly increasing their need for storage products like HBM, high-capacity DDR5, and enterprise SSDs. Memory chips are no longer just supporting components in general-purpose computing devices but are gradually becoming one of the key bottlenecks in AI computing infrastructure. Especially in GPU clusters, HBM's bandwidth, capacity, and power consumption directly impact the performance output of AI chips, leading to Micron's reintegration into the core supplier base of the AI semiconductor supply chain. This report views Micron Technology as a key representative enterprise within the AI storage supply chain and analyzes it focusing on its trillion-dollar market cap milestone, long-term agreements, HBM growth, valuation restructuring, and related trading support via Gate stock.

3. Fundamental Analysis and Investment Logic

According to Gate market data, as of June 3, 2026, Micron Technology's stock was quoted at $1,056. Based on approximately 1.1 billion diluted shares outstanding, the company's total market capitalization is roughly $1.17 trillion. Over the past year, Micron Technology (MU) has shown a clear pattern of volatile upward movement, eventually accelerating to break out. The stock price started from around $110, initially strengthening with AI storage demand expectations and steadily rising to over $400. After experiencing a period of phased consolidation, it entered a main upward wave driven by the explosion in HBM and AI data center demand. From May to June, it experienced consecutive sharp increases, reaching a high of $1,076, cumulatively rising approximately 8 times from its low of the year. Over the past year, Micron's stock price rose from around $110 to approximately $1,056, a cumulative increase of over 800%, pushing the company's market cap above $1 trillion and reflecting the market's ongoing revaluation of AI storage demand and HBM business prospects.

From a business structure perspective, Micron currently focuses on four main application areas: first, Data Center and Cloud Computing, including AI servers, enterprise servers, and networking equipment; second, Mobile Terminals, including smartphones and tablets; third, Storage Business, including enterprise and client SSDs; and fourth, Embedded Business, including automotive, industrial, and consumer electronics applications. With the continuous expansion of AI data center capital expenditures, data center-related storage demand is becoming Micron's fastest-growing and most profit-elastic business direction.

Micron's current market cap breakthrough to $1 trillion is not simply a rebound from the traditional storage cycle but stems from the market repricing its strategic value within the AI infrastructure supply chain. FY2026 Q2 results showed record revenue, gross margin, EPS, and free cash flow, confirming the inflection point in profitability driven by AI demand, tight industry supply, and upgrades to high-end storage products.

3.1 The AI Era: Storage Upgraded from Ancillary Component to Strategic Asset

In traditional computing architectures, memory chips were often seen as ancillary components to CPUs and GPUs, with industry pricing mainly influenced by cyclical supply and demand. However, in the AI era, especially with the continuous expansion of large model training and inference scales, memory bandwidth, capacity, and energy efficiency have become key bottlenecks for AI system performance.

In its FY2026 Q2 earnings release, Micron explicitly stated that the record Q2 performance reflects "the strategic value of memory in the AI era." CEO Sanjay Mehrotra stated that in the AI era, memory has become a strategic asset for customers. This indicates that Micron's management has repositioned the company from a traditional memory supplier to a core participant in AI computing infrastructure.

The rapid growth in demand for HBM, high-capacity DRAM, DDR5, and enterprise SSDs in AI servers has significantly increased the value contribution of memory products in the server BOM (Bill of Materials). As GPU clusters scale up, customers are not only concerned about chip computing power but also increasingly focused on the stability of memory supply, performance matching, and controllable deployment costs. This shift has brought Micron stronger pricing power and higher earnings elasticity.

3.2 FY2026 Q2 Results Validate Demand Strength

Micron's FY2026 Q2 revenue reached $23.86 billion, a significant increase from $13.64 billion in the prior quarter and notably higher than $8.05 billion in the same quarter last year. The company reported Non-GAAP net income of $14.02 billion, Non-GAAP EPS of $12.20, operating cash flow of $11.90 billion, and adjusted free cash flow of $6.90 billion.

More importantly, earnings quality improved simultaneously. The FY2026 Q2 Non-GAAP gross margin reached 74.9%, a significant jump from 56.8% in the prior quarter and 37.9% in the same quarter last year. The Non-GAAP operating margin reached 69.0%, expanding substantially from 47.0% in the prior quarter and 24.9% in the same period last year.

This indicates that Micron's profit growth is not solely driven by revenue increases but has achieved a leap in margins through improved product pricing, product mix, and cost efficiency. For a memory company, a gross margin increase from the 30%-40% range to over 70% signifies a significant shift in industry supply-demand dynamics and the company's product portfolio.

3.3 Data Center and Cloud Business Become Core Growth Drivers

By business segment, Micron's FY2026 Q2 growth was highly concentrated in AI and data center-related directions.

The Cloud Memory Business Unit generated revenue of $7.749 billion, with a gross margin of 74% and an operating margin of 66%. The Core Data Center Business Unit generated revenue of $5.687 billion, with a gross margin of 74% and an operating margin of 67%. Combined, these two businesses generated over $13.4 billion in revenue, becoming the company's most important growth engine.

This demonstrates that Micron's business focus is shifting from traditional consumer electronics cycles (PCs, phones) towards cloud computing, AI servers, and data centers. Compared to consumer electronics, AI data center customers are characterized by large capital expenditures, high product performance requirements, and a strong need for supply continuity, making it easier to establish high-end product premiums and long-term supply relationships.

3.4 HBM and High-End DRAM Drive Product Mix Upgrade

The product areas where Micron benefits most visibly are HBM and high-end DRAM. HBM is a critical memory product for AI GPUs and accelerators, characterized by high bandwidth, high capacity, and high energy efficiency. Its price per GB and gross margins are higher than standard DRAM.

UBS estimates that Micron's HBM ASP will grow approximately 50% year-over-year in 2027, driving continued expansion of HBM revenue. As AI chip platforms evolve, demand for HBM capacity and bandwidth increases, and Micron is well-positioned to capture a higher revenue share through HBM3E, subsequent HBM products, and advanced packaging capabilities.

The significance of the product mix upgrade is that Micron is no longer just following the average DRAM price fluctuations of the industry but is gaining stronger pricing power through high-end products. As the proportion of HBM increases, the company's overall gross margin and earnings stability will improve.

2.5 Tight Industry Supply Enhances Price Elasticity

Micron's strong FY2026 Q2 performance was also driven by tight industry supply. The results were driven by a robust demand environment, tight industry supply, and the company's execution. Some institutions expect the DRAM supply shortage to persist at least until Q2 2028, and the NAND shortage until Q4 2027. In a supply-constrained environment, DRAM and NAND prices have sustained support, allowing Micron's revenue and margins to remain high.

More importantly, this cycle differs from the past. Previously, memory manufacturers would quickly expand capacity following price increases, ultimately leading to oversupply and price declines. However, the demand growth for high-end memory from AI servers is rapid, and HBM capacity expansion is constrained by technology, yields, advanced packaging, and customer qualification cycles, making it difficult for supply release to quickly catch up with demand.

3.6 Long-Term Agreements (LTAs) Enhance Earnings Visibility

LTA stands for Long-Term Agreement. In the semiconductor memory industry, an LTA typically refers to an agreement between a supplier and a core customer regarding future supply arrangements, including purchase quantities, delivery schedules, product specifications, and, in some cases, a pricing framework. In the past, purchase agreements in the memory industry were more often "volume-based, not price-locked." Customers committed to certain purchase volumes in advance, giving suppliers some demand visibility, but prices still fluctuated rapidly with DRAM and NAND market conditions. Therefore, during industry downturns, significant price declines would directly impact the revenue and profits of memory manufacturers like Micron, Samsung, and SK Hynix.

LTAs represent another key logic behind Micron's valuation re-rating. New types of LTAs not only lock in purchase volumes but also partially lock in prices, with terms lasting 3-5 years. This differs from past procurement agreements that only locked volumes. For Micron, the value of LTAs lies in improving revenue visibility, reducing price volatility, and enhancing cross-cycle profitability. For cloud vendors and AI clients, LTAs can secure future memory supply and partially lock in costs, avoiding the need to passively accept higher prices during supply constraints. If LTAs are implemented on a large scale, Micron's business model could transition from a traditional cyclical commodity company towards a semiconductor supplier with long-term orders, stable cash flows, and higher customer stickiness.

3.7 Profitability and Cash Flow Support Valuation Restructuring

Micron's FY2026 Q2 adjusted free cash flow reached $6.9 billion, and the company's board approved a 30% increase in the quarterly dividend. This demonstrates not only a significant improvement in profitability but also a marked enhancement in cash flow quality. In capital markets, stable and substantial free cash flow typically supports higher valuations. Micron's valuation was historically low, mainly because the market was concerned about its earnings sustainability. Now, if AI demand, LTAs, and the HBM product mix upgrade collectively reduce cyclical volatility, Micron is positioned to converge its valuation from a traditional cyclical memory stock towards that of a core AI semiconductor asset.

4. Gate Stock Investment Products

The most closely watched US stock targets in the storage sector. Gate has also integrated US stock-related trading services within its TradFi section, allowing users to participate in trading stocks, ETFs, and other assets from major securities markets using USDT through a unified account system.

Unlike common stock tokenization or RWA mapping models in the market, Gate's stock service emphasizes market access capabilities and a compliant trading system. Gate Stock provides stock and ETF trading services by interfacing with compliant brokerages. These are not on-chain mapped assets or tokenized stock derivatives. Users can buy, hold, and sell stock assets through their Gate accounts, and related holdings, profit/loss, fund flows, and corporate action information can be viewed and managed uniformly within the account.

In terms of asset coverage, Gate Stock currently supports over 10,000 stocks and ETF assets, covering major securities trading markets and liquidity networks like NYSE, Nasdaq, NYSE Arca, NYSE American, and BATS. Gate Stock currently supports intraday trading, with plans to gradually expand to 24/7 round-the-clock trading, providing global users with a more flexible entry point for US stock asset allocation.

In terms of product structure, the stock-related trading tools within Gate TradFi can be categorized into three types, using MU trading products as an example:

Among these, Gate's spot stock trading is independent of the traditional CFD system. Stock trading does not involve funding rates found in perpetual contracts, nor does it have holding costs like swap fees or overnight fees that may exist in CFD products. This makes it more suitable for users wishing to hold US stock assets for the long term. In contrast, perpetual contracts and CFDs are more oriented as trading tools, suitable for directional trading or risk management on Micron's short-to-medium-term price movements.

Leveraging a unified crypto asset account system, Gate further bridges digital asset trading with stock investment scenarios. After completing KYC and meeting regional access requirements, users can enter the stock section via the TradFi module in the Gate App to view quotes, and execute trades after transferring stablecoins via the trading or asset page. This means the application scenario for USDT is extending from crypto asset trading to global stock asset allocation.

From an industry trend perspective, Gate's launch of stock trading services provides users with a unified trading entry point for both digital and traditional financial assets. For users focused on AI semiconductor themes, the introduction of actual stocks, perpetual contracts, and CFDs enables them to conduct more flexible asset allocation and trade management around memory, AI, HBM, and semiconductor cycles within a single platform.

5. Risk Warning

From a sector research perspective, future assessments of the memory industry's outlook and company quality should focus on four key dimensions: First, whether capital expenditures by AI server and cloud vendors continue