MLCC Value Surges 182%: Nvidia's New Rack Unearths AI's Next "Shortage King"

Original Title: Goldman, Morgan Stanley Sound Alarm: MLCCs Become AI Supply Chain's Scarcest Puzzle Piece, Nvidia Next-Gen Rack Usage Surges 182%

Original Author: BitGo Finance

Original Translation: Peggy

Editor's Note: The supply bottlenecks in AI infrastructure are spreading from GPUs, memory, data centers, and power systems to even more fundamental hardware components. Goldman Sachs and Morgan Stanley have recently turned their attention to MLCCs—multilayer ceramic capacitors long regarded as ordinary passive components.

In AI servers, MLCCs are critical for stabilizing current and filtering noise, ensuring the high-speed operation of chips. As Nvidia's next-generation rack architecture drives up MLCC usage per rack, their value is rapidly increasing. Goldman Sachs predicts the AI server MLCC market will more than quadruple between 2025 and 2030, while industry production capacity grows at an annual rate just over 10%. This supply-demand mismatch is emerging as a core variable in the current market cycle.

More importantly, the price cycle has already begun. Japanese leaders like Murata and Taiyo Yuden have initiated price hikes, and Japanese export data is beginning to confirm demand strength. For capital markets, the MLCC logic is straightforward: demand stems from AI servers and high-end vehicles, supply expansion is constrained, and price increases can significantly amplify profit margins.

From chips to capacitors, pricing power in the AI supply chain is shifting towards more niche and less visible segments. Whether MLCCs become the "next memory chip" still depends on sustained AI server demand; however, it is certain that this once-unremarkable basic component now stands at the starting point of a new cycle of simultaneous volume and price growth.

The following is the original text:

Supply bottlenecks in the artificial intelligence (AI) arms race are sequentially igniting opportunities across various hardware sectors. After data centers, energy infrastructure, and memory chips became the focus of capital, Wall Street giants Goldman Sachs and Morgan Stanley have simultaneously pointed their latest reports towards a long-underestimated basic component: Multilayer Ceramic Capacitors (MLCCs). Both institutions anticipate MLCCs will become the next key battleground for "simultaneous volume and price growth," and this AI-driven growth cycle could be the largest in history.

Goldman Sachs analyst Daiki Takayama noted in the report that the AI server MLCC market size is projected to surge from approximately 215 billion yen (about $14 billion) in fiscal year 2025 to roughly 920 billion yen (about $58 billion) in fiscal year 2030, an increase of over four times, with a compound annual growth rate of 34%. Goldman Sachs stated outright that the current AI-driven MLCC cycle "will be the largest and longest-lasting in history, and we believe it is still in its early stages."

MLCCs: The 'Invisible Heart' Keeping AI Servers Running

MLCCs (Multi-layer Ceramic Capacitors) can be understood as extremely miniaturized, ultra-fast charge-discharge units. Unlike ordinary batteries that store large amounts of energy for slow release, MLCCs store very little energy but can complete charge and discharge cycles in milliseconds or even less. Their core function is to smooth power fluctuations and filter noise: absorbing instantaneous voltage spikes or quickly supplying current during voltage sags, providing stable power to sensitive chips and blocking electrical interference that could corrupt digital signals.

The operational characteristics of AI servers make MLCCs indispensable. When AI models perform massive computations, processor power demand can spike in microseconds and drop rapidly to near zero after calculations cease. Power systems themselves struggle to respond to such drastic fluctuations in time. MLCCs, typically installed directly near the AI chip, can instantaneously release energy during power peaks, preventing server crashes. Since AI chips like Nvidia GPUs need to process billions of tasks simultaneously, a top-tier AI server rack may require up to 600,000 MLCCs working in concert to maintain system stability.

Goldman Sachs analyst Nelson Armbrust further pointed out that MLCCs have become the third most costly component in the AI server Bill of Materials (BOM), trailing only GPUs and memory. The overall MLCC market is currently around $15 billion, with the server-related segment being approximately $1.3 billion, expanding at an 80% compound annual growth rate. In contrast, demand growth in other application areas like automotive and smartphones has notably slowed. Daiki Takayama estimates that the cost share of MLCCs in the AI server BOM will gradually increase from the current ~0.5% to about 1%.

Structural Supply-Demand Contradiction: Annual Capacity Growth of Just 10%, Struggling to Absorb a Fourfold Demand Shock

The core factor igniting market attention is the severe structural supply-demand imbalance facing the MLCC industry. Goldman Sachs analyst Allen Chang clearly stated that the entire MLCC industry's annual capacity growth rate is just slightly above 10%. Furthermore, expansion progress is constrained by internal engineering resources, making significant acceleration difficult. However, the demand shock from AI servers is on an entirely different scale. Goldman Sachs expects MLCC demand stemming from AI servers to grow approximately 4.3 times between fiscal year 2025 and fiscal year 2030.

Adding to market concerns, demand for high-voltage, high-capacitance MLCCs driven by automotive electrification remains strong, with MLCC usage per vehicle continuing to rise. These two demand pillars—AI servers and electric vehicles—are collectively consuming already limited new production capacity. This leads to a situation where, even with declining consumer electronics demand, relevant customers are actively seeking long-term supply agreements to hedge against potential future shortages.

Signals of current market tightness are appearing on multiple fronts: lead times for high-end MLCCs (high-capacitance, high-voltage specs) have exceeded 20 weeks; spot and distributor channel prices for low-capacitance and consumer-grade MLCCs have risen 20% to 40% due to stockpiling and duplicate ordering; and prices of key raw materials like nickel and silver remain elevated, pressuring costs across product types.

Price Increase Cycle Officially Underway: Japanese Duo Takes the Lead, Official Data Confirms Trend

Price signals are intensifying rapidly. Price hike actions by Japan's two leading companies, Murata Manufacturing and Taiyo Yuden, mark the official start of the MLCC price increase cycle. Starting April 1st this year, Murata raised prices by 15% to 35% for MLCC products used in AI servers and high-end automotive applications. Taiyo Yuden has also notified customers of price adjustments starting in May across multiple product lines, including MLCCs, inductors, RF devices, FBAR/SAW devices, and aluminum electrolytic capacitors, citing continued increases in costs of precious metals and other raw materials.

Trade statistics released by Japan's Ministry of Finance on May 28th validated this price trend from a macro perspective. Data show that in April, the average export price for MLCCs rose 3% month-over-month and 16% year-over-year; export volume increased 10% year-over-year; and export value surged 28% year-over-year. Goldman Sachs believes this data confirms signals from recent Japanese MLCC manufacturer earnings reports: all companies confirmed strong order momentum remains.

Looking at the timeline of the entire AI supply chain, Goldman Sachs' analytical framework shows that MLCC price increases lag significantly behind core AI components like DRAM, NAND flash, ABF substrates, and CCL (Copper Clad Laminate). Therefore, Goldman Sachs judges that among all AI components and materials, MLCCs have the longest and most sustainable upside for price increases. Goldman Sachs has revised its year-over-year MLCC price change forecast for 2026 from roughly 0% to 0% to +5%, emphasizing that actual future increases could be much higher than this level.

Remarkable Profit Leverage: A 5% Price Hike Could Boost Operating Profit by up to 37%

For investors, the profit leverage from the MLCC supply-demand mismatch should not be underestimated. Daiki Takayama estimates that a mere 5% product price increase could theoretically boost Murata's operating profit by approximately 13% and Taiyo Yuden's operating profit by up to 37% in fiscal year 2027.

Goldman Sachs forecasts Murata's fiscal year 2027 sales to reach 1.05 trillion yen (about $6.6 billion), up 13% year-over-year; and Taiyo Yuden's sales to reach 286 billion yen (about $1.8 billion), also up 13% year-over-year. Goldman Sachs maintains "Buy" ratings on Murata, Taiyo Yuden, and TDK. Its constructed Asian MLCC thematic stock portfolio has recently started strengthening but still shows significant catch-up potential compared to other popular AI themes.

Morgan Stanley Dissects Nvidia's New Rack: Peripheral Component Importance Rises, MLCC Usage Surges 182%

Another significant catalyst comes from Nvidia's next-generation Vera Rubin AI rack. After dissecting Nvidia's latest VR200 rack, Morgan Stanley found that the importance of peripheral components in the latest BOM is rapidly increasing.

The MLCC value per single rack has risen from approximately $1,530 in the previous GB300 generation to roughly $4,320, a staggering increase of 182%. While the absolute value of MLCCs remains lower than GPUs, memory, and PCBs, their growth rate among peripheral components is exceptionally prominent.

Morgan Stanley's channel checks further reveal that MLCC usage on both compute boards and switch boards has increased significantly, with the increase on compute boards being more pronounced. Additionally, the newly introduced BlueField and ConnectX modules will further boost total MLCC usage per rack. This partially explains the current robust demand for high-end AI server MLCCs and motivates multiple ODM manufacturers to actively prepare inventory for the production and delivery of Rubin racks starting in the second half of 2026.

Morgan Stanley's teardown of the Nvidia Vera Rubin rack shows changes in key component values as follows:

Market intelligence indicates that in the infrastructure arms race of the AI super cycle, the sequential rotation of supply bottlenecks has already created wave after wave of market winners. Goldman Sachs' latest assessment describes MLCCs as the "new memory chips"—a niche segment of passive components standing at the starting point of a cycle of simultaneous volume and price increases.

With exponential demand shocks from AI servers and Nvidia Rubin racks, lead times for high-end MLCCs exceeding 20 weeks, price hikes initiated by Japanese industry leaders, and persistently strong official export data, all signals point to the same conclusion: this AI-driven MLCC super cycle has only just begun.

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