Nvidia Rack Disassembly Reveals New Growth Opportunity, MLCC Value Surges 182%

marsbitPublicado em 2026-06-01Última atualização em 2026-06-01

Resumo

Supply bottlenecks in AI infrastructure have expanded to fundamental hardware components like multilayer ceramic capacitors (MLCCs), crucial for stabilizing power and filtering noise in AI servers. Both Goldman Sachs and Morgan Stanley highlight MLCCs as entering a historic "volume-price dual increase" supercycle driven by AI. Goldman forecasts the AI server MLCC market to surge over fourfold from ~$1.4B in FY2025 to ~$5.8B in FY2030, a 34% CAGR. The core driver is a structural supply-demand imbalance. While AI server demand is projected to grow ~4.3x by 2030, industry capacity expands at only ~10% annually, constrained by internal production of equipment and materials. This is compounded by strong demand from electric vehicles. The shortage is evident, with lead times for high-end MLCCs exceeding 20 weeks. The price cycle has officially begun. Japanese leaders Murata and Taiyo Yuden have raised prices by 15-35% for AI server and automotive MLCCs since April, citing material costs. Japan's April export data confirms the trend, with MLCC export value up 28% year-over-year. Profit leverage is significant: Goldman estimates a mere 5% price increase could boost Murata's FY2027 operating profit by ~13% and Taiyo Yuden's by up to 37%. Morgan Stanley's teardown of Nvidia's upcoming Vera Rubin AI rack reveals another catalyst: the MLCC value per rack has skyrocketed 182% from the previous generation to ~$4,320, highlighting the component's growing importance. With demand set to ...

Editor's Note: 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 now turned their attention to MLCCs — the multilayer ceramic capacitors long regarded as ordinary passive components.

In AI servers, MLCCs are responsible for stabilizing current and filtering noise, serving as critical components to ensure high-speed chip operation. As Nvidia's new-generation rack architecture increases MLCC usage per rack, their value is rising rapidly. Goldman Sachs expects the AI server MLCC market to grow more than fourfold between 2025 and 2030, while industry capacity is increasing at an annual rate of just over 10%. This supply-demand mismatch is becoming the core variable driving the current market cycle.

More importantly, the price cycle has already begun. Japanese leaders Murata and Taiyo Yuden have initiated price hikes, and Japanese export data are also beginning to validate demand strength. For capital markets, the MLCC logic is not complex: demand comes from AI servers and high-end automobiles, supply expansion is constrained, and price increases can significantly amplify profit elasticity.

From chips to capacitors, pricing power within the AI supply chain is shifting to more segmented and hidden links. Whether MLCCs will become the "next memory chip" still depends on whether AI server demand continues to materialize. However, it is certain that this once-overlooked fundamental component has now reached the starting point of a new cycle of simultaneous volume and price growth.

Original Article:

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 focal points for capital, Wall Street giants Goldman Sachs and Morgan Stanley simultaneously pointed in their latest reports to a long-underestimated fundamental component: multilayer ceramic capacitors (MLCCs). Both institutions expect MLCCs to become the next key battleground for "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 is expected to surge from approximately ¥215 billion (about $1.4 billion) in FY2025 to about ¥920 billion (about $5.8 billion) in FY2030, an increase of over fourfold, representing a compound annual growth rate (CAGR) of 34%. Goldman Sachs stated bluntly 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."

MLCC: The 'Invisible Heart' Keeping AI Servers Running

An MLCC (Multi-layer Ceramic Capacitor) can be understood as an extremely miniaturized, ultra-fast-response charge/discharge unit. Unlike ordinary batteries that store large amounts of energy and release it slowly, MLCCs store very little energy but can complete charging and discharging within milliseconds or even shorter timeframes. Their core function is to smooth power fluctuations and filter noise: absorbing instantaneous voltage spikes or rapidly replenishing current during voltage dips, thereby providing stable current to sensitive chips and blocking electrical interference that could disrupt digital signals.

The operating characteristics of AI servers make MLCCs indispensable. When an AI model performs massive calculations, the processor's power consumption can spike dramatically within microseconds and then drop rapidly to near zero after the computation ends. The power supply system itself struggles to respond promptly to such drastic fluctuations. MLCCs are typically placed directly near AI chips, releasing energy instantaneously when power peaks occur to prevent server crashes. As Nvidia GPUs and other AI chips need to handle 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 expensive component in the AI server bill of materials (BOM), trailing only GPUs and memory. The overall MLCC market is currently about $15 billion, with the server-related market at around $1.3 billion, expanding at a CAGR of 80%. In contrast, demand growth in other application areas like automobiles and smartphones has noticeably slowed. Daiki Takayama expects MLCCs' cost share in the AI server BOM to gradually rise from about 0.5% currently to about 1%.

Structural Supply-Demand Imbalance: Annual Capacity Growth of Just 10%, Unable to Withstand Fourfold Demand Shock

The core factor sparking market attention is the severe structural supply-demand imbalance facing the MLCC industry. Goldman Sachs analyst Allen Chang explicitly stated that the annual capacity growth rate for the entire MLCC industry is only slightly above 10%. Moreover, as equipment and materials rely heavily on in-house production, expansion progress is constrained by internal engineering resources, making it difficult to accelerate significantly. However, the demand shock from AI servers is on a completely different scale. Goldman Sachs estimates that MLCC demand driven by AI servers will grow by approximately 4.3 times between FY2025 and FY2030.

Adding to market concerns, demand for high-voltage, high-capacitance MLCCs driven by automotive electrification remains robust, with per-vehicle MLCC usage continuing to rise. These two demand pillars—AI servers and electric vehicles—are jointly consuming the limited new capacity. This situation has led consumer electronics clients, despite a downturn in demand, to actively seek long-term supply agreements to hedge against future shortage risks.

Signals of current market tightness are emerging on multiple fronts: lead times for high-end MLCCs (high-capacity, high-voltage specifications) exceed 20 weeks; prices for low-capacity and consumer-grade MLCCs in spot and distribution channels have risen 20% to 40% due to stockpiling and double-ordering; prices for key raw materials like nickel and silver remain elevated, putting pressure on costs across various products.

Price Increase Cycle Officially Begins: Japanese Leaders Initiate Hikes, 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. Effective April 1 this year, Murata increased prices for MLCC products used in AI servers and high-end automotive applications by 15% to 35%. Taiyo Yuden has also notified customers of price adjustments across multiple product lines starting in May, involving MLCCs, inductors, RF devices, FBAR/SAW devices, and aluminum electrolytic capacitors, citing continuously rising costs of precious metals and other raw materials.

Trade statistics released by Japan's Ministry of Finance on May 28th verify this price trend at a macro level. The data shows that the average export price of MLCCs in April 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 financial reports of Japanese MLCC manufacturers: all companies affirmed that order momentum remains strong.

Examining the timeline of the entire AI supply chain, Goldman Sachs's analytical framework shows that MLCC price increases lag significantly behind other AI core components like DRAM, NAND memory, ABF substrates, and copper-clad laminate (CCL). Therefore, Goldman Sachs judges that among all AI components and materials, MLCCs have the longest runway and strongest sustainability for price increases. Goldman Sachs has revised its forecast for the year-over-year MLCC price change in 2026 from approximately 0% previously to 0% to +5%, emphasizing that actual future increases could far exceed this level.

Remarkable Profit Elasticity: 5% Price Hike Could Boost Operating Profit Up to 37%

For investors, the profit elasticity resulting 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 FY2027 operating profit by about 13% and Taiyo Yuden's operating profit by up to 37%.

Goldman Sachs expects Murata's FY2027 sales to reach ¥10.5 trillion (about $66 billion), a 13% year-over-year increase, and Taiyo Yuden's sales to reach ¥286 billion (about $1.8 billion), also a 13% year-over-year increase. Goldman Sachs maintains a "Buy" rating on Murata, Taiyo Yuden, and TDK. Its constructed Asia MLCC thematic stock portfolio has recently started to strengthen but still shows significant catch-up potential compared to other popular AI themes.

Morgan Stanley Disassembles Nvidia's New Rack: Rising Importance of Peripheral Components, MLCC Usage Soars 182%

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

The MLCC value within a single rack has increased from about $1,530 in the previous-generation GB300 era to about $4,320, a surge of 182%. Although the absolute dollar amount of MLCCs remains lower than that of GPUs, memory, and PCBs, their growth rate among peripheral components is exceptionally prominent.

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

Morgan Stanley's disassembly of the Nvidia Vera Rubin rack shows the following changes in key component values:

Market intelligence indicates that in the infrastructure arms race of the AI supercycle, the sequential rotation of supply bottlenecks has already spawned wave after wave of market winners. Goldman Sachs's latest assessment describes MLCCs as the "new memory chip"—a passive component sub-industry standing at the starting point of a cycle of simultaneous volume and price growth.

As exponential demand shocks from AI servers and Nvidia Rubin racks emerge, lead times for high-end MLCCs exceed 20 weeks, Japanese industry leaders initiate price hikes, and official export data remain robust. All signals point to the same conclusion: this AI-driven MLCC supercycle has only just begun.

Perguntas relacionadas

QAccording to the Goldman Sachs report, what is the projected growth of the AI server MLCC market from FY 2025 to FY 2030?

AAccording to Goldman Sachs, the AI server MLCC market is projected to grow more than fourfold, from approximately ¥215 billion in FY 2025 to about ¥920 billion in FY 2030.

QWhat is the primary function of MLCCs in AI servers, and why are they so critical?

AThe primary function of MLCCs in AI servers is to smooth power fluctuations and filter electrical noise. They provide stable power to sensitive chips by absorbing voltage spikes and rapidly supplementing current, which is critical for preventing system failures during the microsecond-level power surges characteristic of AI computation.

QWhat are the two main factors causing the structural supply-demand imbalance in the MLCC industry highlighted by Goldman Sachs?

AThe two main factors are: 1) A limited annual MLCC industry capacity growth rate of just over 10%, constrained by internal engineering resources for production equipment and materials. 2) Surging demand from two major pillars: AI servers (projected 4.3x growth from FY2025-2030) and the automotive electrification sector, which are jointly consuming the limited new capacity.

QBased on the Morgan Stanley analysis of Nvidia's new Vera Rubin VR200 rack, what was the percentage increase in MLCC value per rack compared to the previous generation?

AAccording to Morgan Stanley's teardown analysis, the MLCC value per rack in the new Nvidia Vera Rubin (VR200) rack increased by 182% compared to the previous generation (GB300 era), rising from about $1,530 to approximately $4,320.

QWhich companies were mentioned as leading the MLCC price increase cycle, and what profit elasticity does a 5% price hike potentially bring for one of them?

AThe Japanese companies Murata Manufacturing and Taiyo Yuden were mentioned as leading the MLCC price increase cycle. According to Goldman Sachs estimates, a 5% price hike could theoretically increase Murata's FY2027 operating profit by about 13% and Taiyo Yuden's operating profit by up to 37%.

Leituras Relacionadas

Seeking Alpha's Hot Article: Why Might the U.S. Stock Market Crash in June?

In a recent Seeking Alpha article, financial professor and analyst Damir Tokic argues that the US stock market may be poised for a significant crash in June 2026. The core thesis centers on a "mega-bubble" in equities, particularly within the technology sector, which has driven the S&P 500 to near-record valuations, with a Shiller P/E ratio exceeding 40—a level comparable to the 2000 dot-com bubble. Tokic identifies two primary catalysts for a potential collapse. First, he points to unsustainable market exuberance fueled by what he terms the "Trump Stimulus"—massive AI capital expenditure by tech giants, which he believes is politically driven and cannot last. Second, and more urgently, he highlights the escalating Iran war as a critical threat. The ongoing closure of the Strait of Hormuz has created a severe global energy supply crunch. Strategic petroleum reserves are projected to hit critically low operational levels by June, potentially causing oil prices to spike above $200 per barrel and triggering a severe, supply-driven inflationary shock. This scenario, Tokic warns, would force the Federal Reserve's hand. Despite currently maintaining a dovish bias, the Fed would likely be compelled to officially pivot to a hawkish stance at its June FOMC meeting to combat soaring inflation and bond yields. He contends that such a shift—or even a failure to act, which would destroy Fed credibility—could be the trigger that punctures the market bubble. The resulting downturn, he concludes, could rival the bear markets of 2000 and 2008, advising investors to prepare for a major correction.

marsbitHá 3m

Seeking Alpha's Hot Article: Why Might the U.S. Stock Market Crash in June?

marsbitHá 3m

AI PC Battle: Bet on the Toll Booth, Not the Camp

**Title:** The AI PC Battle: Don't Bet on Sides, Bet on the Tollbooth **Summary:** The AI PC competition is moving beyond simple "x86 vs. Arm" narratives. The core investment thesis should focus on identifying which players can sustain margins, cash flow, and pricing power throughout the upgrade cycle, rather than backing a particular architecture. The opportunity is analyzed in three layers: 1. **The Advanced Foundry Tollbooth:** TSMC is positioned to collect "tolls" regardless of which chip designer wins, due to its dominant ~70% share in advanced semiconductor manufacturing, which is essential for high-end AI PC chips. 2. **Compute & Platform Spillover:** AMD represents an offensive in the x86 CPU+GPU space, while NVIDIA leverages its GPU and CUDA software stack dominance. Both benefit from the demand for increased local AI compute. 3. **Architecture Diffusion & Turnaround Plays:** ARM and Intel offer potential for significant upside (elasticity), but investments here require stricter discipline due to higher execution risks and competitive challenges. The industry is transitioning from concept to shipment validation. While short-term forecasts for AI PC adoption have been revised down slightly due to tariffs and procurement delays, the long-term trend towards AI becoming a standard PC feature remains intact. The key driver for upgrade cycles will be whether compelling enterprise applications (e.g., privacy-sensitive computing, low-latency inference) emerge beyond consumer-focused features like meeting summarization. Investment strategy should prioritize companies with platform-level advantages and recurring revenue streams. TSMC offers high certainty as the foundational tollbooth. AMD presents a strong offensive play within the established ecosystem. ARM and Intel are higher-risk, higher-potential-reward turnaround bets. The report cautions against chasing short-term hype and emphasizes a disciplined, long-term approach focused on buying ecosystem strength and cash-flow certainty after market enthusiasm subsides. **Key Risks:** Underwhelming AI PC applications slowing upgrade cycles; slow improvement in Windows on Arm compatibility; macro/tariff impacts on PC demand; potential advanced node supply-demand mismatches affecting TSMC; high overall AI sector valuations making stocks vulnerable to a risk-off shift in markets.

marsbitHá 17m

AI PC Battle: Bet on the Toll Booth, Not the Camp

marsbitHá 17m

Ten-Thousand-Word Analysis: From $10 to $290, MRVL Wins the Entire AI Era by 'Not Making GPUs'

Marvell Technology's stock price surged from under $10 in 2016 to a record $290 in June 2026, fueled not by making GPUs, but by dominating AI infrastructure connectivity. This analysis argues the market misvalues MRVL as merely a smaller Broadcom in custom AI chips, overlooking its true, unique position. Marvell's core strength lies in enabling high-speed data flow for AI clusters through three interconnected businesses. First, it holds a commanding ~70% market share in high-speed optical DSPs (essential for data center light modules), a deep-moat business with accelerating growth. Second, its custom AI chip design business serves hyperscalers like AWS, Microsoft, and Google, with a significant revenue pipeline despite lower margins. Third, stable cash flows come from Ethernet switch chips and enterprise storage controllers. Together, they form a full-stack "AI data movement" platform. CEO Matt Murphy's transformative leadership since 2016, involving strategic divestments, key acquisitions (like Inphi for optical DSPs), and securing long-term agreements with major cloud providers, repositioned the company. A pivotal $2 billion strategic investment from NVIDIA in 2026 underscored Marvell's critical role in the AI ecosystem, particularly through collaborations like NVLink Fusion. While Marvell faces risks—including client concentration (losing the Amazon Trainium3 design), lower-margin business mix, competitive threats, insider selling, and complex supply chains—its fundamentals remain strong. The optical interconnect moat is widening with the acquisition of Celestial AI (photonics fabric), and financial metrics show accelerating revenue growth and operating leverage. With a PEG ratio suggesting undervaluation relative to its growth, the thesis is that the market undervalues Marvell's monopolistic position in AI "plumbing" while overemphasizing its competitive custom chip segment. The story transcends investing, symbolizing how in any complex system—from the internet to AI—the value of "connection" ultimately surpasses that of individual "nodes."

marsbitHá 47m

Ten-Thousand-Word Analysis: From $10 to $290, MRVL Wins the Entire AI Era by 'Not Making GPUs'

marsbitHá 47m

AI Relay Stations Spark Heated Debate on Zhihu: Behind Cheap Tokens, What Are Users Really Worried About?

A discussion on Zhihu about "AI relay stations" shifted the niche developer topic of "cheap tokens" into broader user awareness. Users moved beyond simply questioning the legitimacy of these services to focus on practical concerns: Where do cheap tokens truly come from? Is the model being accessed the real one? Can relay stations see prompts, code, and API keys? For occasional users, are the risks worth it? The core debate centered less on price and more on trust. A primary worry is model authenticity—the risk of "model swapping," where users paying for a premium model might be routed to a cheaper one, creating an information asymmetry. Others argued that cost comparisons matter; while cheaper than official pay-as-you-go APIs, relay stations may not be the lowest-cost option versus subscriptions, domestic models, or free tiers, making user needs assessment crucial. Speculation about token sources ranged from legitimate bulk discounts to gray-area methods like account sharing or exploiting regional pricing. This opacity makes risk assessment difficult for users. Data security emerged as a critical concern, especially for enterprise use. When processing sensitive information like code, contracts, or client data, the inability to verify a relay station's data handling, retention, or access policies poses significant compliance and confidentiality risks. The evolving consensus suggests relay stations can be used cautiously for low-sensitivity, disposable tasks (e.g., summarizing public info, simple translation). However, they should not be the default for sensitive, professional, or production workflows involving proprietary data, Agents, or automated systems. Recommendations include avoiding large prepayments, not relying on a single service, using test prompts to monitor quality, anonymizing data where possible, and keeping official channels as backups. Ultimately, the discussion framed tokens not just as a billing unit but as a measure of real cost encompassing price, model integrity, data security, and service stability. The popularity of relay stations highlights user demand for affordable access, but the debate underscores a key trade-off: the savings from cheap tokens may come at the price of trust, transparency, and control over one's data and AI experience.

marsbitHá 1h

AI Relay Stations Spark Heated Debate on Zhihu: Behind Cheap Tokens, What Are Users Really Worried About?

marsbitHá 1h

Trading

Spot
Futuros
活动图片