AI Server Single Rack Requires 600K MLCCs, Capacitor Costs Rise to Third-Largest Component
N.R. Finch
MLCCs have become the third-largest cost item in AI servers, behind only GPUs and memory chips. Goldman Sachs says the server MLCC segment is growing at 80% CAGR, yet industry capacity can expand by only ~10% a year — making capacitors potentially the AI component with the longest pricing upside runway.
A tiny capacitor — why is it suddenly the third-biggest AI server cost?
MLCCs — multilayer ceramic capacitors, ultra-small energy-storage components that respond in microseconds — now rank behind only GPUs and memory chips in server cost.
This means → a component once dismissed as "fractions of a cent apiece" is being repriced by AI compute demand.
A single advanced AI server rack needs up to 600,000 MLCCs placed right next to the chips. In plain terms = AI chips draw power in violent microsecond spikes that the main supply cannot match instantly; MLCCs act as tiny fast-discharge batteries glued beside the chip — they fill the power gap and filter electrical noise to prevent data corruption.
Demand growing at 80%, capacity at 10% — how big is the gap?
Goldman Sachs puts the total MLCC market at roughly $15 billion; the server segment accounts for about $1.3 billion and is expanding at an 80% CAGR.
But industry capacity can grow at most ~10% per year — equipment and critical materials must be built in-house, constrained by internal engineering resources.
This means → if AI servers keep absorbing new capacity, the supply-demand squeeze may not be a one- or two-quarter event but a structural gap lasting years.
Meanwhile, traditional demand from autos, smartphones, and PCs is softening — the MLCC industry is shifting from broad-based growth to an "AI eats all the incremental output" pattern.
MLCCs have barely risen in price — what does that actually tell us?
Goldman notes that memory (DRAM, NAND), ABF substrates, and copper-clad laminates (CCL) have all already repriced. MLCC is one of the last categories in the pricing cycle.
This means → its price upside runway is the longest among all AI components — the later the move starts, the larger the elastic potential.
In plain terms = the current "no price hike" is not a sign of slack supply; it means the pricing transmission chain has not yet reached MLCCs. Once it does, the upcycle could last longer than earlier movers.
Who captures this wave — three oligopolists, and TDK on a different track?
In the low-voltage, high-capacitance MLCCs needed around GPUs and ASICs, Murata, Samsung Electro-Mechanics (SEMCO), and Taiyo Yuden form an oligopoly and stand to benefit directly from both volume and price gains.
TDK currently lacks the technology to enter this segment; it is waiting for a joint materials R&D program with Japan Chemical Industry to deliver results.
TDK is, however, seeing strong orders for high-voltage, high-capacitance MLCCs used in power circuits — products that overlap heavily with EV automotive technology, potentially lifting factory utilization.
This reflects a key nuance: the MLCC market is not monolithic — low-voltage and high-voltage are two distinct technology tracks with very different competitive landscapes.
What to watch next — can MLCCs replicate the memory-chip pricing story?
Goldman estimates AI server demand will grow roughly 4.3× from FY2025 to FY2030.
Smartphone and PC clients, despite falling shipment volumes, have already begun seeking long-term MLCC contracts, further tightening available capacity.
In plain terms = whether MLCCs trace a memory-chip-style pricing curve comes down to a race: the speed at which AI demand absorbs new capacity vs. the pace at which the industry can expand. Right now, the demand side is running faster.
Content is for reference only, not financial advice.