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MLCC stands for multilayer ceramic capacitor. It is a tiny component that stores and releases electrical energy, helps keep voltage stable when a chip’s load changes, and filters unwanted electrical noise. AI servers use unusually large numbers of MLCCs because GPUs and other accelerators draw far more power, switch loads rapidly, and leave little room around their power pins for bulky components.
TAIYO YUDEN estimates that an AI server may contain roughly 10,000–20,000 MLCCs, compared with about 2,500 in a general server. That is a manufacturer estimate, not a universal count, but it illustrates the direction of modern data-center design: more power, more local decoupling, and higher capacitance in smaller packages.
What an MLCC is
A multilayer ceramic capacitor is made from alternating ceramic dielectric layers and metal electrodes, connected so the layers act in parallel. The stack provides useful capacitance in a compact package. “Multilayer” describes the internal construction; “ceramic” identifies the dielectric material.
Like any capacitor, an MLCC temporarily stores electrical energy and releases it when the circuit needs support. Murata describes four related functions:
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- Temporarily storing and discharging electricity.
- Absorbing noise on power or signal lines.
- Selecting or extracting signals at particular frequencies.
- Blocking direct current while allowing alternating-current components to pass.
In an AI server, the most important use is decoupling. A capacitor placed close to an integrated circuit supplies a brief local current reserve when the chip’s demand changes faster than the voltage-regulation system can respond. It also provides a low-impedance path for high-frequency noise, helping keep power rails within the limits expected by the processor and memory.
MLCCs are not batteries. Their energy storage is short-term and their job is to smooth fast electrical changes, not to power a server for minutes or hours.
Why AI servers need more MLCCs
Accelerators create larger and faster load changes
AI servers commonly combine several GPUs or purpose-built accelerators with high-speed memory and networking. During an inference or training workload, those devices can change their current demand very quickly. Every change travels through a power-delivery network that includes voltage-regulator modules, power planes, connectors and cables. Parasitic resistance and inductance in that network can produce voltage droop or ringing unless local capacitors provide a nearby current path.
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A free scan shows the junk files, broken settings and background clutter dragging Windows down - then fixes them in one click.Free scan · Windows 10 & 11Samsung Electro-Mechanics says AI servers can consume more than five to ten times the power of conventional servers and therefore require a higher number of MLCCs. This is the company’s 2025 comparison, not a measurement that applies to every AI machine. Nevertheless, the engineering relationship is straightforward: a higher-power processor generally needs more carefully distributed capacitance, and a faster-changing load makes placement and electrical characteristics more important.
Capacitance must be close to the chip
A capacitor located several centimeters away is not electrically equivalent to one beside the processor package. Trace length, vias, planes and package connections add equivalent series inductance (ESL). At high frequencies, that inductance limits how effectively a distant part can respond. Designers therefore distribute many MLCCs around GPU, CPU, memory and accelerator power pins instead of relying on one large capacitor elsewhere on the board.
AI boards also have severe area constraints. The region around a GPU is occupied by the package, memory, power stages, heat-transfer hardware and high-speed interconnects. Compact, high-capacitance MLCCs let engineers add charge storage without consuming as much surface area as larger parts. Samsung specifically points to limited mounting space around GPUs as a reason for using small, high-capacitance products.
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More power stages mean more capacitor locations
Capacitors are used throughout the power path, not only at the processor pins. A typical data-center system may include an incoming power supply unit (PSU), intermediate bus converters (IBCs), board-level voltage regulators and point-of-load stages close to each accelerator. Each stage has its own input and output filtering requirements, so an increase in rack and server power can increase MLCC demand in several places at once.
TDK’s July 2026 application material discusses MLCC requirements across PSU and IBC stages as well as processor-side conversion. The exact circuit topology varies by server generation, but the principle is consistent: every conversion stage must control ripple and respond to changing load current.
How many MLCCs are in an AI server?
TAIYO YUDEN’s 2025 MLCC product-strategy presentation gives one of the clearest published comparisons:
| System type | Published estimate | How to interpret it |
|---|---|---|
| AI server | Approximately 10,000–20,000 MLCCs | TAIYO YUDEN estimate; the count depends on the server design and what assemblies are included. |
| General server | Approximately 2,500 MLCCs | TAIYO YUDEN estimate for comparison, not an audited industry average. |
These figures should not be multiplied into a data-center total without a sourced server count and a definition of scope. A “server” might mean a motherboard, a complete chassis, or a system containing accelerator and networking boards. Different GPU counts, memory configurations, power architectures and reliability targets can all change the bill of materials. TAIYO YUDEN’s published material does not establish an independent, industry-wide average.
The useful conclusion is directional rather than arithmetic: an accelerator-heavy server can require several times as many MLCCs as a conventional server because it needs more capacitance, more power-conversion stages and more locations where that capacitance must be placed.
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The move toward higher capacitance in smaller packages
Manufacturers are responding by increasing capacitance while keeping the package footprint small. The following examples are published product announcements or solution examples, not a universal AI-server bill of materials.
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| Manufacturer example | Capacitance and size | Published context |
|---|---|---|
| Murata Manufacturing | 47 μF in 0402-inch size (1.0 × 0.5 mm) | Mass-production announcement in 2025; described as the world’s first mass production of this size-capacitance combination. |
| TAIYO YUDEN | 22 μF in 1005 size (1.0 × 0.5 mm) | Embeddable MLCC commercialized and mass-produced in 2025 for decoupling on AI-server IC power lines. |
| TAIYO YUDEN solution examples | 10 μF at 0.6 × 0.3 mm; 47 μF at 1.0 × 0.5 mm; 100 μF at 1.6 × 0.8 mm | Compact examples shown in the company’s AI-server solution material. |
| Samsung Electro-Mechanics examples | 47 μF in 0402-inch and 100 μF in 0603-inch packages | Examples cited for high-temperature AI-server applications. |
A package code such as 0402 refers to a standard footprint convention, not a guarantee that two parts are interchangeable. Capacitance can fall with applied DC voltage, and the permissible voltage, dielectric formulation, temperature rating, aging behavior and mechanical construction all matter. A part that fits the same land pattern may still be unsuitable electrically or for the expected service life.
Where MLCCs work in the power system
At the accelerator and memory power pins
The smallest, fastest transients are handled by decoupling capacitors placed immediately around the IC package or in an embedded layer of the circuit board. Their short connection path minimizes ESL. Several values may be used together so that different parts of the network respond effectively over different frequency ranges.
At voltage-regulator inputs and outputs
Voltage-regulator modules convert a higher distribution voltage to the low voltages required by GPUs, CPUs and memory. MLCCs on the input side reduce switching noise presented to the converter; output capacitors help the regulator maintain its target voltage during load steps and suppress ripple. The regulator’s control loop, switching frequency and stability requirements determine the acceptable capacitance and impedance.
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Higher-power servers place greater demands on the PSU and the intermediate bus that feeds board-level converters. Filtering at these stages limits ripple and electromagnetic interference before power reaches the accelerator boards. The parts used here may have different voltage, capacitance and package requirements from the tiny capacitors beside an IC, even though all are MLCCs.
How engineers select an MLCC
Counting parts is less useful than matching each part to its electrical and mechanical job. Engineers normally evaluate these factors together:
| Selection factor | Why it matters |
|---|---|
| Capacitance under operating bias | The marked value is not always the value available at the circuit’s DC voltage. Voltage derating and temperature effects must be included in the calculation. |
| Voltage rating | The rating must exceed the circuit’s maximum operating and transient voltage with an appropriate safety margin. |
| ESR and ESL | Equivalent series resistance affects ripple loss and heating; equivalent series inductance limits high-frequency response and is strongly influenced by placement. |
| Temperature range | Parts near GPUs, voltage regulators and heat sinks may face elevated temperatures. Capacitance stability, aging and reliability must be specified for that environment. |
| Package and footprint | The package must fit the available board area and assembly process while meeting mechanical-strength and thermal requirements. |
| Surface mount versus embedded construction | Surface-mounted parts are placed on the board exterior; embedded capacitors can be built into board layers to shorten the electrical path when surface area is scarce. |
| Reliability and failure requirements | Data-center hardware is expected to operate continuously, so qualification, process control and allowable failure rates influence the approved component list. |
These criteria explain why a generic assortment of ceramic capacitors is not a server upgrade or a repair substitute. The system designer must verify the dielectric type, voltage rating, effective capacitance, thermal behavior, dimensions and mounting rules against the exact power network.
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Why one large capacitor cannot simply replace many small ones
A larger capacitor may provide substantial low-frequency energy storage, but it cannot automatically replace capacitors distributed around a high-speed processor. Distance adds inductance, and different stages of the power network operate over different frequency ranges. Multiple small MLCCs can be placed at many power pins, share ripple current and fit into gaps that a single large component cannot occupy.
Parallel placement also gives designers flexibility to tune total capacitance and impedance. The required combination depends on the regulator, processor package, board stack-up and transient specification. Increasing capacitance without checking control-loop stability, inrush behavior or voltage derating can create a new problem rather than solve the original one.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.What the published numbers do—and do not—tell you
The 10,000–20,000 estimate is best used to communicate scale. It does not tell an operator how many capacitors a particular rack contains, because a rack may include different server models, switches, storage devices and power shelves. Nor does it show that every MLCC has the same capacitance or role.
Likewise, the “five to ten times” power comparison from Samsung Electro-Mechanics is a company-published description of AI servers versus conventional servers. Actual consumption varies with accelerator model, workload, utilization, cooling, memory and power-management settings. It is evidence of the pressure on power delivery, not a universal specification.
The 2025 high-capacitance product announcements from Murata and TAIYO YUDEN demonstrate what manufacturers are trying to achieve: more usable capacitance in less area. They should be read as technology examples. The correct component for a production board still comes from that board’s electrical, thermal, mechanical and reliability requirements.
Implications for data-center builders and operators
For a builder, the growth in MLCC count is one visible consequence of rising power density. Component placement, board-layer design, converter selection and thermal layout must be planned together rather than treated as separate tasks. Procurement teams also need lifecycle control because a substitute with the same nominal capacitance and package may have different DC-bias, temperature or reliability characteristics.
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For an operator, a high MLCC count is not a user-serviceable performance upgrade. Do not add capacitors to a server board or replace them with parts chosen only by printed capacitance. Board-level changes require the original design files, approved parts and controlled assembly and inspection. When a server shows a power fault, the appropriate action is to follow the platform manufacturer’s service procedure or involve a qualified board-repair specialist.
Common misconceptions
“MLCC” means one standard part
MLCC is a component family, not a single specification. Two parts can share the same package and nominal capacitance while differing in voltage rating, dielectric, temperature behavior, ESR, ESL and reliability qualification.
More MLCCs always means a better server
Quantity follows the power architecture. Adding parts without modeling impedance, regulator stability, thermal stress and layout can be ineffective or harmful. The goal is the required impedance and transient response at each circuit location, not the largest possible count.
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1Repair Windows errors before they cause bigger problems2Scan for outdated or missing drivers - takes under a minute3Clear out junk files and repair common Windows errorsThe published AI-server count applies to every data center
It does not. TAIYO YUDEN’s 10,000–20,000 figure is an estimate for an AI server in the context of its product strategy presentation. Server generations and configurations differ, and no independent industry-wide total is established by that figure.
Bottom line
MLCCs are the small, fast energy buffers and noise-control components that let complex power systems feed demanding chips reliably. AI data centers need so many because accelerators consume much more power, change load quickly, and have very little room for decoupling near their power pins. The industry’s response is to distribute more capacitors through the power path while making individual parts smaller and capable of higher capacitance; the exact count and part selection remain specific to each server design.
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