Dicing the wafer
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Chip economics · Explainer 10

What a chip costs

A chip's price starts with three numbers: how many fit on a wafer, how many of those work, and what the wafer cost. This page counts the first two live and lets you set the third.

300 mmone wafer, 707 cm²
814 mm²one NVIDIA H100 die
~$30,000reported for a TSMC N2 wafer, 2025
Scene: a 300 mm wafer cut into dies of 120 mm², and killer defects landing on it; each die a defect lands on turns red. The wafer, its dies and the €2 coin beside it are to scale; the defects are drawn far larger than they are. No foundry we read publishes a price per wafer: the N2 figure is a press report, and every price on this page is one you can change. Wafer size: SEMI; its area is our arithmetic. Die size: NVIDIA. N2 price: TrendForce and DIGITIMES. All sources are listed at the end.
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01 · Dies per wafer

Squares on a circle.

Chips are rectangles; wafers are round. Every die has to fit whole inside the usable area, so the edge of the wafer is always lost, and the squares it cuts through, hatched here, are thrown away. The bigger the die, the more of the edge it cannot use.

The coin is a €2 coin, 25.75 mm across. The largest die one exposure can print is 26 × 33 mm, 858 mm²; NVIDIA's H100 die fills 95% of it.

Whole dies
616
Cut by the edge
0
Wafer area used
0%
Die side, square
0 mm
The textbook estimate
about 601
The count is geometry, done live: square dies on a grid, the best of four grid positions kept. Our assumptions: dies stay 3 mm clear of the edge and 0.1 mm apart for the saw, the pair CSET used in 2020; DISCO's own example uses 2 mm and 50 µm. The estimate is π(d/2)²/S − πd/√(2S), as University College Cork's course slides give it, with d the usable diameter and S one die with its saw lane. Die: NVIDIA. Exposure field: Nikon and Canon; its area and the share are our arithmetic. Coin: European Central Bank.
02 · Yield

Where a speck lands, a chip dies.

A killer defect is any physical flaw that makes a circuit fail. A fab counts them as defect density, D0, killer defects per square centimetre. In the simplest picture they land at random, so a small die usually slips between them and a big die is a big target.

The simplest model, named after Poisson, says the share of dies with no killer defect is e−A·D₀ for a die of area A. Scatter a wafer and set it beside the model.

Good dies
0
Whole dies
0
Yield, this wafer
0%
Yield, Poisson
0%
Killer defects on this wafer
0
Defect and model: Robert Leachman's yield notes (UC Berkeley, 2014). For scale, AnandTech (August 2020): TSMC's N7 reached 0.09 defects per cm² three quarters after volume production started, as TSMC announced in 2019, and a TSMC chart put N5 at about 0.10 to 0.11 during its 2020 ramp. We found no reported number for N3 or N2. Each wafer here is a seeded random draw, so the same settings give the same wafer.
03 · Defects cluster

Clumps kill fewer chips.

Real defects tend to cluster. Several defects in one die kill it only once, so a wafer whose defects clump keeps more good dies than one with the same number spread out. That is why the Poisson model tends to underestimate the yield of large dies.

Both wafers carry the same number of killer defects. Murphy's model, from Bell Labs in 1964, lets the density vary across the wafer: set a large die and a high D₀, and watch the two models part. The clustered wafer is our own picture of clumping, not what Murphy's model predicts, so its count and Murphy's yield need not agree.

Good dies, at random
0
Good dies, clustered
0
Yield, Poisson
0%
Yield, Murphy
0%
Clustering and both models: Leachman (UC Berkeley, 2014), citing B. T. Murphy in the Proceedings of the IEEE (1964); Murphy's model is ((1 − e−A·D₀) ÷ A·D₀)². A University of Maryland course page notes that some authors find the simple Poisson formula too pessimistic for single chips. The clumps are ours: groups of about 8 defects, each spread about 5 mm.
04 · Cost per good die

Big dies pay twice.

Divide the wafer price by the good dies on it. A die eight times bigger costs more than eight times as much: fewer fit, and more of them are hit. The white plates show where each column would stop if cost grew with area alone.

No foundry we read publishes a price per wafer, so set your own. It starts at $20,000, the price of a 3 nm wafer in TrendForce's summary of an EE Times report (October 2025).

A 100 mm² die
$0
An 814 mm² die
$0
Area ratio
0×
Cost ratio
0×

TSMC's revenue per wafer is its revenue over the wafers it shipped, our arithmetic: US$6,983 in 2024 and US$8,161 in 2025. GlobalFoundries: US$3,178 in 2024. Not a price TSMC states: it blends every node, and TSMC's revenue holds more than wafers.

Silicon only, at the price you set. As reported: N2 about $30,000 (TrendForce citing Investor.com, October 2025; DIGITIMES, August 2025); N3 about $20,000 (TrendForce, summarizing an EE Times report about a rumour) or $25,000 to $27,000 (Investor.com, via TrendForce, the same article); N4 and N5 "believed to cost around $15,000" (Tom's Hardware, October 2024). TSMC's 2025 revenue, US$122.42 billion, over 15.0 million 12-inch equivalent wafers: its annual reports; GlobalFoundries: its 2024 results. On top of the silicon come chip design and assembly, test and packaging (CSET, 2020). Epoch AI estimates the B200's variable cost of production: memory and advanced packaging about two-thirds, NVIDIA's logic die under 15%; it leaves out fixed costs such as R&D (December 2025).
05 · Chiplets

A big die can be cut into pieces.

Split a big design into chiplets joined in the package, and a defect scraps a quarter of the silicon. The price is extra silicon for the links between them and a package that joins them, the subject of Chips on chips.

AMD made this case for its EPYC server processor at Hot Chips in 2017: four dies of 213 mm², 852 mm² in all, against one hypothetical die of about 777 mm², at 0.59 times the cost by AMD's own yield model. Here is that example at your settings.

Yield, one die
0%
Yield, each chiplet
0%
Silicon, one die
$0
Silicon, four chiplets
$0
Silicon saved
0%
Wafer price
$20,000
AMD's figures: its Hot Chips 29 slides (August 2017), about 10% more silicon for the four, and the cost ratio from AMD's internal yield model, on historical defect density data for mature technologies. The overhead starts at 9.7%, AMD's 852 against 777 mm², our arithmetic. The arithmetic assumes each chiplet is tested before it is joined; Intel Foundry describes test services that "identify and deliver known good die before final assembly". The rest is our arithmetic, silicon only, with the wafer price and yield model you set in chapter 04.
06 · Where to go next

Geometry, luck and a price tag.

Everything a fab does to lower defect density, and everything a designer does to shrink a die, shows up in the cost of one good chip. This is your wafer from chapter 02.

Named on this page, and on this record: AMD, GlobalFoundries, Intel, NVIDIA and TSMC; Canon and Nikon, which make lithography scanners; and DISCO, which makes dicing saws. Where the wafers are made: the fab map.

Counts, yields and costs on this page are our arithmetic, done live from your settings.