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Node · capacity · yield · price · geopolitics — weighted

Foundry Comparison Engine

No foundry wins on everything. Compare TSMC, Samsung, Intel Foundry, GlobalFoundries and others across capability, capacity, yield, price and geopolitical risk — weighted to what your product values.

01 · Foundries & priorities

Rate 0–100 each. Node/capacity/yield: higher better. Price/geo-risk: lower better (cheaper / safer).

FoundryNodeCap.YieldPrice↓Geo↓Score
0.782
0.731
0.761
0.736
Node capability20
Capacity20
Yield / maturity20
Price competitiveness20
Geopolitical risk20
Top foundry
TSMC
score 0.782
Ranking & criteria breakdown ↓
02 · Deep analysis

Foundry decision console

Weighted ranking
#1TSMC
0.782
#2Intel Foundry
0.761
#3GlobalFoundries
0.736
#4Samsung
0.731

Bars are the weighted, normalized scores. Shift the priority sliders above and watch the ranking — and the winner — change.

Top foundry
TSMC
Score
0.782
Foundries
4
Runner-up
Intel Foundry
Sourcing verdict

Under your weighting, TSMC ranks first with a 0.782 normalized score. It's a close call — only 2.7% ahead of Intel Foundry; qualitative factors (relationship, IP ecosystem) may decide.

Try the leading-edge, cost-driven and resilience-first presets — if the winner holds across them, it's robust; if it flips, your priorities are decisive. Geopolitical risk is now a first-class criterion, not a footnote.

Inform the geo-risk ratings via Taiwan Risk; check you're not recreating concentration in Vendor Concentration.

Why it matters

Why there's no single best foundry

Foundry choice is multi-criteria

No foundry wins on everything. The leader on node may be the worst on geopolitical risk; the cheapest may lag on capability. The right choice depends on which criteria your product weights.

Geopolitics is now a sourcing criterion

Location used to be a footnote; now it's central. Concentration in one region is a risk that buyers actively weight, driving demand for fabs in the US, Japan and Europe even at a cost premium.

Capability and cost pull apart

Leading-edge capacity is scarce and priced accordingly; mature-node capacity is cheaper and more available. A product that doesn't need the bleeding edge often shouldn't pay for it — match the foundry to the need.

Normalize, then weight

Node, capacity, price and risk are different scales and directions (some higher-better, some lower-better). Normalizing each to a best-in-class baseline before weighting is the only way to combine them honestly.

Field notes

Choosing where to build

Selecting a foundry used to be mostly a question of technology and price: who has the node you need, and what does the wafer cost. That calculus has broken open. The leader on capability may be the most geographically concentrated and therefore the riskiest; the cheapest option may lag a generation behind; the safest location may carry a cost or capability penalty. No foundry wins on every axis, which means the choice is irreducibly multi-criteria — and the right answer depends entirely on what your particular product values.

The newest and most consequential shift is that geopolitics has become a first-class sourcing criterion rather than a footnote. The concentration of leading-edge manufacturing in one region, the use of export controls as leverage, and the hard lessons of recent shortages have made buyers actively weight where a foundry operates. That demand is reshaping the industry, pulling capacity toward the US, Japan and Europe even at a premium, and it means a technically superior but concentrated foundry can lose to a slightly less advanced but safer one for strategic programs.

Capability and cost also pull apart in a way that punishes lazy choices. Leading-edge capacity is scarce and priced for it; mature-node capacity is cheaper and more available. A product that genuinely needs the bleeding edge should pay for it — but a great many products don't, and paying leading-edge prices for them wastes money and competes for supply that something else needs more. Matching the foundry to the product's actual node, volume, cost and risk requirements is the whole game.

The honest way to combine criteria on different scales and directions is to normalize each to a best-in-class baseline and then weight by your priorities. Use this engine to do exactly that: rate the foundries, set the weights that reflect your program, and read the ranking — then shift the weights to test how robust the winner is. Inform the geopolitical-risk ratings with the Taiwan and China risk calculators, and check that your foundry mix doesn't quietly recreate concentration in the Vendor Concentration calculator.

Foundry Comparison FAQs

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Trusted by Foundry Sourcing Teams

4.8
Based on 2,980 reviews

Normalize-then-weight across node, capacity, yield, price and geo-risk is exactly how I run a foundry RFQ evaluation. The presets nail it — leading-edge weighting puts TSMC top, resilience-first elevates Intel Foundry, cost-driven elevates GF. Watching the winner flip with the weights is the conversation I have with leadership. Indispensable.

A
Andrew Pell
Foundry sourcing lead
June 13, 2026

Finally geopolitical risk is a first-class criterion, not a footnote. Weighting it 40% for our strategic program changed the recommended foundry, and the tool makes that trade-off explicit and defensible. The capability-and-cost-pull-apart point is exactly why we don't pay for leading-edge on mature products. Excellent.

S
Sofia Andersson
Procurement strategy
May 21, 2026

Clean multi-criteria scoring with editable foundries and ratings. Adding emerging players and re-ranking was trivial. Would love an IP/PDK-ecosystem criterion, but the five quantitative ones cover the core decision and I add ecosystem qualitatively. Pairs naturally with the Taiwan/China risk tools for the geo ratings.

H
Hiro Tanaka
Supply strategy
April 2, 2026

The lower-is-better handling for price and geo-risk is done right — no manual inversion. Running our actual foundry shortlist with our weights produced a ranking the whole team could see the logic of. Chains naturally from the design tradeoff explorer. A full foundry evaluation in minutes. Fast and clear.

R
Rebecca Hall
Program management
January 12, 2026

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score = Σ(weight · normalized criterion) ÷ Σweights · node/cap/yield higher-better · price/geo-risk lower-better · Last reviewed: 2026-06