The fabs that physically manufacture every AI chip — leading-edge and specialty nodes.
Sorted by one-month move. “Vs target” compares the current price with the mean analyst price target — a figure from analysts, not from us.
| Company | Price · todayThe latest closing price, and how far it moved from the previous close in dollars and percent. | 1 MonthPrice change since the last close on or before the same date one month ago — a calendar month, not 21 trading days. | 1 YearPrice change since the last close on or before the same date one year ago. | Vs targetHow far the price sits below the average of analysts’ published 12-month price targets. Negative means the price has already risen past that average.Analysts’ figures, not ours. Not a forecast we make or endorse. |
|---|---|---|---|---|
| UMCUnited Microelectronics | $24.61+$0.14 (+0.57%) | ▲ 33.2% | ▲ 258% | ▼ 25%$11 … $34 |
| TSMTaiwan Semiconductor | $434.67+$4.41 (+1.02%) | ▲ 5.4% | ▲ 64% | ▲ 27%$440 … $700 |
| GFSGlobalFoundries | $47.82+$1.98 (+4.32%) | ▼ 4.2% | ▲ 44% | ▲ 59%$55 … $140 |
As of close, Sep 18, 2026 · prices from Yahoo Finance
Data: daily close · Reporting, not recommendations · Not financial advice.
Foundries are the factories that physically manufacture chips other companies design. Leading-edge capacity — the most advanced process nodes — is concentrated in very few hands, which makes this one of the most strategically watched sectors on the map.
A foundry's constraint is capital and physics, not demand. Fabs cost tens of billions, take years to build, and depend on a short list of equipment makers. That lead time is why capacity decisions made today shape chip supply several years out.
What moves it: node transitions, utilisation rates, customer concentration, and government incentives for domestic manufacturing.
The Weekly Pulse covers Foundry (Chip Manufacturing) alongside every other sector — one email, Sunday, free.
The most advanced manufacturing processes available, usually described in nanometres. Leading-edge nodes deliver more performance per watt, which is why the largest AI chips compete for that capacity specifically.
Each generation costs more to develop than the last, so fewer firms can fund the step. Companies that fell behind on one node found the next one harder to fund, and the field narrowed with each cycle.
Older, cheaper processes still make the majority of chips in the world — power management, sensors, microcontrollers, automotive parts. An AI server needs many of these alongside its accelerators.