[News] CoWoS Production Surges at TSMC, UMC, Amkor, and ASE Hasten to Catch Up

According to a report by Taiwan’s Commercial Times, JPMorgan’s latest analysis reveals that AI demand will remain robust in the second half of the year. Encouragingly, TSMC’s CoWoS capacity expansion progress is set to exceed expectations, with production capacity projected to reach 28,000 to 30,000 wafers per month by the end of next year.

The trajectory of CoWoS capacity expansion is anticipated to accelerate notably in the latter half of 2024. This trend isn’t limited to TSMC alone; other players outside the TSMC are also actively expanding their CoWoS-like production capabilities to meet the soaring demands of AI applications.

Gokul Hariharan, Head of Research for JPMorgan Taiwan, highlighted that industry surveys indicate strong and unabated AI demand in the latter half of the year. Shortages amounting to 20% to 30% are observed with CoWoS capacity being a key bottleneck and high-bandwidth memory (HBM) also facing supply shortages.

JPMorgan’s estimates indicate that Nvidia will account for 60% of the overall CoWoS demand in 2023. TSMC is expected to produce around 1.8 to 1.9 million sets of H100 chips, followed by significant demand from Broadcom, AWS’ Inferentia chips, and Xilinx. Looking ahead to 2024, TSMC’s continuous capacity expansion is projected to supply Nvidia with approximately 4.1 to 4.2 million sets of H100 chips.

Apart from TSMC’s proactive expansion of CoWoS capacity, Hariharan predicts that other assembly and test facilities are also accelerating their expansion of CoWoS-like capacities.

For instance, UMC is preparing to have a monthly capacity of 5,000 to 6,000 wafers for the interposer layer by the latter half of 2024. Amkor is expected to provide a certain capacity for chip-on-wafer stacking technology, and ASE Group will offer chip-on-substrate bonding capacity. However, these additional capacities might face challenges in ramping up production for the latest products like H100, potentially focusing more on older-generation products like A100 and A800.

(Photo credit: TSMC)