- Revenue rose over 53% from a year earlier and more than 10% from July.
- The world’s largest contract chipmaker has continued to benefit from strong demand for chips used in artificial intelligence applications.
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Follow your favorite stocksCREATE FREE ACCOUNTThe TSMC logo is displayed on a building in Hsinchu, Taiwan April 15, 2025. Ann Wang | ReutersTaiwan Semiconductor Manufacturing Co. reported record monthly revenue for August on Thursday, as demand for chips used in artificial intelligence applications remained strong.
The world's largest contract chipmaker posted revenue of $514.8 billion New Taiwan dollars ($16.35 billion) for last month, up 53.3% from a year earlier and 10.1% from July.
TSMC shares closed 0.61% lower on Thursday ahead of the revenue release.
The company's monthly revenue has now risen for four straight months.
During its second-quarter earnings call in July, TSMC said AI-related demand continued to be "extremely robust."
The Taiwanese tech giant reported a more than 77% year-on-year jump in second-quarter profit and forecast third-quarter revenue between $44.6 billion and $45.8 billion.
TSMC has maintained its dominance in the global foundry market, with a 72.5% market share in the second quarter, according to a data released by TrendForce Wednesday. Strong demand for AI server processors kept TSMC's advanced 5-, 4- and 3-nanometer capacity fully booked during the quarter, the research firm said.
Samsung Foundry ranked second with a 5.9% share, followed by China's SMIC at 5.4%.
The world's top 10 foundries posted record combined revenue of nearly $53.49 billion in the second quarter, driven in part by supply constraints for advanced processes used in AI and high-performance computing processors.
Separately, TSMC and Dutch chip equipment giant ASML this week announced an initiative to advance the industry's transition tonext-generation chipmaking technology.
TSMC said it plans to use ASML's High NA technology in large-scale manufacturing for advanced nodes starting in 2030, with adoption expected to increase as AI applications require more complex transistor architectures.
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