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TSMC reportedly weighs 20% CoWoS price increase as Nvidia Blackwell and Rubin chips put pressure on packaging capacity — equipment lead times stretch to eight months TSMC’s reported 20% CoWoS price hike comes as AI demand strains packaging capacity TSMC is weighing raising prices for its Chip on Wafer on Substrate (CoWoS) advanced packaging technology by as much as 20%, reports Trendforce, citing supply chain sources and local media. The increase reflects strained capacity amid AI demand and longer delivery times for chipmaking tools. Such a hike would be significant, as CoWoS is already one of the tightest links in the AI supply chain. TSMC has yet to confirm the report. CoWoS combines logic dies and high-bandwidth memory (HBM) stacks within a single package, which is how AI accelerators get the data bandwidth that demanding workloads require. Building these packages is only getting harder as chip designers cram in more compute and memory. Nvidia’s Blackwell already pairs two large GPU dies with eight HBM3E stacks, whereas the upcoming Rubin and Rubin Ultra are expected to push integration further, which will increase pressure on packaging and the supply chain that supports it. Testing is turning into another bottleneck. Blackwell reportedly takes three to four times longer to test than Nvidia’s previous-generation Hopper, and Rubin could need as much as seven times longer. Extended test cycles keep equipment occupied for longer, which makes it harder to increase output as demand grows. GPUs are not the only products competing for capacity either, as server CPUs and custom ASICs also need advanced packaging, adding more strain to an already crowded supply chain. Tools are also taking longer to arrive, as equipment lead times have reportedly stretched from three to six months to as long as eight months, making timely access to fab equipment increasingly important. As a result, TSMC has reportedly placed this year’s equipment orders at existing prices instead of negotiating discounts or extra features — a departure from its customary approach of using its purchasing power to secure better terms. Essentially, getting the tools on time now appears to matter more to the company than getting them cheaply. The squeeze echoes a report from September, which said that TSMC’s projected semiconductor equipment requirements had almost doubled in six months as the company expanded production to meet AI demand. Cliff Hou, deputy co-COO at TSMC, said that by July the company’s expected equipment needs had reached 1.9 times its original estimate as AI demand accelerated. “Compared with the pattern 30 years ago, we have never seen the demand increase that much, that frequency of changes,” Hou said at the time. TSMC is also trying to broaden its packaging supply chain. Earlier this month, GlobalFoundries agreed to produce silicon interposers for TSMC’s CoWoS in the U.S. under a five-year contract worth $2 billion, with production expected to ramp up in the first half of 2028. However, interposers are only one part of the packaging flow, so the agreement alone will not eliminate shortages. Higher costs are not limited to packaging. TSMC is reportedly considering broader price increases for 2027, with wafer prices on advanced process technologies expected to rise by 5% to 10%. Customers using 2nm and 3nm-class nodes could face the steepest hikes, whereas those seeking capacity beyond their original allocations may have to pay additional premiums, which could push some costs up by as much as 25%. Get Tom's Hardware's best news and in-depth reviews, straight to your inbox. Industry estimates cited by Trendforce put TSMC’s monthly capacity at over 106,000 wafers in 2026, with a target of 227,000 wafers in 2027 as the company works to keep pace with demand for increasingly complex AI processors. If both the packaging and wafer price increases materialize, the cost of AI hardware will likely climb further, and some of that will inevitably be passed down the chain. Follow Tom's Hardware on Google News, or add us as a preferred source, to get our latest news, analysis, & reviews in your feeds. Newton Gitonga is a tech journalist covering gadgets, PC hardware, AI, data centers, and the wider tech industry. His interest in technology started early, taking apart things around the house to see how they worked, often to his dad’s frustration. His curiosity sometimes got the better of him, including a few failed attempts to fix laptops, one of them a gifted Dell XPS. He has previously written for Notebookcheck, ZyCrypto, CoinCentral, and Crypto News Flash. - alan.campbell99 Do any consumer SoCs use this tech or is it generally limited to server CPUs, HPC and AI-related SoCs?Reply
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