In April this year, SK Hynix announced signing a Memorandum of Understanding (MOU) with Taiwan Semiconductor Manufacturing Company (TSMC) for close collaboration on next-generation HBM product manufacturing and advanced packaging technologies that strengthen the integration of HBM with logic layers. The partnership involves joint development of sixth-generation HBM products, namely HBM4, with TSMC responsible for producing the base dies. Unlike previous HBM products, HBM4 will feature custom designs, and NVIDIA plans to utilize them in next-generation AI accelerators based on the Rubin architecture GPU next year.

According to TrendForce reports, rumors suggest that NVIDIA has begun developing its own HBM base dies, creating ripples throughout the supply chain as this could potentially reshape the next-generation HBM landscape. NVIDIA's self-developed HBM base dies are expected to be manufactured using 3nm process technology, with plans for small-scale trial production in the second half of 2027.

Analysts point out that this move demonstrates NVIDIA's advancement toward custom HBM design base dies, potentially integrating some GPU functions into the base dies to enhance overall performance of both HBM and GPU. NVIDIA may initially adopt standard HBM4E supplied by SK Hynix in the first half of 2027, then transition to its own custom HBM4E design from the second half of 2027 through 2028.

Currently, SK Hynix dominates the HBM market with internal chip design leadership. However, achieving I/O speeds above 10Gbps requires support from advanced process nodes, such as TSMC's 12nm or smaller processes for chip manufacturing. Due to memory manufacturers' lack of complex base chip IP and ASIC design capabilities, NVIDIA needs to develop dedicated HBM base dies, leveraging NVLink Fusion to provide more modular solutions and strengthen ecosystem control.

Industry sources reveal that NVIDIA will integrate UCIe interfaces into HBM4 to enable direct GPU-CPU connections, which will significantly increase design complexity. The biggest beneficiary could be TSMC, whose close collaboration with major chip design companies, combined with continuously improving process technologies, positions it at the core of rapid artificial intelligence development.