Samsung to Use TSMC Technology for Nvidia Next-Generation AI Chips
South Korean technology conglomerate Samsung Electronics plans to utilize manufacturing technology from foundry rival TSMC to produce base dies for Nvidia's next-generation artificial intelligence memory hardware. The cross-foundry collaboration marks the first time Samsung has partnered with the Taiwanese semiconductor manufacturer at the specialized high-bandwidth memory production level, Reuters reported.
Nvidia Common Base-Die Specification and Architecture
American graphics processing unit designer Nvidia requested that memory suppliers Samsung, SK Hynix, and Micron Technology adopt a unified base-die fabrication standard. Unveiled in August, Nvidia's proprietary NVHBM specification integrates a custom high-performance memory controller directly onto the base die to optimize throughput for advanced artificial intelligence workloads. Samsung Electronics will manufacture base dies for Nvidia custom memory hardware using advanced lithographic processes to meet strict computational bandwidth specifications. The architectural standard centers on NVHBM, an enterprise product family engineered to eliminate computational memory bottlenecks across hyperscale artificial intelligence data clusters. High-bandwidth memory architectures employ vertically stacked silicon dies to provide advanced processors with rapid access to massive data caches during demanding artificial intelligence workloads.
Foundry Rivalry and Dual-Track Production Strategy
Industry analysts note that Samsung Electronics and TSMC compete aggressively in leading-edge contract chipmaking, making collaborative fabrication an unprecedented structural shift. Samsung agreed to Nvidia's manufacturing terms following an internal operational review, while simultaneously maintaining proprietary in-house fabrication lines for conventional commodity HBM units. The South Korean chipmaker is also evaluating whether its internal semiconductor foundry could fabricate NVHBM base dies if market demand outstrips TSMC's manufacturing allocation.
Advanced 3-Nanometer Process and TSMC Financial Surge
Samsung Electronics plans to leverage TSMC's leading-edge 3-nanometer logic process node to fabricate the high-efficiency base dies required by Nvidia's accelerator designs. The supply agreement follows record quarterly financial results at TSMC, where third-quarter revenue reached 46.72 billion dollars, expanding 41.2 percent over the prior year. In its official quarterly disclosure, TSMC reported third-quarter net income reaching 763.06 billion New Taiwan dollars, representing a 68.7 percent year-over-year surge. TSMC Chief Financial Officer Wendell Huang attributed quarterly performance to robust customer demand for advanced lithography nodes across smartphones and artificial intelligence computing systems.
Industry Capacity Realignment and Three-Way Dynamics
South Korean peer SK Hynix has historically served as Nvidia's dominant high-bandwidth memory supplier across earlier hardware generations, having pioneered volume production. Samsung Executive Vice President Kim Taewoo noted that high-bandwidth memory is projected to consume nearly 30 percent of total DRAM wafer output by 2027. Kim said that expanding production for stacked memory modules directly competes for identical cleanroom wafer lines, potentially constraining conventional dynamic random-access memory supply.
Why a memory base die is a special case
High-bandwidth memory stacks combine layers of memory with a base die that helps connect them to a processor. Nvidia's requirements may push suppliers toward a common manufacturing standard for those base dies, but that does not mean Samsung is outsourcing all memory manufacturing to TSMC. The design of an AI accelerator, production of memory layers, logic fabrication and final advanced packaging are separate stages with different providers and capacity constraints.
A reported plan to use TSMC's process is therefore best understood as a supply-chain and engineering proposal until the companies confirm contracts, production volumes and qualification results. Nvidia must test reliability, performance and yields before a component becomes part of a shipping product. For customers, the larger issue is whether HBM supply can keep pace with accelerator demand, not which manufacturer wins a headline about one chiplet. Any specific process-node figure or production start date requires an attributable technical disclosure.