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News3 min read·2026-10-20

NVIDIA Reportedly Standardizes NVHBM Base Dies on TSMC 3nm, Samsung Accepts Partial Outsourcing

NVIDIA has reportedly required Samsung, SK Hynix and Micron to manufacture the base dies of their NVHBM custom memory on TSMC's 3nm process, reducing multi-supplier validation costs. Samsung had long emphasized internal integration from memory to base die as a core competitive advantage; its acceptance of TSMC foundry for NVHBM marks a shift where chip designers now influence manufacturing choices at the process-node level.

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2026-10-19 08:25 GMT+8

NVIDIA is redefining who decides which process node gets used in the AI semiconductor supply chain. According to reports, NVIDIA has asked Samsung Electronics, SK Hynix and Micron to have the base dies—which assist computation beneath the HBM stack—for their next-generation custom memory NVHBM manufactured uniformly on TSMC's 3nm process. The core logic is standardization: when a single GPU must be compatible with HBM products from multiple vendors, verifying each base die's interface and power characteristics individually is extremely costly, while locking all base dies to the same process node dramatically reduces adaptation work.

Samsung had long emphasized its ability to integrate everything from memory to base die in-house as a core competitive strength. Its acceptance of TSMC foundry for NVHBM base dies represents a significant departure from that strategy.

However, this does not mean Samsung is overhauling its entire HBM approach. Samsung plans to continue using its own foundry for the base dies of its proprietary HBM4, HBM4E and products destined for other customers.

TSMC's record third-quarter 2026 results provide context for this landscape. Revenue reached NT$1.4942 trillion and net profit NT$763.1 billion, up roughly 51% and 69% year-on-year respectively, marking the sixth consecutive quarter of record earnings.

The engine behind those results is advanced process nodes. 2nm, which entered mass production at the end of last year, already accounts for 8% of wafer revenue; combined with 3nm and 5nm, advanced processes make up 69% of the total.

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TSMC plans to more than double its 2nm-series capacity by 2027. Because advanced chips are designed around a specific manufacturing process from the outset, switching foundry partners after design is prohibitively expensive. Securing capacity early means the next generation of AI chips will naturally remain within TSMC's ecosystem.

In foundry market share, TrendForce data shows TSMC held 72.5% and Samsung only 5.9% in Q2 2026. Samsung is seeking breakthroughs through its Taylor, Texas fab ramp-up and new 2nm orders—last year it secured a roughly $16.5 billion contract with Tesla. Yet the sheer growth in AI chip demand means even TSMC's aggressive expansion cannot absorb every customer, leaving room for second-source suppliers like Samsung.

The deeper shift lies in supply-chain power structure. As AI accelerators evolve from single chips into massive systems, the influence of design firms like NVIDIA now extends to memory manufacturing methods and foundry selection. Previously, Samsung and SK Hynix each optimized their own HBM independently; now GPU, memory, logic chips and packaging must be co-optimized within one design framework.

In this process, competition and cooperation coexist: Samsung and TSMC compete fiercely in the foundry market, yet enter the same supply chain for NVHBM. Part of the explanation for TSMC's record earnings is precisely this—the more advanced process becomes the common substrate for AI semiconductors, the more competitors' products embed TSMC's manufacturing technology.

Sources

  • 原始出处thecore.media↗
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