# Samsung Adopts TSMC's 3nm Technology for Nvidia's AI Memory Chips

> In a groundbreaking collaboration, Samsung will use TSMC's 3nm technology to produce Nvidia's next-gen HBM chips, marking a significant shift in the competitive semiconductor landscape.

**Source**: yugatech.com | **Published**: 2026-10-19 | **Type**: article

## Key Facts

- Samsung's use of TSMC's 3nm tech reveals a shift in semiconductor collaboration dynamics.
- Nvidia's NVHBM standardizes memory architecture, enhancing supplier flexibility and competitiveness.
- TSMC's expanded role in Nvidia's supply chain could threaten Samsung's market positioning in AI.
- Growing HBM demand signals financial opportunities for memory suppliers amid AI hardware expansion.
- Samsung's potential foundry shift indicates strategic adaptability in response to production capacity needs.

## Summary

Samsung Electronics is set to leverage Taiwan Semiconductor Manufacturing Company’s (TSMC) 3-nanometer manufacturing process to produce the base dies for Nvidia’s next-generation high-bandwidth memory (HBM) chips. This collaboration, reported by the Seoul Economic Daily, marks a significant development in the semiconductor industry, as it represents the first instance of Samsung and TSMC working together in the HBM manufacturing sector, traditionally dominated by fierce competition.

The strategic partnership is driven by Nvidia’s evolving needs in the AI hardware space. The company has approached Samsung, SK Hynix, and Micron Technology to utilize TSMC’s advanced 3nm process for the base dies, while employing sixth-generation DRAM technology for the core dies of the memory chips. This dual approach is part of Nvidia’s custom memory technology, NVHBM, unveiled in August, which integrates Nvidia’s proprietary memory controller into the base die. The intent is to standardize the architecture across various memory suppliers, enhancing compatibility and performance.

By relocating the memory controller to the base die, Nvidia aims to optimize space on its graphics processors, allowing for additional computing circuits. This design shift not only streamlines Nvidia’s manufacturing process but also facilitates collaboration with multiple memory manufacturers, ensuring a more uniform architecture. Samsung will continue to produce the memory layers while utilizing TSMC’s process for the base die, a move that underscores the growing interdependence in the semiconductor supply chain.

This collaboration arrives at a time when demand for high-bandwidth memory is surging, driven by the increasing adoption of AI accelerators and data center hardware. HBM is particularly crucial for AI workloads, as it enables rapid access to the vast data sets processed by advanced chips. For Nvidia, this arrangement could mean a more robust supply chain, allowing the company to source memory from various suppliers without sacrificing architectural consistency.

For Samsung, this partnership presents a dual opportunity. While it will rely on a competing foundry for part of the manufacturing process, it also positions itself as a key supplier for Nvidia’s next-generation AI hardware. Despite this collaboration, Samsung plans to maintain its own manufacturing methodologies for standard HBM products and custom memory solutions for other clients, ensuring it retains a competitive edge in the broader market.

The implications of this partnership extend beyond immediate manufacturing capabilities. TSMC’s expanded role in Nvidia’s supply chain could redefine competitive dynamics within the semiconductor industry. As Nvidia seeks to diversify its memory sourcing, the collaboration could prompt other players in the market to explore similar partnerships to enhance their offerings and capabilities.

Looking ahead, the semiconductor landscape may witness increased collaboration among competitors, driven by the need for advanced technologies to meet the demands of AI and data-intensive applications. This shift could lead to a more integrated supply chain, where companies prioritize innovation and efficiency over traditional rivalries. As the industry evolves, the ability to adapt and forge strategic alliances will be crucial for maintaining market relevance and competitiveness.

## Entities

- **Companies**: Samsung Electronics, TSMC, Nvidia, SK Hynix, Micron Technology
- **Products**: high-bandwidth memory (HBM), sixth-generation DRAM, NVHBM
- **Technologies**: 3-nanometer manufacturing process

## Key Concepts

collaboration between competitors, AI hardware, memory manufacturing, semiconductor industry, custom memory technology, foundry business, high-bandwidth memory demand, data center hardware

## Definitions

- **high-bandwidth memory (HBM)**: A type of memory that provides high-speed access to large amounts of data, essential for AI workloads.
- **3-nanometer manufacturing process**: A semiconductor manufacturing technology that allows for smaller, more efficient chips.
- **NVHBM**: Nvidia's custom high-bandwidth memory technology that integrates its memory controller into the base die.
- **foundry business**: A business model where a company manufactures chips for other companies, often using their own technology.
- **sixth-generation DRAM**: The latest generation of dynamic random-access memory technology used in modern computing.

## Use Cases

- Manufacturing custom high-bandwidth memory chips for AI hardware
- Standardizing memory architecture across different suppliers
- Enhancing graphics processors by freeing up space for additional circuits
- Sourcing memory from multiple suppliers with a consistent design
- Expanding TSMC's role in Nvidia's AI supply chain

## Frequently Asked Questions

**Why is Samsung using TSMC's technology?**

Samsung is reportedly using TSMC's 3nm process to produce base dies for Nvidia's next-gen memory chips, marking a collaboration between two major semiconductor rivals.

**What is NVHBM?**

NVHBM stands for Nvidia's custom high-bandwidth memory technology, which integrates a memory controller into the base die to enhance performance and standardization.

**How does this collaboration affect Nvidia's supply chain?**

The collaboration allows Nvidia to source memory from multiple suppliers while maintaining a consistent design, potentially expanding TSMC's role in Nvidia's AI supply chain.

**What are the implications for Samsung's foundry business?**

Samsung is assessing whether its own foundry could manufacture NVHBM base dies if TSMC's capacity is insufficient, indicating a strategic move to leverage its manufacturing capabilities.

**What is the significance of high-bandwidth memory in AI?**

High-bandwidth memory is crucial for AI workloads as it provides the necessary speed and access to large datasets, which are essential for efficient processing in AI applications.

## Links

- [Read on Welcome.AI](https://welcome.ai/content/samsung-adopts-tsmcs-3nm-technology-for-nvidias-ai-memory-chips)
- [Original source](https://www.yugatech.com/news/samsung-to-use-tsmcs-3nm-technology-for-nvidias-next-gen-ai-memory-chips/)
- [NVIDIA](https://welcome.ai/company/nvidia): Featured company

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Source: Welcome.AI | https://welcome.ai/content/samsung-adopts-tsmcs-3nm-technology-for-nvidias-ai-memory-chips