321-Layer QLC NAND Development Completed, Mass Production Begins
Full-Scale Targeting of 'eSSD for AI Servers' Demand Starting Next Year

SK Hynix has begun mass production of a new NAND flash product optimized for ultra-high-capacity enterprise solid-state drives (eSSD) used in artificial intelligence (AI) servers. The core of NAND competitiveness lies in stacking technology, which increases data capacity by vertically stacking cells. For this product, SK Hynix has applied the "highest density ever achieved." The company explained that it has not only built a high-capacity, high-performance portfolio suitable for AI server demand but also secured cost competitiveness.


On August 25, SK Hynix announced that it has completed the development of a 321-layer 2TB Quad-Level Cell (QLC) NAND product and has started mass production. NAND is a type of non-volatile memory semiconductor that retains data even when the power is off. Depending on how many pieces of information (in bits) are stored in a single cell, the standards are divided into Single-Level Cell (SLC, 1 bit), Multi-Level Cell (MLC, 2 bits), Triple-Level Cell (TLC, 3 bits), Quad-Level Cell (QLC, 4 bits), and Penta-Level Cell (PLC, 5 bits).


SK Hynix announced on the 25th that it has completed the development of a 321-layer 2TB Quad-Level Cell (QLC) NAND product and has started mass production. SK Hynix

SK Hynix announced on the 25th that it has completed the development of a 321-layer 2TB Quad-Level Cell (QLC) NAND product and has started mass production. SK Hynix

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This product is optimized for ultra-high-capacity eSSD for AI servers. This is an area where big tech companies are rapidly expanding investments, and SK Hynix's development strategy aims to quickly secure market leadership. An SK Hynix official stated, "By implementing QLC technology in NAND with more than 300 layers for the first time in the world, we have once again overcome technical limitations. With this product, which has the highest density among existing NAND products, we plan to target the AI data center market in earnest from the first half of next year after obtaining global customer certification."


In particular, to maximize cost competitiveness, the company developed the product with 2TB capacity, doubling the previous standard. As NAND capacity increases, more information is stored in each cell, and memory management becomes more complex, which can slow down data processing speeds. To address performance degradation resulting from higher capacity, SK Hynix increased the number of planes-the independently operating groups within the NAND chip-from four to six, enabling more parallel operations. Here, a plane refers to a group of cells and peripheral circuits that can operate independently within a single chip.


As a result, this product delivers significantly improved performance compared to previous QLC products, in addition to its high capacity. Data transfer speed has doubled, write performance improved by up to 56%, and read performance by 18%. Data write power efficiency has also increased by more than 23%, ensuring competitiveness in areas such as AI data centers where low power consumption is essential.


The company plans to first apply the 321-layer NAND to SSDs for PCs, then expand its use to eSSD products for data centers and Universal Flash Storage (UFS) for smartphones. Furthermore, SK Hynix aims to target the ultra-high-capacity eSSD market for AI servers by implementing its proprietary packaging technology, which stacks 32 NAND chips at once to achieve high density.



Jung Woopyo, Executive Vice President in charge of NAND development at SK Hynix, stated, "With the start of mass production of this product, we have significantly strengthened our high-capacity product portfolio and secured price competitiveness. In response to the explosive growth in AI demand and the high-performance requirements of the data center market, we will take a greater leap forward as a 'full-stack AI memory provider.'"


This content was produced with the assistance of AI translation services.

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