[News] QLC SSD: The Game-Changer for NAND Flash?

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In the era of AI and big data, new market demands are emerging in the storage industry, and QLC NAND SSDs, which play a critical role in AI training. This suggests that NAND flash may be on the verge of a new growth opportunity.

QLC, or Quad-Level Cells, refers to NAND flash where each storage cell can record 4 bits. Each cell maintains a standard size, and compared to traditional SLC, MLC, and TLC technologies, QLC enables higher data density, allowing more data to be stored in the same space.

The Advantages of QLC Flash

QLC flash offers several key advantages:

• Capacity: Compared to mainstream TLC flash, QLC increases storage density by 33%.
• Cost: With the same number of flash chips cut from a wafer, QLC provides about 33% more storage capacity than TLC, leading to a lower cost per unit of storage.
• Total Cost of Ownership (TCO): QLC-based SSDs offer lower TCO compared to traditional HDDs. TCO includes considerations like storage density, reliability, and power consumption. While QLC’s write performance is somewhat inferior to other technologies, its read performance is strong.

However, QLC technology also faces some challenges. Since data is stored across more charge levels, this increases the risk of data vulnerability, requiring more advanced error correction and data protection mechanisms. QLC storage devices typically need stronger error correction algorithms and robust data protection to ensure integrity and reliability.

Despite these challenges, as technology continues to advance, QLC is expected to play an increasingly important role in the storage field, potentially revolutionizing the entire information industry.

QLC NAND is Entering the AI SSD Battlefield

Many believe that QLC SSDs are a complement to TLC SSDs, particularly suited for read-intensive and mixed read/write workloads, such as those found in AI, content delivery networks, and machine learning.

In AI applications, TrendForce points out that SSDs are used in AI inference servers to help adjust and optimize AI models during inference, especially by updating data in real-time to fine-tune model outputs. AI inference mainly supports Retrieval-Augmented Generation (RAG) and Large Language Models (LLMs), and SSDs can store reference documents and knowledge bases for RAG and LLM to generate richer responses.

As more generated information is displayed as videos or images, data storage demands increase, making large-capacity SSDs, such as 16TB+ TLC/QLC models, essential for AI inference.

Currently, companies like Samsung, SK Hynix’s Solidigm, Western Digital, and Kioxia hold key positions in the QLC SSD market.

Industry experts are optimistic about the future of QLC SSDs, emphasizing their benefits for data centers, cloud storage providers, and enterprises handling massive amounts of data. QLC SSDs are seen as a potential game-changer for the NAND flash market.

TrendForce also predicts that QLC will account for 20% of NAND flash shipments by 2024, with this share expected to rise in 2025. Moreover, QLC is likely to expand into consumer-embedded storage such as eMMC and UFS, with some products already adopting QLC as the storage medium.

Industry forecasts suggest that by 2025, large-capacity QLC enterprise SSDs will rise, and smartphones will start using QLC-based UFS storage solutions.

(Photo credit: Samsung)