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TrendForce’s latest findings indicate that over the next two years, AI infrastructure will mainly focus on high-performance inference services. As traditional high-capacity HDDs face significant shortages, CSPs are increasingly sourcing from NAND Flash suppliers, boosting demand for nearline SSDs designed specifically for inference AI and catering to urgent market requirements.
NAND Flash vendors are quickly validating and adopting nearline QLC NAND Flash products to address the supply gap. QLC technology offers higher storage density at lower costs, making it essential for meeting large-capacity demand. Suppliers are also increasing QLC SSD production, with capacity utilization expected to steadily grow through 2026. The demand is likely to persist into 2027 as inference AI workloads expand, leading to tight supply conditions for enterprise SSDs by 2026.
TrendForce highlights that to enhance the competitiveness of nearline SSDs in AI storage and better replace HDDs, future products will focus on increasing capacities and lowering prices. Manufacturers are working on new nearline SSDs that surpass mainstream HDDs in capacity, offer better cost efficiency, and significantly cut power consumption.
Diversification of NAND Flash applications: Training and inference in parallel
Beyond inference AI, NAND Flash suppliers are also focusing on AI training applications by introducing High Bandwidth Flash (HBF) products, dividing the industry into two main technology groups. The first is led by SanDisk, which is developing a hybrid design that integrates HBM with HBF. This approach seeks to balance large capacity and high performance to fulfill the dual needs of data throughput and storage in AI model training.
The other group is led by Samsung and Kioxia, focusing on storage-class memory technologies like XL-Flash and Z-NAND. These offer a more affordable alternative to HBM, aiming to attract a wider range of customers.
TrendForce emphasizes that the rivalry among technology routes is driving NAND Flash beyond conventional storage, integrating it more deeply with AI computing. This suggests a future with more diverse NAND Flash applications.
