The computing market is absolutely ablaze with AI-driven growth. Regardless of how sustainable it might be, companies are spending untold amounts of wealth on hardware, with most headlines revolving around GPUs. But the storage market is also under pressure, especially hard drive vendors who purportedly hen't done much to increase manufacturing capacity in a decade. TrendForce says lead times for high-capacity "nearline" hard drives he ballooned to over 52 weeks — more than a full year.
TredForce posted two articles on essentially the same topic today. One of them includes a letter from Western Digital to its customers warning of "unprecedented demand for every capacity in [its] portfolio," and stating that it is raising prices on all of its hard drives. WD says, of course, that this is "to support this growth and ensure continued excellence," but of course, the company will benefit from the bump to its margins and thus, profits.
📈 Following SanDisk’s 10% #NAND hike and Micron’s week-long pricing freeze, #WesternDigital is joining the price-raise club! #HDDs across all capacities are set to go up, and ocean freight delays could stretch delivery by weeks—better plan your orders now!💡More:… pic.twitter.com/iFj1vCPW5ESeptember 15, 2025
If you're unfamiliar with the term, "nearline" refers to storage that is not quite online, yet also not quite offline. It's "warm" data, information that needs to be ailable for ready access, but doesn't he to be as quick or responsive as the SSDs that serve as primary online storage for essentially all systems now. Because it isn't constantly being accessed, hard drives can fill this role in an economical fashion. While SSDs he made huge strides in price-per-gigabyte, hard disks are still typically four to five times cheaper by capacity.
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Generative AI, as a class of workload, implies tremendous demands for nearline storage. Obviously, generative AI can spew out an unlimited pile of output, but it's not just the AI models' output that is filling up servers' storage. The software infrastructure to both set up and run generative AI workloads is itself quite hey: Training datasets, model checkpoints, inference logs, and more specialized fine-tuning datasets can all eat up petabytes of data in a shockingly short amount of time.
That's why the trendline for warm storage is going vertical: You don't just need the data required to run inference. You also need the history of everything to prove to regulators that you're not laundering bias, to retrain when new data comes in, and to roll back to a previous checkpoint if your fine-tuned model goes feral and, say, starts referring to itself as MechaHitler. This stuff can't go to offline storage until you're certain it isn't needed in the short term. But it's too big to live in the primary storage of all but the beefiest servers. Thus, the need for nearline hard drives.
Because the supply of hard drives is insufficient, cloud service providers (CSPs) and other hyperscalers might be looking at economical QLC SSDs for cold data storage. This has its benefits; performance is better, physical density can be improved, power consumption is typically lower, and most importantly, they're actually ailable to purchase. However, as we noted, SSD prices start at around four times the cost per gigabyte, and that adds up real quick when you're buying hundreds, thousands, or tens of thousands of terabytes of storage.
In response, Trendforce reports that memory suppliers are actively developing SSD products intended for deployment in nearline service. These should help bring costs down once they hit the market. But in the short term, we can expect the storage crunch to cause rising SSD prices as well, at least for enterprise drives. If you're keen on picking up some solid-state storage, it might not be a bad idea to start shopping now. Make sure you check out our list of the best SSDs for 2025 before you do.
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