In the near future, smartphone performance may deteriorate, not due to a lack of innovation, but due to the sharp increase in the cost of a key component: memory. DRAM and NAND prices are rising sharply and are expected to remain high through at least the first half of 2026.
Vendors are raising prices as demand for AI servers, data centers and enterprise hardware solutions soars. The pressure first showed up in PC RAM prices.; it now extends to devices such as smartphones, tablets and smartwatches.
Every popular brand you know will respond by doing one of three things: raising prices, cutting profits, or quietly cutting RAM in future models. While shrinking profits are the least likely scenario, manufacturers are likely to raise prices or reduce device storage, especially for devices that account for a large share of their sales.
For smartphones, this means that you may no longer find 16GB of RAM, even in top-end models (there may be some exceptions), fewer models with 12GB of RAM (down by more than 40%), and 8GB models reduced by more than 50% (via a post on Korean Naver Blog).
Less RAM can be a bottleneck for AI features on the device
To mitigate the impact of prices, Xiaomi is already considering reducing RAM on specific 2026 smartphone models (via GizChina). Along with this, other Chinese smartphone giants such as OnePlusVivo, Oppo and global brands such as Samsung And GoogleIt will also have to deal with the heat, leading to a rare moment in smartphone history where performance could stagnate or even deteriorate even as software requirements continue to rise.
Unlike cloud-based AI, on-device models require a significant amount of memory, which is why you see flagship Android devices or even mid-range devices with more than 8GB of RAM. If smartphone manufacturers reduce the amount of physical memory on a device, it will leave less room for the AI model and apps to coexist, resulting in aggressive RAM management, app reloads, or slower AI features.
What's more, the growing number of on-device AI features and the looming threat of memory supply chain constraints could push smartphone specifications back at least several years (with software being released by 2026). Even if manufacturers decide to keep similar memory, there's a good chance they'll pass on the extra cost to customers.
Simply put, your next Android smartphone may be either more expensive or noticeably less responsive. While companies often sell flagships at higher margins, leaving more room for cost adjustments, the impact may be worse on mid-range devices, which are often sold at lower margins: Buyers may end up paying more for lower specs.
The problem is concentrated in the middle class segment.
Strictly speaking, in the US market, the memory issue matters most in the $400 to $800 segment, where Android smartphones prioritize performance per dollar and longevity above all else.
And yes, Apple iPhones You can also get a taste of it, as the company is banking on greater software optimization and chipset efficiency than on-board memory. But this does not mean that the company is completely protected. If the condition does not improve and the price of high-quality RAM increases, Apple buyers may have to pay more for the level of performance they are accustomed to.
Laptop manufacturers could also focus on reducing shipments of models with more than 16 GB of RAM (by more than 60%). Brands could instead focus more on 8GB RAM variants, primarily due to the large number of built-in models, but these could come with price hikes.
If memory prices remain high, manufacturers will have to make long-term decisions about what smartphones, tablets and other consumer devices they want to ship. We could see a clearer segmentation, with premium models retaining more RAM, greater software optimization, and fewer AI-powered features on devices with less memory or budget devices.
Memory as a bottleneck may also force Google to rethink how Twins The Nano model is deployed across devices and the amount of system resources it consumes. The industry as a whole could adopt hybrid AI approaches, where some functions are performed on the device while others are offloaded to the cloud. Will manufacturers retain certain AI-powered features for the top trims of their models?
