NAND spot: still weak on the module side. 512Gb TLC ▼1.28% | eMMC ▼1.25% | MicroSD ▼3.91% | MLC ▲0.92% High inventories, sluggish trading. TrendForce, Oct 19. #NAND# #MemoryPrices# #AIStorage#

#Memory# prices are so high, reportedly rising by up to RMB 500 per unit, that some Chinese phone makers are turning to chips salvaged from discarded phones via Shenzhen’s Huaqiangbei.💡More: 🔗

Memory prices keep climbing. DRAM: +8.0% MoM in August → Q4 forecast +17.5% NAND: +5.0% MoM in August → Q4 forecast +16.0% AI-driven demand continues to tighten supply, with HBM crowding out conventional capacity. Structural shortage still intact. #Memory# #DRAM# #NAND# #AI# #Semiconductors#

Memory & storage stocks sold off as fears of a Samsung chip strike disruption eased + new warnings about future oversupply out of China weighed on the group. Why Seagate led the declines and what insiders are saying about memory prices next year: $MU $STX

DDR5 memory prices continue to climb in Germany, with average prices now at 419% of their July 2025 levels. According to data from 3DCenter some high-end kits have seen massive increases. One 64GB DDR5-6000 CL28 kit that sold for €208 in July 2025 has climbed to nearly €1,000, including a 22% jump in the last month.

DDR5 MEMORY PRICES UP NEARLY 10X DDR4 is older memory that was being phased out but it's spiking too as $MU, Samsung & SK Hynix shift wafer capacity from conventional memory into HBM for AI chips. The AI cycle is pulling on compute, memory, storage & servers at the same time with pricing power now flowing through the rest of the hardware stack.

Thoughts on memory: Anyone who thinks compute will stay in shortage while memory slides into oversupply must be smoking something. Compute and memory are destined to tighten together or deflate together. One cannot die while the other survives. By the same logic, the pods shorting memory and going long HDD are out of their minds. How do you think HDD isn't joined at the hip with memory? You really think HDD stays safe if this cycle rolls over? In the end, all of this comes down to nobody having conviction about what happens after 2027. Historically, we have watched P peak one to two quarters before supply ramps, then Q expands and the entire profit pool collapses. But everyone forgets that this cycle runs on nonstandard products, unlike PCs, smartphones, and general purpose servers, and that it was triggered by factors different from past cycles. This is because of the boomers who still see memory as an industry where you make a killing in the upcycle and lose your shirt in the downcycle. These self proclaimed veterans view memory through the lens of their past experience, and since they drive the market and set the stock prices, memory trades at such a low valuation. What I keep saying is that a sharp collapse like in the past is impossible. A gradual decline is possible. But even if Samsung and SK Hynix margins were cut in half from current levels, they would still trade at a P/E in the teens. That is still roughly half of HDD valuations. Personally, I think that as memory prices fall, other sources of demand will absorb the supply at each step down. In particular, I expect personal AI demand, led by local AI, to emerge. Looked at another way, for local AI to take off, the hyperscaler driven spike in memory prices has to be brought under control. At current memory prices, local AI can never diversify. Just as mainframes gave way to PCs and the cloud gave way to smartphones, each time carrying the cycle from P into a Q expansion phase, I think this AI cycle will also move from frontier labs to local open source AI. Based on these historical precedents, I believe local AI will take over the memory cycle from the frontier labs and carry memory demand. I am not saying memory prices will hold for more than a decade. Memory P will fall at some point. But what is different from the past is that new consumer devices and new consumer demand, such as open source driven local AI, will support the floor for memory. So the market right now keeps discounting these stocks out of fear of a memory peak nobody can time. This discount is being driven by boomer investors who dismiss the idea that AI supports the downside and keep pushing the view that earnings will collapse and the trough will revert to past levels too. My point is that this is completely wrong.

Some color on current memory environments for the $MU / $SKHY bros: "There is zero risk of memory prices dropping" per Team Group GM Gerry Chen. - Memory module makers have received notices warning of drastic cuts to their 2027 supply allocations. Some could receive 50% or less of their 2026 allocation. - Upstream manufacturers have reportedly sold out nearly all of their 2027–2028 capacity. - DDR5 supply, in particular, is projected to come in at less than 80% of previous expectations. - Chen expects prices to continue rising 20–30% quarter-over-quarter into 2027 (source Digitimes) - Chen's commentary on $MU is that even before their new MegaFab capacity comes online Q4 2027 at the earliest, orders for 2028 through 2029 are already fully booked. So that there's virtually no relief in sight to current shortages. Sharply lower allocations, fully booked capacity into 2029, and future price hikes doesn't quite sound like the AI buildout is slowing down.

SK Securities: Memory Revaluation Stemming from a Shift in the Perception of Compute Perception of compute: from consumable to asset AI compute is not a consumable. Rather than a technology good whose value erodes quickly, it could become an infrastructure asset that is redeployed across generations and generates recurring cash flows. From this perspective, AI CapEx is not simply a recurring cost but a process of accumulating a compute stock that can be monetized multiple times going forward. CoreWeave's recent earnings release shows this possibility. Even A100 based resources, six years past launch, are being signed into long term contracts running through 2029, and prices for older GPUs are also holding at meaningful levels. This does not have to be read purely as a supply shortage. Customers choose the cost relative to the performance their workload requires, not the fastest GPU. The newest GPUs handle frontier training and high performance inference, while existing H100/A100 can shift to general inference, fine tuning, batch workloads and the like. This is the concept of compute tiering, analogous to memory tiering. Once the perception of compute changes, the lens through which the expansion of AI infrastructure finance is viewed also changes. If AI infrastructure such as GPUs can generate revenue repeatedly through recontracting after the initial contract ends, it becomes a financeable infrastructure asset rather than simply a piece of electronic equipment. BEP within three years, and the period after that may be the real profit zone The same logic can apply to hyperscaler FCF. Amazon stated that its investments in servers and networking equipment reach BEP on average in less than three years. This means that if the economic life of compute assets including GPUs extends beyond three years, the subsequent period of use may be not simple principal recovery but a zone that generates additional profit. Revenue from new GPUs and second life revenue from the existing compute stock would occur at the same time. If, as with the A100, assets remain applicable into their ninth year, it means a considerable, highly profitable excess return zone opens up between the payback period the market worries about and the actual economic life. The change in memory's status is a structural phenomenon. A change that has to be accepted Once the perception of AI CapEx changes, it is entirely natural that memory's status changes. AI is an asset heavy industry, and physical supply capacity constraints in the real world are not something that can be changed. The reason five year LTAs with high binding force have been signed also becomes clear. Memory has a material impact on the customer's "true" profit zone. If memory does not make money, meeting demand will remain out of reach, volumes will not be secured while memory prices alone rise, and the future revenue curve will be revised downward. Memory making a lot of money is structural, and it is a change that has to be accepted. Inflection point in the change of memory valuation metrics: shareholder returns strengthen in earnest through greater earnings durability and visibility SK Securities maintains its Overweight view on memory. We focus on memory's structurally enhanced earnings power and on the shareholder returns that will begin in earnest, driven by greater durability based on a long cycle. Combined estimated operating profit for Samsung Electronics and SK Hynix is KRW 641tn in 2026 and KRW 977tn in 2027, among the highest globally, and aggressive shareholder returns are expected to be the key foundation for building confidence in the long cycle and for memory's revaluation. We are wary of peak out logic based on the inevitable slowdown in the rate of memory price increases. This is now an era in which the strength of the cycle is absorbed not only through "price" but also through "durability and visibility."