The persistent expansion of AI server demand is providing a sustained boost to memory prices, granting top-tier manufacturers increased pricing power.

According to a Bank of America Merrill Lynch survey released on August 1, Samsung Electronics has integrated 60% to 70% of its memory sales into long-term agreements (LTAs). These contract terms are notably skewed in favor of the supplier: price decreases are capped, while the potential for price increases has no upper limit. Against a backdrop of rising high-end memory demand from AI infrastructure builds and constrained supply expansion, Samsung is locking in demand from major clients under these LTAs while retaining flexibility for upward price adjustments. The report forecasts that spot prices for both DRAM and NAND will continue to recover ahead of the peak fourth-quarter season.

Expanding Long-Term Agreements to Secure AI Client Demand

Currently, approximately 60% to 70% of Samsung Electronics' memory sales are conducted through LTAs, with contract structures clearly favoring the supplier. The Bank of America Merrill Lynch survey reveals that Samsung's LTA terms limit the scope of price reductions, typically capping a single quarterly decline at no more than 5%. Conversely, price increases can range from 10% to 20% or even higher, with no explicit ceiling. Notably, the LTAs Samsung has signed with major US technology companies predominantly use a five-year rolling model, where the next cycle can be renewed shortly before or after the first year's contract concludes, creating a long-term binding relationship. The report suggests this model enhances the revenue certainty of Samsung's memory business while preserving its ability to raise prices during periods of tight supply and demand. As AI server demand grows, memory manufacturers are using LTAs to secure demand and bolster price control.

Rising DRAM and NAND Prices: August Rally Fueled by AI and Inventory Restocking

The spot market for memory has remained robust recently. As of the report's release, DRAMeXchange data shows the spot price for 16Gb DDR5 reached $51, up 733% year-over-year; the spot price for 16Gb DDR4 hit $85.2, a 896% annual increase; and the price for 8Gb DDR4 stood at $42.1, up 722% from the previous year. On the NAND front, the spot price for 1Tb wafers was $26.4, a 3% weekly increase and a 415% year-over-year gain. The report identifies three primary factors supporting the continued rise in memory prices in August: first, an increase in downstream customer orders is strengthening demand for inventory replenishment; second, despite rising memory costs, multiple OEM manufacturers are still planning to launch new products in September and the fourth quarter, driving procurement needs; and third, terminal inventory levels have significantly decreased, initiating a channel restocking cycle. Additionally, supply in the spot market remains tight. As it takes time for memory manufacturers to ramp up production capacity, new market supply is struggling to quickly match the demand growth from AI servers, high-end PCs, and smart terminals. In server DRAM, the contract price for 64GB DDR5 memory modules has already exceeded $1,480, while DDR4 module contract prices have reached $1,300, both setting new historical highs. Client SSD prices have doubled since the end of 2025, compared to a full-year increase of only about 35% to 40% in 2025.

Hyper-Scale Cloud Providers Intensify AI Investments, Providing Long-Term Support for Memory Demand

The core driver of the memory price rally remains the wave of investment in AI infrastructure. Bank of America Merrill Lynch data indicates that the combined capital expenditure of the five major hyper-scale cloud providers—Amazon, Microsoft, Alphabet, Meta, and Oracle—is projected to reach $730 billion in 2026, a year-over-year increase of approximately 100%. From 2027 to 2028, the scale of related capital spending is expected to exceed $1 trillion annually. Meanwhile, AWS, Azure, and Google Cloud are anticipated to maintain revenue growth of 35% to 45% over the next few years, persistently supporting investments in AI computing infrastructure. Although some cloud providers may face periodic free cash flow pressures in 2026 and 2027, Bank of America Merrill Lynch believes this reflects the commitment of tech giants to long-term AI infrastructure building, which will continue to drive demand for the memory, advanced packaging, and server supply chain. As the AI capital expenditure cycle progresses, this memory upcycle is jointly supported by three factors: AI computing power, long-term supply agreements, and persistently tight supply-demand dynamics.