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High-bandwidth memory generally costs about 5x more per GB than conventional DRAM. As AI systems support longer context windows and more complex reasoning, memory demand is spreading into conventional DRAM and NAND. The mechanism is a tiered memory system. HBM holds active model weights and the context needed now. External DRAM holds a broader pool of context that the model can retrieve, while NAND-based SSDs store less frequently used context and model checkpoints. This keeps more context accessible at a lower cost, with a latency trade-off. Memory producers are operating at approximately 80% gross margins and 60%+ EBIT margins. The industry's through-cycle average gross margin has been 35-40%, and past peaks rarely exceeded 55-60%. Supply explains much of this. Samsung, SK Hynix and Micron invested heavily in capacity during the 2021-2022 boom. That capacity came online in 2023 and 2024, when smartphone, PC and non-AI server demand was weak. All three cut production, recorded operating losses and set conservative capex plans. Samsung cut DRAM output by approximately 15-20% in 2023. The capacity response as of mid-2026: 1. Samsung has targeted a roughly 50% increase in HBM production capacity this year. 2. SK Hynix has accelerated its HBM4 ramp through the M15X fab, while reportedly redirecting some planned HBM4 capacity toward DDR5. 3. $MU has accelerated DRAM and HBM output in Taiwan. Meaningful wafer starts from its new US and Singapore facilities are not expected until 2027 and beyond. These additions are weighted toward HBM and high-end server DRAM, not broad conventional memory capacity. They appear insufficient to close the gap in the near term, so the unusually high margins look likely to persist for several more quarters.

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