Tom Lee, head of research at Fundstrat, believes that AI capital is shifting to Ethereum rather than memory chip makers. Over one month, ETH gained 24% while the Roundhill Memory ETF, or DRAM, fell 38%.
In brief
- Tom Lee talks about an “AI downstream trade” which, according to him, favors Ethereum.
- Over one month, the spread between ETH and the DRAM ETF reaches 7,200 basis points.
- The thesis is currently based on performance, not proven capital flows.
Why Tom Lee is talking about an AI rotation to Ether
The market has already started treating Ether as a more cyclical asset than yesterday. Tom Lee relies on this same vigor to defend his reading.
In his post relayed by Cryptopolitanhe observes a gap of 7,200 basis points between ETH and the Roundhill Memory ETF over one month.
Lee’s message is simple. When ETH advances by 24% and DRAM falls by 38%, he sees this as a shift in the “AI downstream trade” towards Ethereum. In other words, the capital that benefited from the AI infrastructure boom would seek a relay further down the value chain.
Tom Lee wrote on X: “ The downstream AI trade continues to strengthen. Over a month, ETH outperformed the Roundhill Memory ETF (DRAM) by 7,200 basis points. »
This reading gives Ethereum a place in the AI narrative without reducing it to a simple speculative asset. It also has a clear limit. Tom Lee does not show here incoming flows towards ETH, he only shows a performance gap between two assets which evolve in very different universes.
The memory chip ETF is not a perfect AI thermometer
DRAM is not an ETF like any other. The fund, launched on April 2, 2026, bills itself as the first ETF entirely dedicated to memory makers, including DRAM, NAND and high-bandwidth memory, or HBM. It therefore serves as a proxy for part of the AI infrastructure, not the entire sector.
The problem is that memory component prices don’t always tell the same story as stocks. TrendForce on July 3 forecast a 13% to 18% increase in DRAM contract prices in the third quarter of 2026, as well as a 10% to 15% increase in NAND Flash prices. IDC, for its part, still anticipates $758 billion in global AI-related spending by 2029. The fund therefore remains buoyant, even if the DRAM ETF fell over the period observed.
In other words, the drop in memory funds does not prove a leak from AI. It can also reflect profit taking, sectoral arbitrage or a simple rebalancing after a too rapid phase. Here again, Tom Lee reads a movement of capital. The visible data above all shows a difference in stock market behavior.
Why Ethereum still benefits from the AI narrative
The case remains interesting for another reason. Ethereum is no longer just about decentralized finance. Its settlement layer, its capacity to carry tokenization and its role as an on-chain infrastructure give it a new macro reading, especially when investors are looking for concrete uses beyond mining and trading.
Cryptopolitan also recalls that Lee sees in Ethereum a network likely to benefit from the growing needs of AI in decentralized settlement, tokenization and digital infrastructure. This thesis does not only depend on the price of Ether. It also depends on the network’s ability to remain relevant when liquidity cycles change.
The market loves this type of narrative because it connects two powerful themes, AI and crypto. On the other hand, we must not confuse story and proof. For the moment, Ethereum is mainly benefiting from a favorable context, a renewed interest in crypto ETFs and a return to the theme of programmable assets.
In short, Tom Lee’s reading says something useful about the market, but not yet about the flows themselves. ETH benefits from a broader narrative, memory remains under market pressure, and the rotation to Ethereum thesis needs stronger data to be validated.
At this point, the topic still reads like a market signal, not definitive proof. To extend the reflection, Tremplin.io also treated tokenization as the next major project in finance.
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