On July 19, 2026, a report from South Korea's Meritz Securities truly pushed this round of "sovereign AI" onto the hardware cost curve: Sovereign AI funds in the Middle East, including Saudi Arabia, began negotiating mid to long-term procurement plans with South Korean memory chip manufacturers. Meritz expects the Q3 2026 DRAM contract prices to increase by more than 15% quarter-over-quarter, while industry research revised the expected average global DRAM price upwards by +21%. The spot prices of server DRAM have already shown upward pressure, while prior TrendForce forecasts for the overall increase of traditional DRAM and that including HBM remained in a more moderate range. Qiming Venture Capital emphasized in a recent report that the demand for AI computing power is shifting from the training phase to the inference phase, and that storage, advanced processes, and packaging will face structural shortages in the next two years, which means sovereign funds locking in long-term supply is only the starting point of a hardware inflation cycle. On the equity side, The Kobeissi Letter pointed out that the volatility of US momentum stocks (including Nvidia, etc.) relative to the S&P 500 has skyrocketed to four times, reaching an all-time high. During the same period, SpaceX's stock price fell below its initial offering price, accumulating a drop of over 40%, with a market value evaporating by more than a trillion dollars. Musk's personal wealth declined by over $250 billion in a month. AI assets and non-AI tech assets have been repriced simultaneously, with relevant data primarily from a single source pointing in the same direction: the AI infrastructure cycle is pulling global tech funds from "valuation expansion" to "cost and volatility constraints." Under such compounded shocks, hardware cost inflation and the increase in technology asset volatility will inevitably change the roles and trading structures of BTC, ETH, and on-chain tokens related to the AI narrative in the portfolio, shifting from purely tech risk amplifiers to core chips that rebalance liquidity and risk preferences under high volatility and high cost constraints.

Middle East sovereign AI funds buying up storage raise costs

Meritz Securities pointed out a key change in its report on July 19, 2026: Middle Eastern sovereign AI investors, including Saudi Arabia, no longer regard memory chips as "on-demand operating costs," but are directly negotiating mid to long-term procurement plans with South Korean storage manufacturers. Coupled with the expectation that Q3 2026 DRAM contract prices may rise more than 15% quarter-over-quarter, and channel research showing that the spot market for server DRAM has already seen upward price pressure, along with industry research raising the expectation for Q3 global DRAM average prices to 21%, significantly higher than the 13%-18% range previously given by TrendForce, this suggests that DRAM, a traditional cyclical product, is being "nailed" by sovereign funds onto a higher, more solid cost step. Sovereign AI funds locking in multi-period contract supply effectively withdraw future storage elasticity from the open market, forcing global AI infrastructure capital expenditures to concentrate on realizing value within a shorter timeframe, entering a capital expenditure cycle of "locking resources first, then calculating returns" even before hardware prices have peaked.

In the cost transmission chain, the rise in spot prices for server DRAM directly increases the global bottom line of computing power, forming a closed loop with Qiming Venture Capital's judgment of "structural shortages in storage, advanced processes, and advanced packaging in the next two years": computing power is no longer just a story about GPUs, but is jointly "taxed" by memory and packaging stages. For the US tech sector, this rewriting of cost will lead to a reevaluation of the profit paths for AI hardware and cloud platforms, compressing the valuation safety cushion and increasing stock price sensitivity to every adjustment in cost and supply expectations. For the on-chain world, the global price increase of computing power and storage marginally raises the production costs of computing-intensive assets such as BTC and ETH, tying them more explicitly to the macro variable of "hardware inflation." When Middle Eastern sovereign funds view AI hardware as a long-term strategic allocation, on-chain tokens around computing power and AI narratives will passively gain a longer story cycle and higher potential portfolio weight, and the long-term trading coordinates of the crypto market will begin to rearrange around this new axis of "hardware costs — computing power premiums — on-chain risk preferences."

Expectations of DRAM price increases and computing power inflation

When Meritz raises the expectation for Q3 2026 DRAM contract prices to increase by over 15% quarter-over-quarter, and industry research gives a 21% quarter-over-quarter increase for global DRAM average prices, the previous TrendForce predictions of 13%-18% for traditional DRAM and 8%-13% for the inclusion of HBM have effectively been thrown behind by the new computing power cost curve. Qiming Venture Capital emphasizes that AI demand is shifting from training to inference, which is more sensitive to storage capacity and bandwidth with longer lifecycles. This means the weight of DRAM and other storage in the cost structure of large model inference is elevated; if cloud vendors and AI application service providers cannot successfully pass on this cost to end users, profit margins will be directly eroded by hardware prices, creating a sustained "cost inflation" for computing power.

The result of computing power inflation is a rewriting of the future cash flow discounting structure for AI publicly traded companies: downward revisions in profit expectations and increased profit volatility will prompt the market to raise discount rates and risk premiums in valuation models, compressing the duration premium of high-growth tech stocks and shifting the entire discount coordinates of risk assets toward "more expensive computing power and higher return requirements." In such an environment, BTC, ETH, and on-chain tokens surrounding computing power and AI narratives are constrained by rising hardware costs, while also potentially being viewed by some funds as structural trading tools against computing power inflation, as they do not directly anchor to a single company's profit statement. Their relative attractiveness in a portfolio will be repeatedly reassessed alongside changes in discount rates and computing power costs.

Surge in volatility of AI growth stocks ignites risk

As computing power costs rise on the supply side, the stress reaction on the asset side has already given price signals in the most crowded US AI sector. Statistics from The Kobeissi Letter show that the three-week volatility of momentum stocks, including Nvidia, has risen to four times that of the S&P 500, reaching an all-time high. This group of AI leaders, previously regarded as "pseudo-index assets" in many portfolios, has suddenly slid from steady blue chips into an asset pool dominated by high-frequency trading and speculative sentiment. At the same time, SpaceX's stock price fell below its initial offering price, accumulating a decline of over 40%, with its market value evaporating by more than a trillion dollars. Musk's wealth shrank by over $250 billion in a month, indicating that funds are being pulled between "high volatility of AI core assets" and "sharp corrections of non-AI tech assets." The mainline of this repricing has become: the tech weighting overall must exchange for a higher risk premium, and all high beta assets must reprove their existing value. It is important to emphasize that the data mentioned comes from a single source, serving more as a market expectation outline being formed rather than a crystallized consensus.

At this level of volatility, traditional funds show path dependence in their responses: first by reducing leverage, then increasing required returns on portfolios, and finally cutting exposure to the most volatile assets. Historical correlations show that the expansion of volatility in tech growth stocks will, at times, synchronously elevate the volatility and option implied volatility of BTC and ETH, as these three are often packaged together in the same "growth + narrative premium" risk bucket in many long positions. The result is that AI-themed funds and momentum funds are beginning to make cross-asset rotations between the US stock market and crypto: when AI stocks such as Nvidia become overly crowded and volatility peaks, some funds may choose to increase positions on-chain or switch to assets like BTC and ETH, which are not anchored to a single company's cash flow, viewing them as structural trading tools against "computing power inflation + an increase in tech risk premiums." Yet in a risk manager-led phase, the same batch of funds may also be forced to cut on-chain high volatility exposure, first trimming AI narrative tokens, and then reducing leveraged long positions on BTC and ETH. Therefore, in the coming weeks, whether the volatility curve of BTC, ETH, and AI narrative tokens follows or diverges from the extreme volatility of this round of US momentum stocks will become a key observation point to determine whether the "high volatility premium of AI" is amplified or hedged on-chain.

SpaceX crash and Musk's wealth and AI cycle divergence

When the three-week volatility of US momentum stocks relative to the S&P is pulled to an extreme range of four times, another clue quietly moves in the opposite direction: SpaceX's stock price has fallen below its issue price, accumulating a drop of over 40%, with a single source calculation estimating its market value has evaporated by more than a trillion dollars. During the same period, Musk's personal wealth shrank by over $250 billion, also coming from a single source. While it is important to be cautious with the data, this magnitude of pullback is sufficient to create a clear "valuation scissors" on the asset manager's screen: on one end are the storage and computing hardware being augmented by Middle Eastern sovereign AI funds and expected to increase in price, while on the other end are the old aerospace technology assets not central to this round of AI infrastructure narrative.

In the past few cycles, "Musk assets" have consistently been one of the most direct emotional barometers of global risk appetite: Tesla's share price, concept tokens issued around his image, and sentiment trades that fluctuate with social topics have all proven to be highly sensitive to his wealth and changes in public opinion. Now, as Musk's wealth shrinks significantly in the short term, funds are faced with a more complex choice set: on one hand, stocks and concept tokens tied to him may see passive reductions and cooling of sentiment, weakening technology risk exposure driven by the "single hero narrative"; on the other hand, the mainline AI infrastructure under dual pressures of heightened storage price expectations and soaring volatility is attracting a more systematized allocation mindset from funds. From the perspective of the crypto market, this retreat of old technology and divergence of the new AI cycle are drawing some funds away from tech stories anchored in personal IP and toward diversified exposures in AI and digital assets: some seek on-chain AI narrative tokens linked to computing power and storage logic, while others flow back into BTC and ETH, which are closer to "macro risk hedging" underlying assets. This cycle divergence of "Musk assets" and AI assets will be a key signal for assessing whether funds continue to migrate from a single tech narrative to diversified AI and on-chain exposures.

New coordinates for crypto trading amid the upward AI infrastructure cycle

This round of Middle Eastern sovereign AI funds locking in mid to long-term storage procurement, combined with Meritz and industry research signaling a potential quarter-over-quarter increase of over 15% for Q3 2026 DRAM contract prices and a global average price revision up to 21%, has essentially established that the AI infrastructure cycle is entering a stage of rising hardware cost inflation against the backdrop of Qiming Venture Capital's portrayal of "transition from training to inference, and structural shortages in storage and packaging over the next two years," becoming the core macro variable for repricing risk assets. Concurrently, the three-week volatility of US momentum stocks (including Nvidia) relative to the S&P 500 has been identified by The Kobeissi Letter as rising to four times, marking an all-time high, while SpaceX's stock price has fallen below its issue price, accumulating a drop of over 40%, with its market value evaporating by more than a trillion dollars and Musk's wealth shrinking by over $250 billion in a month indicates that funds are paying a higher volatility and risk premium for AI-centric narratives, leading to drastic valuation and position redistributions within technology. Under this dual constraint of "AI hardware inflation + high volatility in technology," the often-seen sector differentiation logic in the crypto market is reemerging: BTC, ETH, and on-chain assets anchored to the dollar continue to take on the roles of liquidity center and macro hedge, while narrative-driven AI tokens and high-leveraged positions are more often used as trading tools to capture volatility, bearing the brunt of the first round of risk compression. Moving forward, the actual trend of DRAM contract prices and server spot market, whether Middle Eastern sovereign AI procurement can land as expected, the evolution of price correlations between AI stocks and on-chain assets, as well as whether dollar-anchored assets and on-chain funds concentrate on "BTC, ETH defensive positions" or again flow into high-beta AI narratives will jointly determine whether the trading coordinates in this round of AI infrastructure ascent return to defensive macro assets or push toward more aggressive AI risk exposures.

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