Spot prices for DDR5 memory modules have plummeted by nearly 30% in a single month. Wholesalers in mainland China are describing the current market as a &#34;price crash,&#34; and Google's TurboQuant algorithm has further ignited concerns that AI memory demand will shrink significantly, keeping memory sector stocks under sustained pressure. However, analysts point out that this crash is occurring in the consumer spot market rather than the server demand that drives industry profitability—structurally, the two are almost parallel markets.
Influenced by doubts about a sharp drop in memory usage caused by Google's latest TurboQuant compression algorithm, combined with the concentrated sell-off of previously hoarded capital, DDR5 memory module quotes in U.S. and Chinese retail channels have led the decline, dropping nearly 30%. This is the first significant pullback since the current surge in memory prices, and market sentiment is rapidly shifting from the previous &#34;universal shortage&#34; to a wait-and-see stance.
Despite panic over a &#34;price crash&#34; at the retail end, Wall Street and industry research institutions generally emphasize that the spot market accounts for only a tiny fraction of total memory transactions. Recent reports from Goldman Sachs and South Korean brokerage Daishin Securities both indicate that the enterprise contract market has not been affected. Major cloud service providers' demand for server memory remains urgent, and supply-demand fundamentals have not undergone a substantial reversal. The spot market primarily consists of PCs and consumer electronics, accounting for at most a low single-digit percentage of total market transactions.
The risks truly unsettling institutional investors come from another direction: The escalation of the Middle East conflict is driving energy costs sharply higher, while AI industry debt leverage is accumulating at a historic pace. Multiple fragile points are interweaving to form the most severe systemic stress test since AI became an economic pillar.
<h2>Spot Price Collapse: Speculation Fades After Price Hikes Outpace Demand</h2>
This price correction first brewed in the retail and spot markets, with declines generally falling between 15% and 30%.
In the U.S. market, 32GB 6400MHz DDR5 modules on Amazon have dropped from a high of $490 to $379.99; in the Chinese market, mainstream 16GB DDR5 module prices have also fallen from a peak of 1,000 RMB to around 700 RMB. Wholesalers in mainland China stated frankly that high prices led to a significant decrease in non-essential purchases, with recent sales down over 60% compared to last November. The concentrated sell-off of hoarded inventory further intensified the decline.
Goldman Sachs noted in a report that the spot price correction was inevitable. Previously, the premium of spot prices over contract prices was at a significant high, with DDR5 and DDR4 spot prices at premiums of 25% and 111% over February contract prices, respectively. This extreme premium made buyers hesitant. Even after a large correction, spot prices remain well above contract prices and historical absolute levels. High memory prices have suppressed PC consumption and caused Chinese smartphone shipments to decline in double digits for three consecutive months.
<h2>Server Demand: The True Engine Supporting Memory Fundamentals</h2>
Away from the noise of the spot market, signals for server-side demand are clear and strong. Ryu Hyung-geun, an analyst at Daishin Securities, pointed out that the spot market primarily consists of PCs and consumer electronics, representing at most a low single-digit percentage of total market transactions. In the current structure, mobile and server products are what truly determine memory semiconductor profitability.
Macro data confirms this logic. According to the Goldman Sachs report, combined revenue for Taiwanese server ODMs (including Inventec, Quanta, Wiwynn, and Wistron) in February rose 84% year-on-year and 7% month-on-month, maintaining a year-on-year growth rate of over 80% for four consecutive months. This is mainly due to the rapid ramp-up of rack-level AI server shipments and strong growth in ASIC AI servers. Aspeed, the world's largest supplier of server BMC chips, saw its February revenue grow 66% year-on-year, remaining solid despite the high base of February 2025; memory distributor Supreme Electronics saw its February revenue grow 137% year-on-year, showing clear demand at the channel level.
Channel surveys by Daishin Securities also provide a more convincing detail: a large cloud service provider has decided to purchase server DDR4 at a price exceeding HBM3e. &#34;If real demand had begun to weaken, it wouldn't explain why buyers are willing to pay a premium for traditional products,&#34; wrote Ryu Hyung-geun.
<img src="https://imageproxy.pbkrs.com/https://wpimg-wscn.awtmt.com/e6f9bb4d-13aa-4ee7-92ac-6bbd9bff1638.png?x-oss-process=image/auto-orient,1/interlace,1/resize,w_1440,h_1440/quality,q_95/format,jpg" alt="Image" original-src="https://imageproxy.pbkrs.com/https://wpimg-wscn.awtmt.com/e6f9bb4d-13aa-4ee7-92ac-6bbd9bff1638.png"/>
There is also a significant divergence between Goldman Sachs' HBM forecasts and the Wall Street sell-side consensus—forecasting a 56% growth in SK Hynix's HBM shipments for 2026, which is 15 percentage points higher than the consensus expectation of 41%, reflecting high institutional confidence in continued AI infrastructure investment.
Notably, according to the Goldman Sachs report, even as spot prices fall, memory shortages in mainland China remain severe. Some mobile clients have even been forced to lower their full-year smartphone shipment targets due to limited memory supply. The structural contradiction between supply and demand has not been resolved; it is merely obscured by price volatility in the retail market.
<h2>TurboQuant: An Emotional Shock Far Greater Than Fundamental Damage</h2>
Google's TurboQuant algorithm was the core catalyst for the worsening market sentiment, but its actual impact may be significantly overestimated.
According to a previous article from Wall Street Insights, TurboQuant reduces memory usage to about one-sixth by compressing the KV Cache on the AI inference side, which could indeed lower the memory load of individual AI servers in the short term. However, according to the Goldman Sachs report, this effect is two-way: more efficient memory utilization means lower barriers to AI deployment, which could significantly increase the overall penetration of AI Agents and on-device AI scenarios, thereby driving the continuous expansion of total memory demand.
Goldman Sachs' report points out that investors are currently focused on the first half—'the decrease in memory usage'—while ignoring the second half—'volume expansion brought by accelerated AI adoption.' This concern is more of a short-term emotional pressure than actual fundamental damage. The industry generally believes TurboQuant may accelerate AI application adoption in the long run, and its medium-to-long-term impact on memory remains to be seen; the logic currently interpreted by the market as bearish is incomplete.
<h2>The Real Black Swans: Energy Shocks and Debt Accumulation</h2>
While the market focuses on falling memory prices, real systemic risks are quietly gathering on another front.
The Middle East conflict has already had a substantive impact on the AI industry supply chain. According to an article from Wall Street Insights, shipping in the Strait of Hormuz has been disrupted, Brent crude prices rose 40% in a month, and liquefied natural gas prices surged simultaneously in Western and Asian markets, while helium spot prices doubled. The world's most advanced memory and training chips are primarily supplied by three Asian companies, and these economies rely on the Persian Gulf for the vast majority of their crude oil and large amounts of liquefied natural gas. Key raw materials for chip manufacturing, such as helium, sulfur, and bromine, are also highly dependent on the region. Sam Winter-Levy, a research fellow in technology and national security at the Carnegie Endowment for International Peace, stated that the Strait of Hormuz &#34;is critical to almost every aspect of the global economy, and the AI supply chain is not immune.&#34;
Meanwhile, the pace of debt expansion in the AI industry has triggered high institutional vigilance. Hyperscalers like Microsoft, Google, Meta, and Amazon have a combined annual investment in AI approaching $700 billion. In 2025, debt issuance by hyperscalers reached $121 billion, four times the average level of previous years. Private equity firms such as Blackstone, BlackRock, and Blue Owl Capital have invested heavily in data center construction based on the rental income of tech companies, with funding coming from pension funds, endowments, and insurance institutions, extending the risk transmission chain to the entire financial system.
Of course, a full-scale crisis is not the only possible outcome. Revenues for Anthropic and OpenAI are doubling annually, and data center spending might cool down gradually enough to avoid a hard landing. However, under the combined weight of energy shocks, debt accumulation, and highly concentrated supply chains, &#34;a small problem in just a few links could simultaneously trigger a systemic crisis&#34;—and this is the variable memory sector investors truly need to monitor closely.

Google’s latest TurboQuant reduces large model KV cache to around 3-bit, enabling about 6× memory savings along with performance gains, directly weakening AI inference’s reliance on high-capacity storage. For leading companies in the storage sector (such as HDD, flash memory, and cloud storage providers), this could bring pricing pressure or margin compression.Do you think Google’s new technology will truly impact the investment value of the storage sector? Is it a short-term fluctuation or a long-term structural shift? Feel free to share your thoughts!

Google’s latest TurboQuant reduces large model KV cache to around 3-bit, enabling about 6× memory savings along with performance gains, directly weakening AI inference’s reliance on high-capacity storage. For leading companies in the storage sector (such as HDD, flash memory, and cloud storage providers), this could bring pricing pressure or margin compression.Do you think Google’s new technology will truly impact the investment value of the storage sector? Is it a short-term fluctuation or a long-term structural shift? Feel free to share your thoughts!

Google’s new technology is coming—will the storage sector cool down?

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Affected by concerns over reduced demand triggered by Google's compression algorithm and previous overstocking, DDR5 memory spot prices have recently plummeted by nearly 30%. However, this market crash is confined to the consumer retail market, which accounts for at most a low single-digit percentage of total market transactions; the core AI demand driven by servers remains explosive. Despite pressure on spot sentiment, server OEM revenue and DRAM export data show strong growth, indicating solid industry fundamentals. Compared to spot volatility, rising energy costs caused by Middle East conflicts and the accumulation of debt in the AI industry are the real systemic risks facing the memory sector

- The price of DDR5 memory modules has fallen nearly 30% in a month, driven by concerns over reduced AI memory demand due to Google's TurboQuant algorithm.  
- Analysts emphasize this decline impacts the consumer market, while server demand remains strong and critical for industry profitability.  
- Key systemic risks stem from rising energy costs due to Middle East conflicts and rapid debt accumulation in the AI sector, which could lead to a broader economic crisis.

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Memory Module Market Crash? "Consumers Can No Longer Afford It," but "AI Demand Remains Explosive"