Is the semiconductor bull market over? Meta enters cloud computing to sell excess computing power, AI hardware stocks plummet across the board

In the first trading day of the second half of 2026, the US stock market experienced an extreme divergence. Social media giant Meta surged nearly 10% in a single day on news of "selling computing power," while AI hardware sectors such as memory chips, semiconductor equipment, and optical communications saw a widespread collapse. The Philadelphia Semiconductor Index (SOX) plummeted 6.27% in a day, closing at 13,353.28 points. Micron Technology (MU) fell 10.57%, SanDisk (SNDK) dropped 10.62%, Intel (INTC) lost 9.03%, and Applied Materials (AMAT) declined 9.97%.

Is this crash a signal of the end of the AI hardware bull market, or just an emotion-driven overreaction?

How a Single Report Triggered a Full-Scale Collapse in the Semiconductor Sector

Before the market opened on July 1 Eastern Time, Bloomberg reported that Meta is developing a plan for a cloud infrastructure business, aiming to sell AI computing power and model access to external customers. The internal codename for this initiative is "Meta Compute," co-led by Meta's infrastructure chief Santosh Janardhan, AI department executive Daniel Gross of the super-intelligence lab, and Meta President Dina Powell McCormick.

The core takeaway from the report: Meta is considering commercializing its vast AI infrastructure resources—including data centers and AI chips—externally, in a model similar to Amazon AWS's Bedrock service. Upon the news, the market's interpretation quickly shifted from "Meta opening a new revenue stream" to a more damaging question: If Meta already has so much spare computing power that it can sell it externally, has its demand for upstream chips, memory, and optical modules reached a stage of saturation?

This narrative shift directly triggered a concentrated sell-off in the semiconductor sector. Only 2 of the 30 components in the Philadelphia Semiconductor Index posted gains. Memory stocks bore the brunt, with the Roundhill Memory ETF plunging 10.82% in a single day. Semiconductor equipment stocks also crashed in tandem, with KLA Corporation (KLAC) down 11.77% and Teradyne (TER) down 11.68%. In the optical communications sector, Corning (GLW) dropped 13.62%, and Astera Labs fell 10.80%.

Why Micron and SanDisk Became the Hardest Hit

Memory chip stocks suffered the most severe losses in this crash. Micron Technology fell 10.57%, SanDisk dropped 10.62%, Western Digital (WDC) declined over 6%, and Seagate Technology (STX) lost more than 5%.

This structural disparity is no accident. Memory chips are a core beneficiary of AI infrastructure buildout—large model training and inference require massive amounts of HBM (high-bandwidth memory) and SSDs (solid-state drives). Micron is one of the biggest beneficiaries of this logic. Just a week earlier (June 24), Micron released its fiscal Q3 2026 earnings: revenue of $41.46 billion, up 345.7% year-over-year; GAAP net profit of $28.24 billion, surging 1,398.3% from a year ago. Gross margin reached 84.9%, setting a new record for the fifth consecutive quarter. The company's revenue guidance for the next fiscal quarter was approximately $50 billion, significantly above the analysts' average estimate of $43.58 billion.

It was precisely this extreme earnings growth that created fertile ground for profit-taking. Micron Technology's cumulative gain in the first half of 2026 exceeded 260%. When the market narrative shifted from "computing power is always scarce" to "computing power might be in surplus," the massive accumulated paper profits became a direct driver of concentrated selling. As one of the most aggressively valued segments in the AI hardware supply chain, memory chips naturally became the primary target for profit-taking.

Why Meta Selling Computing Power Was Interpreted as a Signal of "Computing Power Surplus"

The market interpreted Meta's cloud business plan as a signal of "computing power surplus," supported by a complete logical chain.

First logic: Expectations of a peak in capital expenditures. Meta's 2026 capital expenditure guidance has reached $125 billion to $145 billion. In the first quarter of 2026, the combined CapEx of the four major North American cloud providers (Amazon, Microsoft, Google, Meta) was $130.6 billion, up about 70% year-over-year. Previously, the market had a high tolerance for tech giants' "unrestrained" AI capital spending, based on the core premise that "computing power is absolutely scarce"—as long as supply could not meet demand, any capital expenditure would find demand absorption. Meta's move to sell excess computing power directly shattered this belief.

Second logic: Concerns about a reversal in supply-demand dynamics. Rich Privorotsky, head of Goldman Sachs' 1-Delta desk, previously made a precise prediction: "The market's core premise has always been computing power scarcity. Once supply increases and leasing prices decline, the scarcity narrative will be directly overturned, and the hardware sector will be the first to feel the pain." Meta's move exactly validated this reasoning—when a top-tier cloud provider starts to "sell" computing power externally, it means internal computing power is already oversupplied, or at least structurally idle.

Third logic: Collapse of momentum trading strategies. The hardware sector crash directly triggered a comprehensive unraveling of momentum strategies. Goldman Sachs' high-beta momentum basket (mainly composed of chip and memory stocks) suffered a 9% single-day plunge after hitting record gains. This is essentially a classic crash scenario of crowded trades—when the narrative reverses, a large number of same-direction positions exit simultaneously, amplifying the decline.

Why Wall Street Is Deeply Divided on "Computing Power Surplus"

Although the market voted with its feet to sell hardware stocks, Wall Street institutions are far from united in their interpretation of this event.

The bearish camp is represented by Goldman Sachs. Its 1-Delta desk explicitly warned about the risk of disrupting the computing power scarcity narrative. UBS trader Christina Dwyer noted that the Meta report "shifts the narrative toward stronger financial discipline, alleviating concerns about continued rising CapEx," but the mention of "excess capacity" also casts doubt on underlying AI demand.

The bullish camp is represented by Nomura. Since the fourth quarter of 2025, Nomura has been tracking global new data center projects as a leading indicator for Asian semiconductor and hardware supply chains. The latest data shows that Nomura-tracked global new data center projects have increased from about 240 at the end of March to about 280, with GW-level projects rising from over 40 to about 50. Based on this, global incremental data center deployment capacity is expected to grow from 26GW in 2026 to 32GW in 2027, with an estimated 23GW still in 2028. Nomura thus concludes that the peak of AI infrastructure demand is still extending further out, not ending early.

Nomura further warns that the AI semiconductor cycle is far from its peak, and the second half of 2026 may see "epic" supply chain mismatches—as Nvidia's Rubin architecture and AWS Trainium 3 begin mass production in the second half of 2026, shortages of advanced packaging, PCBs, CCLs, and other components will drive a new round of price increases and earnings upgrades.

The core disagreement between the two views lies in: Is Meta's "surplus" a global surplus or a structural idle capacity? The bullish camp believes that Meta is still purchasing new GPUs on a large scale, and external enterprises are still paying a premium to acquire computing power. This looks more like a company's resource allocation optimization at a specific point in time, rather than a systemic turning point in industry demand.

How High Was the Valuation Bubble Before the SOX Plunge?

To understand this crash, we must return to a more fundamental dimension: valuation.

In the first half of 2026, the Philadelphia Semiconductor Index gained more than 80%. Before the crash, the SOX's P/E ratio was about 26 times expected earnings, far above the 10-year average of 19 times, and close to the recent high of 30 times set in 2024. In comparison, the Nasdaq 100 index had a P/E of 23 times, and the S&P 500 was at 20 times.

The valuation premium of the semiconductor sector was already at historical extremes. Against this backdrop, any marginal narrative change—whether or not it had a substantial fundamental impact—could trigger a large-scale valuation correction.

Michael Burry, the real-life inspiration for "The Big Short," disclosed his latest holdings the day before the crash. In addition to continuing his short positions against Nvidia, Applied Materials, Tesla, and the SOXX semiconductor ETF, he added Caterpillar to his short list for the first time. Burry pointed out that the Philadelphia Semiconductor Index was about 65% above its 200-day moving average, a situation that has only occurred once before in history—during the 2000 dot-com bubble. He publicly warned: "What is happening now looks more like the final stage of a bubble, not the beginning of a bull market."

Whether Burry's judgment is accurate remains to be seen over time, but this comparison is sufficient to show: even without Meta's news, the semiconductor sector's valuation was already at a level that needed to be "paid off."

How Macro Policy and Market Rotation Amplified Semiconductor Selling Pressure

The semiconductor sector crash was not an isolated event but the result of multiple macroeconomic factors converging.

Regarding Fed policy: Fed Chair Kevin Warsh stated at the European Central Bank's annual central bank forum on July 1 that upside risks to prices had eased in recent weeks, but he remained firmly committed to bringing inflation down to the 2% target. Warsh avoided questions about whether the July monetary policy meeting would result in a rate hike, emphasizing that he would not provide forward guidance on future interest rate policy. Data from LSEG shows that the market still prices at least one rate hike by the Fed this year. The high-interest-rate environment continues to exert pressure on the high-valuation tech hardware sector.

Regarding market rotation: The US stock market had already recorded significant gains in the first half of the year: the Dow Jones Industrial Average rose 8.9%, its best first-half performance since 2021; the S&P 500 gained 9.6%; and the Nasdaq climbed 12.8%. Jeff Kilburg, founder of KKM Financial, noted that "the great rotation has extended into the third quarter, with funds flowing out of recently profited tech stocks and continuing to pour into traditional blue-chip Dow stocks." As one of the biggest gainers in the first half, the semiconductor sector naturally became a primary direction for fund rotation.

Regarding macro data: US ADP private employment in June added 98k jobs, below market expectations. The June manufacturing PMI fell 0.7 points from the previous month to 53.3, below the expected 53.9. The marginal weakening of economic data further strengthened the momentum of funds shifting from risk assets to defensive sectors.

Has the AI Hardware Bull Market Truly Reached Its End?

Returning to the initial question: Is this crash the end of the bull market or a sharp mid-cycle correction?

From a fundamental perspective, the long-term growth logic for AI hardware demand has not been materially disproven. The continued growth of global data center projects, the supply-demand imbalance for AI chips, and the tight supply of memory chips—these structural drivers have not disappeared because of a single report about Meta. Just one week before the crash, Micron Technology delivered earnings with revenue up 346% and net profit up nearly 14-fold, along with a better-than-expected guidance for the next quarter. There are multiple hard constraints on the supply side of semiconductors, with new capacity typically taking 2-3 years to come online. The supply-demand imbalance for AI-related chips, memory, and equipment will likely persist through 2026-2027.

But from a market perspective, the digestion of the valuation bubble may take time. The SOX's P/E of 26 times expected earnings, the semiconductor sector's cumulative gain of over 80% in the first half, and Micron's year-to-date gain of over 260%—these numbers mean that even if the long-term logic remains intact, a meaningful correction in the short term is needed to digest valuations.

Rich Privorotsky, head of Goldman Sachs' Delta One desk, may have provided the most precise framework: "The first hyperscaler to hint at cutting spending will see its stock price rise, but its upstream supply chain will come under pressure." This judgment was validated with pinpoint accuracy on July 1—Meta rose nearly 10%, while chip stocks completely collapsed.

From this perspective, the July 1 crash looks more like a structural repricing within the AI investment cycle: The market's focus is shifting from solely building hardware infrastructure toward corporate free cash flow stability and computing power utilization. This does not mean the end of AI hardware investment, but rather that the market is starting to demand that hardware suppliers prove they can maintain growth and profitability as computing power transitions from "scarce" to "abundant."

Summary

On July 1, 2026, the Philadelphia Semiconductor Index plunged 6.27% in a single day, with Micron and SanDisk each falling over 10%, marking one of the most severe single-day corrections in the AI hardware bull market to date. Meta's plan to sell excess AI computing power shattered the market's core belief in "absolute computing power scarcity." Combined with the semiconductor sector's extremely high valuation levels, crowded momentum trading positions, and macroeconomic market rotation, all of this triggered the sell-off.

However, Wall Street is deeply divided. Institutions like Nomura believe the peak of AI infrastructure demand is far from over, with global data center projects continuing to expand rapidly. In contrast, Goldman Sachs and others warn that the disruption of the computing power scarcity narrative will put sustained pressure on the hardware sector. The clash between these two views will be further tested in the upcoming earnings season.

For investors, the July 1 crash provides an important observation window: Whether the long-term logic for AI hardware investment remains valid depends on whether the actual growth rate of computing power demand can continue to outpace supply expansion. This is not a question that can be answered overnight; it will need to be gradually verified over the next several quarters through CapEx data, computing power leasing prices, and corporate earnings reports.

Frequently Asked Questions (FAQ)

Q1: How much did the Philadelphia Semiconductor Index fall on July 1, 2026?

A: The Philadelphia Semiconductor Index (SOX) dropped 893.68 points in a single day, a decline of 6.27%, closing at 13,353.28 points.

Q2: What were the specific declines for Micron Technology and SanDisk?

A: Micron Technology (MU) fell 10.57%, and SanDisk (SNDK) dropped 10.62%. Intel fell 9.03%, and Applied Materials fell 9.97%.

Q3: What exactly is Meta planning to do that triggered this crash?

A: Meta is developing a plan for a cloud infrastructure business to sell AI computing power and model access to external customers, with the internal codename "Meta Compute." The market interpreted this as a signal that Meta's internal computing power is already in surplus, raising concerns that AI hardware demand has peaked.

Q4: What is the divergence among Wall Street institutions regarding this event?

A: Goldman Sachs and other institutions warn that the disruption of the computing power scarcity narrative will impact the hardware sector. Meanwhile, Nomura and others argue that the peak of AI infrastructure demand is far from over, with global data center projects still increasing, and they expect "epic" supply chain mismatches in the second half of 2026.

Q5: What was the valuation level of the semiconductor sector before the crash?

A: Before the crash, the Philadelphia Semiconductor Index's P/E ratio was about 26 times expected earnings, far above the 10-year average of 19 times. The index had accumulated gains of over 80% in the first half of 2026.

Q6: Does this crash mean the AI hardware bull market has ended?

A: There is no definitive conclusion yet. Long-term structural drivers for AI hardware demand have not disappeared, and global data center construction continues to accelerate. However, the short-term valuation bubble may need time to digest. The market is shifting from the narrative of "absolute computing power scarcity" toward a repricing of capital expenditure efficiency and computing power utilization.