Meta is preparing to sell part of its surplus artificial intelligence computing capacity, a shift that lifted its shares 8% at the close after gaining more than 10% intraday on July 1, while triggering sharp declines across the AI hardware and cloud ecosystem.
Shares of CoreWeave and Nebius dropped 13% and 17%, respectively, as traders reacted to the prospect of a major new competitor entering the market for leased computing power. The selloff extended into Asia, where South Korea’s KOSPI index fell about 7%, with Samsung Electronics and SK Hynix both sliding more than 8%.
Strategy targets unused infrastructure
According to sources, Meta plans to provide external clients with access to its AI capacity and could roll out a hosted model service similar to existing cloud-based AI platforms. The move is designed to monetize infrastructure built ahead of internal demand.
Meta had already raised its 2026 capital expenditure forecast to between $125 billion and $145 billion. By the end of the first quarter, the company reported $237.7 billion in non-cancelable contractual obligations, largely tied to servers, data centers, and networking equipment.
Capacity race highlights gap with rivals
Analysts estimate Meta will reach roughly 2 gigawatts of computing capacity by the end of 2025, expanding to about 5 gigawatts in 2026. That remains well below projections for Alphabet, Amazon, and Microsoft, each expected to exceed 20 gigawatts within the next three years.
Industry-wide spending continues to surge. Data from Bridgewater shows the four largest U.S. tech companies are expected to invest around $650 billion in AI infrastructure by 2026, up nearly 60% from $410 billion in 2025. Broader estimates place total global AI-related capital spending at about $800 billion in 2026.
Timing mismatch drives surplus
Meta’s decision reflects a short-term imbalance between long-term infrastructure expansion and slower internal adoption. Large-scale data centers take years to build, leaving the company with more capacity than its current models can fully utilize.
Similar strategies have emerged elsewhere. xAI recently leased access to its Colossus 1 cluster—equipped with more than 220,000 GPUs—to Anthropic for $1.25 billion per month, implying a valuation near $30 billion per gigawatt annually for high-performance compute.
Shockwaves across the supply chain
Market reaction points to shifting dynamics across the AI supply chain:
- Cloud providers dependent on Meta contracts may face weaker demand
- Chipmakers and equipment suppliers are seeing renewed volatility
- Pricing power built on rapid infrastructure expansion is being reassessed
The broader concern among traders is that the pace of technology capital expenditure growth could slow after two years of strong momentum driven by AI demand.
Lower compute costs could fuel software gains
At the same time, increased availability of computing resources may reduce training and deployment costs for developers. This could accelerate innovation at the application layer, shifting capital toward companies that can efficiently turn compute power into revenue.
Industry shifts toward efficiency and monetization
Despite the current imbalance, Meta’s 5 gigawatts of projected capacity remains modest relative to global expansion plans. Agreements involving Google and Anthropic alone represent roughly 5 gigawatts of future TPU supply, suggesting overall capacity will continue to grow.
Industry data indicates the issue is not structural oversupply but rather a mismatch between resource buildout and effective usage. The constraint is increasingly tied to developing models and products capable of generating sustainable returns from available compute.
Meta’s move signals a turning point as the AI sector transitions from aggressive hardware expansion to a phase focused on efficiency, monetization, and competitive differentiation.
For deeper insight into how AI shifts affect markets, explore our analysis in Today AI Moves Shake Markets.
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