TL;DR · 30-second read
The Short Version
Meta, the company behind Facebook and Instagram, now expects to spend between $130 billion and $145 billion this year. The cost of the huge computer buildings that power artificial intelligence keeps climbing. This is the second time this year Meta has raised that figure.
The bill is biting. In the latest three months, the cash Meta had left after all its spending shrank to $784 million, from $8.5 billion a year earlier. Its shares fell about 10 percent.
The twist: other companies are offering to pay Meta more than it paid for its computing power. Meta may start renting that power out.
Meta has raised its 2026 capital expenditure guidance to between $130bn and $145bn, DatacenterDynamics reported on August 2, 2026. The range had been $115bn–$135bn at the start of the year and $125bn–$145bn in April. The increase comes as AI data center costs rise. In the same week, Amazon lifted its own capex guidance by $20bn and cited the cost of memory for AI servers.
Meta shares fell around 10 percent. Quarterly free cash flow dropped to $784m, its lowest level in five years, compared with $8.5bn a year earlier. Revenue rose 28 percent to $61bn and profit fell 14 percent to $6bn. Meta again confirmed its interest in becoming a cloud provider. It recently hired AWS cloud lead David Brown, and it is reportedly in early talks to rent compute to Anthropic in a deal that could be worth as much as $10bn.
Executive Summary
Meta now expects to spend $130bn to $145bn this year on capital projects, the long-lived assets such as AI servers, data center buildings and the electrical and cooling systems that support them. This is the second upward revision of 2026. The midpoint of the range has risen from $125bn at the start of the year to $137.5bn. The latest step lifts the bottom of the range and leaves the $145bn ceiling set in April unchanged.
The spending is now visibly squeezing Meta’s cash generation. Free cash flow of $784m for the quarter was a fraction of the $8.5bn Meta generated a year earlier, and the stock fell around 10 percent. Amazon’s shares rose after its own capex increase. The difference shows that investors distinguish between AI spending that feeds an existing cloud business and AI spending whose return is still prospective.
The bigger strategic signal is Mark Zuckerberg’s remark that Meta is receiving offers for its compute “at a significant premium over what we paid for it.” Three things point the same way: that remark, a senior cloud hire from AWS, and reported talks with Anthropic. Together they suggest Meta’s AI fleet may become a product it sells as well as a cost it carries. That would matter for AI developers hunting for capacity, for incumbent clouds, and for the suppliers who build and power data centers.
The Raise Lands at the Floor, Not the Ceiling
Meta’s new range of $130bn to $145bn is its second upward revision of 2026. The year opened at $115bn–$135bn, and April’s update moved it to $125bn–$145bn. This time the top of the range held at $145bn and the bottom rose by $5bn. Since the start of the year, the midpoint has climbed from $125bn to $137.5bn, an increase of $12.5bn or 10 percent. The latest step, however, is a narrowing. Meta is signalling that it is less likely to land at the low end. It is not signalling that it has found room to go higher.
The increase comes as AI data center costs rise. In the same week, Amazon raised its guidance by $20bn and pointed specifically to the price of memory for AI servers. That context matters for how the number is read. Capital expenditure can rise because a company is building more. It can also rise because each unit it builds costs more. Meta has not said how its increase splits between the two. Amazon’s explanation is a reminder that at least part of the industry’s recent guidance creep reflects price rather than volume.
Why Meta’s Data Centers Start to Look Like a Cloud Business
The most consequential line from the earnings call was not the capex figure. It was Zuckerberg’s observation that Meta is “getting a lot of offers for compute at a significant premium over what we paid for it.” Compute here means the processing capacity of Meta’s AI server fleet. If outside buyers will pay more than Meta’s cost for that capacity, every server Meta installs has two possible uses. It can train and run Meta’s own models, or it can be rented to someone else at a margin. That shifts the capex line from pure cost toward something closer to inventory.
Meta has taken steps consistent with acting on that. It again confirmed its interest in becoming a cloud provider, it recently hired AWS cloud lead David Brown, and it is reportedly in early talks to rent compute to Anthropic. That deal could be worth as much as $10bn. For scale, $10bn is roughly 7 percent of the low end of this year’s capex range. That is meaningful, but a single deal of that size would not by itself change the investment case, and the talks are described as early.
The effects would reach both sides of the market. AI developers that cannot secure enough capacity from established clouds would gain another large supplier. Incumbent cloud providers would face a competitor whose capacity was financed by an advertising business rather than by cloud customers. Data center developers and equipment vendors could find Meta’s demand extending beyond what its own apps require. None of this is settled. Running a cloud business requires customer contracts, service-level commitments, support and sales functions that Meta has not historically built. The direction, though, is visible in what the company has said and done.
Why Investors Treated Meta and Amazon Differently
Amazon raised its guidance and its shares jumped. Meta raised its guidance and its shares fell around 10 percent. The cash figures help explain the gap. Free cash flow is the cash left after operating costs and capital spending. Meta’s was $784m for the quarter, its lowest level in five years, against $8.5bn a year earlier. Revenue grew 28 percent to $61bn, but profit fell 14 percent to $6bn, so costs are growing faster than sales.
One reasonable reading of the split reaction is about visibility. Amazon’s spending feeds a business that already sells computing capacity to customers, so investors can see where the return comes from. Meta’s spending serves its own products, and much of the payoff depends on AI products that Zuckerberg described as “coming.” Meta’s third-quarter revenue forecast of $61bn to $64bn has a midpoint of $62.5bn, below the $63.1bn Wall Street expected, so it offered little near-term offset. Renting out capacity is one way Meta could make the return on its data centers easier to see. That is another reason the cloud ambition and the capex number belong in the same story.
What the Spending Means Down the Supply Chain
For suppliers of power, cooling and construction, guidance at this level signals sustained demand from one of the largest private buyers of data center infrastructure. For a transformer maker or a cooling vendor, though, the useful question is not the dollar total. It is how many megawatts of capacity the money buys, on what timetable, and where. Meta has not broken that out. And if more of each dollar is going to pricier components such as memory, then $137.5bn buys less physical build-out than the same sum would have a year ago.
A cloud push would add another layer. Capacity built for external customers generally has to meet those customers’ expectations for reliability and connectivity. It could also extend Meta’s need for sites, power and cooling beyond its internal requirements. Until Meta says how much capacity it intends to offer to others, suppliers can plan only against the capex range.
Background
Meta Platforms, founded by Mark Zuckerberg as Facebook, owns Facebook, Instagram and WhatsApp. It is one of a handful of “hyperscalers,” companies that design and operate their own data centers at enormous scale. Unlike Amazon Web Services, Microsoft Azure or Google Cloud, Meta has historically built that capacity only for its own apps and advertising systems. It has not rented it to outside customers.
The race to build artificial intelligence has changed the scale of that spending. Training and running large AI models requires dense clusters of specialized servers, along with the electricity, cooling and networking to support them. That has made capex guidance from Meta, Amazon and their peers one of the most closely watched demand signals for chipmakers, memory suppliers, data center developers and utilities. Source: Meta boosts AI data center capex, forecasts $130-145bn spend — DatacenterDynamics on Meta’s raised 2026 capital expenditure guidance, second-quarter results and cloud ambitions.Sources