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Meta is spending at hyperscaler scale: it reported $69.69 billion in 2025 purchases of property and equipment and guided to approximately $115 billion to $135 billion in 2026 capital expenditures. That 2026 range supports both AI efforts and Meta’s core business, so it is not an AI-only budget. The closest four-company 2026 comparison available is a dated FactSet consensus estimate reproduced by Morningstar: Amazon $127.551 billion, Meta $96.972 billion, Microsoft $95.991 billion, and Alphabet (Google) $92.904 billion. Those estimates are not company guidance, and they do not line up neatly with company disclosures.
How much is Meta spending on AI infrastructure?
Meta reported $69.69 billion in 2025 purchases of property and equipment, largely covering servers, data centers, and network infrastructure. For 2026, it guided to approximately $115 billion to $135 billion in capital expenditures to support “our AI efforts and core business.” The filing’s wording matters: Meta has not presented that whole range as spending exclusively on AI.
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The 2025 figure is a reported amount for property and equipment; the 2026 range is forward-looking company guidance using the broader capital-expenditure label. They are useful for showing scale and direction, but they are not identical measurements. Meta’s guidance also includes the infrastructure needed to operate its existing services, not only facilities or equipment assigned to AI.
Which company is spending the most: Meta, Google, Microsoft, or Amazon?
There is no dependable single ranking unless the figures use the same period and accounting definition. In Morningstar’s reproduction of FactSet consensus as of October 29, 2025, Amazon had the largest 2026 estimate among the four. Company disclosures tell a different and less directly comparable story: Meta gave a $115 billion–$135 billion range, Alphabet reported 2025 actual spending, and Microsoft’s later 2026 expectation was revised after a lease reclassification.
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| Company | Reported actual | 2026 outlook or estimate | What the figure measures and how to read it |
|---|---|---|---|
| Meta | $69.69 billion in 2025 purchases of property and equipment | Company guidance: approximately $115 billion–$135 billion. FactSet consensus reproduced by Morningstar: $96.972 billion, as of October 29, 2025. | The guidance covers AI efforts and the core business; it is not an AI-only figure. The consensus estimate is a separate, dated external estimate. |
| Alphabet (Google) | $91.4 billion in 2025 capital expenditures | FactSet consensus reproduced by Morningstar: $92.904 billion, as of October 29, 2025. Alphabet said 2026 technical-infrastructure investment would increase significantly, without specifying a total in the cited filing. | The filing reports an actual and a qualitative forward outlook. Do not treat the consensus estimate as company guidance. |
| Microsoft | FY2026 Q4: $41 billion of capex, including $35.8 billion of cash property-and-equipment purchases | Approximately $175 billion for calendar 2026 after a lease reclassification in the later Q4 call. FactSet consensus reproduced by Morningstar: $95.991 billion, as of October 29, 2025. | The quarterly capex figure includes finance leases; cash purchases are a narrower measure. The company expectation and the dated consensus estimate are distinct series. |
| Amazon | Not stated in the cited figures. | FactSet consensus reproduced by Morningstar: $127.551 billion, as of October 29, 2025. | This is an external estimate, not Amazon guidance. The cited material does not provide a corresponding actual or company forecast for a like-for-like table. |
The Morningstar/FactSet figures put Amazon first in that particular estimate set, with Meta, Microsoft, and Alphabet following. But they are estimates from one point in time, not audited spending totals or a current company-by-company commitment. They also should not be used to overrule Meta’s separate $115 billion–$135 billion company-guidance range: the two numbers are different sources and series, and the consensus estimate is dated October 29, 2025.
For comparison, Meta’s guidance and Microsoft’s revised calendar-2026 expectation are company outlooks, while Amazon’s listed figure is only consensus in the cited material. Alphabet’s stated 2026 outlook says investment will rise significantly but provides no amount. Treating all four as equally firm “budgets” would overstate what is known.
How do the reported AI spending numbers differ?
They vary because “capex” can describe different things, and because companies disclose total infrastructure spending rather than a consistent AI-only subtotal. Four distinctions explain most of the apparent conflicts.
Actual spending versus forecasts
A reported actual describes spending already recorded for a completed period. Guidance is management’s forward-looking expectation, while analyst consensus aggregates outside estimates. Alphabet’s $91.4 billion is a 2025 actual; Meta’s $115 billion–$135 billion is company guidance for 2026; Amazon’s $127.551 billion is a FactSet consensus estimate reproduced by Morningstar. These figures do not have the same evidentiary status.
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Cash property purchases versus broader capex
Microsoft’s FY2026 Q4 call reported $41 billion in capex and $35.8 billion in cash purchases of property and equipment. The difference reflects the broader capex measure’s inclusion of finance leases. Comparing Microsoft’s broader total with another company’s cash property-and-equipment purchases can make Microsoft appear larger even when the comparison is not measuring the same type of commitment.
Total infrastructure versus AI-attributed spending
Meta explicitly said its 2026 capex would support AI efforts and the core business. Alphabet said the vast majority of its capex was invested in technical infrastructure, but that statement does not make the full amount an AI-only allocation. Server capacity, data centers, and networks can support multiple products and workloads; the cited company figures do not provide a standardized allocation that isolates AI spending across all four companies.
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Calendar years versus fiscal years
Microsoft reports results on a fiscal-year schedule, while its approximately $175 billion expectation is for calendar 2026. Its FY2026 Q4 quarterly capex figure is not a calendar-year total. Meta, Alphabet, and the consensus estimates are presented here with their stated annual periods, but period labels still need to be checked before comparing any number outside this table.
Why did Microsoft’s 2026 capex outlook move from about $190 billion to $175 billion?
Microsoft’s FY2026 Q3 call expected roughly $190 billion in calendar-2026 capex. Its later FY2026 Q4 call said the expectation was approximately $175 billion after a lease reclassification. That change is an accounting presentation adjustment; by itself, it does not demonstrate an equivalent reduction in Microsoft’s physical infrastructure plans.
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The Q4 call also said roughly two-thirds of capex was for short-lived assets, primarily CPUs and GPUs. That is useful context for interpreting the total: a large share is equipment with a different useful-life profile from long-lived data-center buildings and infrastructure. The call’s $41 billion quarterly capex and $35.8 billion cash property-and-equipment purchases likewise show why the label attached to a figure matters.
For a reader comparing investment intensity, the revised approximately $175 billion figure is Microsoft’s later stated calendar-2026 expectation in the cited calls. The earlier approximately $190 billion figure should not be presented as though it remained the latest outlook, nor should the difference be described as a straightforward cut in physical buildout.
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Alphabet’s 2025 filing reports $91.4 billion in capex and says technical-infrastructure investment will increase significantly in 2026. In its Q2 2025 call, Alphabet had already raised its 2025 outlook to approximately $85 billion and said demand for cloud capacity remained tight. The later filing’s $91.4 billion actual is the relevant reported 2025 total; the earlier outlook illustrates that forecasts can change as infrastructure needs and spending develop.
Amazon’s $127.551 billion 2026 figure is a FactSet consensus estimate reproduced by Morningstar using data as of October 29, 2025. It places Amazon at the top of that specific four-company estimate set, but it is not Amazon’s own announced spending plan. The cited material does not supply an Amazon company-guidance figure that can be placed beside Meta’s range or Microsoft’s outlook on equal terms.
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Stanford’s AI Index 2026 adds broader trend context: it says Google and Amazon led annual capex among major hyperscalers in 2025 and shows hyperscaler annual capex more than doubling since ChatGPT’s release. Its chart marks 2025 and 2026 values as estimates, so it is useful for the direction and scale of the infrastructure race, not as a substitute for company filings or a precise audited ranking.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Is the whole $720 billion for AI?
No. The Associated Press summarized the four companies’ 2026 plans as up to $720 billion, primarily for AI data centers. “Up to” describes a combined upper-end summary, and “primarily” does not mean exclusively. The total is useful context for how much the largest cloud and technology companies may invest, but it is not a single audited accounting measure.
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Why are these companies spending so much on infrastructure?
The spending is a capacity race as well as a software investment. The cited reporting identifies data-center land, energy, networking, and chip supply as constraints facing all four companies. Building or equipping a data center depends on securing several of these inputs together: additional servers do not create usable capacity if power, networking, or suitable sites are unavailable.
Alphabet’s statement that cloud-capacity demand remained tight offers one concrete indication of why investment continues. Stanford’s trend analysis likewise shows hyperscaler capex rising sharply after ChatGPT’s release. These facts establish growing infrastructure demand, but the spending totals alone do not show how quickly each company will turn new investment into usable capacity or revenue.
How should you compare the figures without mixing them up?
Use the disclosure that best matches the question, and keep the year, accounting definition, and source attached to every number. A quick comparison should identify whether a figure is an actual or forecast, whether it includes leases, and whether the company attributes it to AI alone or to broader infrastructure and business needs.
- For spending already recorded: use reported actuals such as Meta’s $69.69 billion in 2025 property-and-equipment purchases or Alphabet’s $91.4 billion in 2025 capex, while retaining each company’s stated measure.
- For what management expects to spend: use company guidance or outlook, such as Meta’s approximately $115 billion–$135 billion for 2026 and Microsoft’s revised approximately $175 billion calendar-2026 expectation.
- For a four-company estimate set: use the Morningstar-reproduced FactSet consensus figures only with their October 29, 2025 date and label them estimates, not company commitments.
- For an AI-only comparison: do not assume total capex is AI spending. The cited figures do not provide a consistent AI-only allocation across Meta, Alphabet, Microsoft, and Amazon.
The practical conclusion is that Meta’s planned spend is enormous, but no single table of mixed company disclosures can prove which firm is investing the most in AI alone. The most defensible comparison keeps actuals, company outlooks, and dated analyst estimates in separate categories.
Frequently Asked Questions
Does higher AI infrastructure spending mean a company has a better AI product?
Not by itself. Capex records investment in assets and infrastructure, not model quality, customer adoption, reliability, or the return those assets eventually generate.
Are these spending figures the same as the companies’ AI research budgets?
No. The figures discussed are capital expenditures or property-and-equipment purchases, not a complete accounting of research-and-development expense, employee costs, or other operating costs.
Can I use these figures to calculate which company gets the best return on AI spending?
Not from these disclosures alone. A return comparison would also require a consistent measure of AI-related revenue and costs, attribution rules, and a time period that accounts for when infrastructure enters service.
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