Is the AI hype
cooling down?
A composite reading of physical build-out and platform economics. Higher means the expansion is still intensifying; lower means the momentum is fading. Here's what goes into it.
What the answer is built from
Five independent signals, each weighted by how directly it reflects real, committed demand. Each is scored from 0 (contracting) to 100 (surging).
The trajectory
Where the money and the megawatts are actually going.
Combined infrastructure spend, per quarter
Billions of dollarsSpend by operator
$B / quarterNew data-center power queued
Gigawatts / yearTotal new power capacity queued
Gigawatts / yearWhere data-center load is landing
GW in queue, top regionsThe latest print
The charts above now run through the June quarter, and up close none of the individual prints points to a cooldown. Alphabet went first on Jul 22, with cloud revenue up 82% and quarterly capex roughly doubled. Microsoft and Meta both reported Jul 29: Microsoft's Azure crossed a $100B annual run-rate and grew 43%, on a record $678B of contracted backlog; Meta's revenue rose 28%, but its capex surge pushed operating margin down to 31% and free cash flow to just $784M, the clearest sign yet that the build is overtaking the cash. Amazon closed the set on Jul 30: AWS reaccelerated to 37%, its fastest growth since 2021, quarterly capex jumped 68% to $54.2B, and management raised full-year 2026 capex guidance to $220B, pinning the increase on the same memory-price surge the bottleneck section below tracks. Across the four, June-quarter capex alone topped $170B. And a fifth name now joins from an unexpected direction: SpaceX, public since June's record $75B IPO, delivered its first results as a listed company on Aug 4. It is not a cloud operator, but it has made the boldest AI-infrastructure bet of all, and it showed: revenue nearly doubled, a new AI segment for its orbital data centers grew 247%, and quarterly capex jumped to $18.4B, sending the shares down about 8%.
Total revenue
$119.8B
+24% vs last year
Google Cloud revenue
$24.8B
+82% vs last year
Cloud operating income
$8.8B
up from $2.8B a year ago
Capex, this quarter
$44.9B
~+100% vs last year
Operating income
$40.8B
+30% · 34% margin
2026 capex guidance
$195–205B
raised from $180–190B
One caveat on Alphabet's headline: reported net income leapt to $112.1B and diluted EPS to $9.11 (both up roughly 295%), but that is flattered by a one-time $99B unrealized gain on equity investments, booked below the operating line. Operating income ($40.8B, +30%) is the clean read. Source: Alphabet Q2 2026 earnings release (quarter ended Jun 30, 2026), reported Jul 22, 2026.
Total revenue
$90.0B
+18% vs last year
Intelligent Cloud revenue
$39.3B
+32% vs last year
Azure revenue growth
+43%
past $100B annual run-rate
Capex, this quarter
$41B
incl. finance leases
Commercial backlog (RPO)
$678B
+84% vs last year
Next-quarter capex guide
>$50B
still climbing
Azure crossing a $100B annual run-rate and the $678B backlog are the demand signals; the $41B of quarterly capex (cash for property and equipment $35.8B plus $5.6B of finance leases) is the spend. GAAP diluted EPS of $4.81 (+32%) includes a $3.2B gain from marking up Microsoft's Anthropic stake, worth about $0.33. Management guided FY2027 capex to roughly $175B and over $50B next quarter. Source: Microsoft FQ4 FY2026 earnings release (quarter ended Jun 30, 2026), reported Jul 29, 2026.
Total revenue
$60.8B
+28% vs last year
Capex, this quarter
$31.1B
incl. finance-lease principal
2026 capex guidance
$130–145B
low end raised
Operating margin
31%
down from 43%
Free cash flow
$0.8B
down from $8.5B
Diluted EPS
$6.18
down 13% · missed
Meta is the sharpest illustration of this page's thesis: revenue still grew 28% to $60.8B, but a $31.1B quarterly capex bill cut operating income to $18.8B (31% margin, down from 43%), net income to $15.8B, and free cash flow to just $784M from $8.5B a year earlier. Shares fell about 7% after hours. Source: Meta Q2 2026 earnings release (quarter ended Jun 30, 2026), reported Jul 29, 2026.
Total revenue
$200.6B
+20% vs last year
AWS revenue
$42.2B
+37% · fastest since 2021
Capex, this quarter
$54.2B
+68% vs last year
Operating income
$27.5B
+43% · 14% margin
2026 capex guidance
~$220B
raised from ~$200B
Free cash flow (TTM)
−$7.6B
outflow as the build outpaces cash
Amazon's $62.6B net income and $5.75 diluted EPS are flattered by a $53.4B pre-tax gain on its Anthropic stake, booked below the operating line; operating income ($27.5B, +43%) is the clean read. The $54.2B of quarterly capex is purchases of property and equipment, and AWS growth of 37% ($42.2B) was its fastest since 2021. Andy Jassy raised full-year 2026 capex to about $220B, citing surging memory prices, and said even that will not meet the demand Amazon is seeing. Source: Amazon Q2 2026 earnings release (quarter ended Jun 30, 2026), reported Jul 30, 2026.
Total revenue
$7.8B
+92% vs last year · beat estimates
AI segment revenue
$2.6B
+247% · orbital compute & cloud
Capex, this quarter
$18.4B
+82% from Q1 · mostly AI & Starship
Loss from operations
−$143M
narrowed from −$970M
Adjusted EBITDA
$3.5B
+191% vs last year
Starlink subscribers
12M
doubled · $4.3B segment rev, +66%
SpaceX is the outlier here, on the page for one reason: it has made the most audacious AI-infrastructure bet of all, and its first report as a public company put numbers on it. Revenue nearly doubled to $7.8B (beating estimates), the net loss narrowed to $541M, and adjusted EBITDA reached $3.5B. The eye-catching line is the new AI segment, the early revenue from its plan to put data centers in orbit: $2.6B in the quarter, up 247%, against a $1.26B operating loss, and $14.1B of contracted AI cloud sales sit within a $47.5B total backlog. Starlink remains the cash engine, now 12M subscribers (doubled year over year) throwing off $1.66B of segment operating income, even as ARPU fell 22% on cheaper international plans. But capex is what moved the stock: $18.4B in a single quarter, up from $10.1B in Q1 and mostly AI compute and Starship, which sent the shares down about 8% after hours despite the beat. The orbital build that revenue only hints at is enormous: the AI1 satellite (a 150 kW compute payload, unveiled Jun 8, 2026), more than 1,000 a year from the Gigasat factory by late 2027, an FCC filing for up to a million satellites and as much as 100 GW, plus a 10 GW solar plant in Bastrop, Texas and a roughly $55B "Terafab" chip fab. Sources: SpaceX Q2 2026 earnings release (quarter ended Jun 30, 2026), reported Aug 4, 2026, and reporting from CNBC and Yahoo Finance.
Funding the build-out
The spending is enormous, but is it being paid for out of pocket or on credit? The cash-flow statements answer that. Between them the five operators throw off about $692B of operating cash a year and are now plowing roughly four-fifths of it straight back into capex. The giants still generate tens of billions in free cash flow after they spend; but at the frontier the build has overtaken the cash, and Amazon and Oracle are now spending more than they earn, filling the gap from reserves and debt.
Operating cash flow, capex & free cash flow, combined
$B · fiscal years 2020–2025Summed across all five operators. Operating cash flow keeps hitting records, but capex is accelerating faster: combined free cash flow peaked near $246B in 2024 and slipped to about $198B in 2025 even as operating cash flow set a high, and the latest snapshot (~$126B TTM) extends that slide.
Snapshot view: trailing twelve months from the operators’ cash-flow statements. History view: annual fiscal-year figures combined across the five (2021–2025 from filings via stockanalysis.com, 2020 from company 10-Ks). Free cash flow here is simply operating cash flow minus purchases of property and equipment; companies’ own free-cash-flow measures differ and can fall on either side of the simple figure shown here: Amazon reports a smaller trailing-twelve-month outflow (about −$7.6B) because it nets proceeds from equipment sales and incentives out of capex, whereas counting finance-lease payments would push the figure the other way. Amazon’s capex also mixes AWS with retail logistics. Fiscal years are offset for Microsoft (ends June) and Oracle (ends May); snapshot periods end Jun 30, 2026 except Oracle (May 31, 2026). Illustrative, not investment advice. Sources: company 10-Q / 10-K cash-flow statements via stockanalysis.com (2020–2026).
The microscalers
The hyperscalers are not the only ones building. A second tier has grown up beneath them: specialist GPU clouds like CoreWeave, Nebius, Crusoe and Lambda that do essentially one thing, rent out Nvidia accelerators at scale. Call them microscalers, or neoclouds. They own no consumer platform and throw off almost no cash flow of their own, so they borrow against the chips themselves and pre-sell the capacity on multiyear contracts, then plow the proceeds straight back into more chips. Their capex curve is the steepest on this page, and their customer lists read like a directory of the AI labs, plus the hyperscalers who still cannot build fast enough on their own.
Capex: the neoclouds and the converted miners
$B · 2023–2026 · dashed = estimatedCoreWeave alone still out-spends the entire rest of the field, and its curve is steeper than any single hyperscaler's early ramp. The converted miners (IREN, Applied Digital, Core Scientific, TeraWulf, Cipher) enter only in 2025, when their AI pivots began, and are drawn fully dashed because their numbers are total company capex that blends mining and AI, much of it customer financed, on fiscal years that do not line up with the calendar. IREN is the outlier: its 2026 spike is the roughly $5.8B of Microsoft GPUs plus further orders. Solid lines are CoreWeave and Nebius reported figures through 2025; every dashed point is guidance or an estimate. The private neoclouds (Crusoe, Lambda, Together) still do not disclose capex, so they are not plotted.
Who they build for
This is the part that ties the neoclouds back to the frontier. The capacity is not speculative: most of it is pre-sold to named AI labs and to the hyperscalers themselves, who rent burst compute from the neoclouds rather than wait on their own construction.
The converted miners
A whole cohort of former Bitcoin miners has worked out that its real asset was never the hashrate, it was the powered land: gigawatts of grid interconnection and cheap energy that now take years for anyone else to permit. Most of them do not build a cloud of their own; they lease that capacity to the neoclouds and hyperscalers, increasingly with Google or Nvidia backstopping the financing. It is the same chokepoint the "shells, land and interconnection" card further down tracks, seen from the supply side. IREN is the exception that went all the way and now runs its own GPU cloud.
Two names sit behind almost everything here: OpenAI on the demand side and Nvidia on the supply-and-financing side, the same loop the funding section flags, since Nvidia invests in the neoclouds that buy its chips to serve the labs it also backs. The converted miners add a second version of that loop, with Google and Nvidia backstopping the leases and taking equity in the very hosts they rent from. The conspicuous absence is Anthropic, which leans on Google TPUs and Amazon Trainium rather than renting neocloud GPUs, so this tier tilts heavily toward OpenAI and the open-model world.
Microscaler here means a specialist GPU cloud (also called a neocloud), distinct from the hyperscalers above. Capex: CoreWeave and Nebius from company filings and guidance (CoreWeave 2025 capex guided to about $20–23B); the 2026 points are guidance or estimates and are drawn dashed. Crusoe, Lambda and Together are private, so no capex line is shown for them; their entries reflect disclosed funding rounds and announced customer deals. Converted-miner figures are from company announcements: IREN's ~$9.7B Microsoft cloud deal (Nov 2025), Applied Digital's ~$11B CoreWeave leases at Ellendale, Core Scientific hosting CoreWeave after its holders rejected CoreWeave's buyout (Oct 2025), and the Google-backstopped Fluidstack leases at TeraWulf and Cipher. The converted miners' capex points on the chart above (2025 and 2026, dashed) are editorial estimates of total company capex, not reported AI-only figures, since these companies report on differing fiscal years and blend mining with AI spend; much of that spend is customer financed. Contract and backlog figures are the parties' announced numbers, are multi-year lifetime totals rather than annual, and can include options and later phases. Illustrative, not investment advice.
The picks and shovels
The hyperscalers get the headlines, but the chipmakers, memory houses and foundries behind them are in a capex super-cycle of their own, together laying out well over $130B a year to build the fabs, HBM lines and tools the AI build-out physically runs on. Trace that capital back through their filings and you can see exactly how the build-out got here.
The multi-year climb in chip capex
Annual capex, $B · 2019–2025One line per filing trail (10-K / 20-F / 6-K). Memory (SK Hynix, Micron) shows the deep 2023 downturn cut and then the HBM-driven surge; TSMC keeps setting records; Intel is the one line bending down, pacing its foundry build to demand.
Annual capital expenditure compiled from company filings (10-K / 20-F / 6-K and quarterly reports); the latest point is FY2025 guidance, earlier points are reported actuals, converted to USD at period rates. Fiscal years and treatment differ (Micron’s ends in August; Intel’s figures are gross additions, before the partner offsets and CHIPS grants that lower net capex materially). “Samsung” is its semiconductor (DS) division. CXMT only began reporting publicly with its July 2026 Shanghai listing, so its bar is the 2026 equipment-procurement plan rather than an audited capex history, and it is absent from the 2019–2025 chart above for the same reason. Two kinds of company carry small capex by design and should not be read as small spenders: equipment makers, whose revenue is the mirror of everyone else’s capex, and fabless designers (AMD, Broadcom, Nvidia), who buy foundry capacity instead of building it, so R&D is the figure that matters and their volume lands on TSMC’s capex line. Illustrative, not investment advice. Sources: company filings & investor releases (2019–2025).
The sovereign money
It isn't only US hyperscalers writing the checks anymore. Governments and sovereign wealth funds now treat AI compute as strategic infrastructure, and have pledged hundreds of billions to build it, buy into it, or avoid being left behind. Here's who's committing what, and how each region's playbook differs.
Headline announcements, not deployed cash, a mix of state programs, sovereign wealth funds and public-private ventures, so they aren't strictly comparable (European figures overlap; * South Korea's cluster runs to 2047). Illustrative, not investment advice. Sources: government announcements, Global SWF, IEA and press reporting (2024–2026).
Where it could actually jam
Demand is only half the story. Even with the money flowing, the build-out slams into hard limits, from the accelerator itself (a market chokepoint as much as a physical one), through raw silicon and the machines that pattern it, packaging, passives, optics and the network fabric, out to water, power, the skilled trades who build it, and the export politics that can throttle any link overnight. Here's how binding each chokepoint becomes year by year through 2030, and the companies with the most leverage over it.
Company names indicate supply-chain exposure to each bottleneck, illustrative, not investment advice. Trajectory synthesized from IEA, McKinsey, SemiAnalysis, TrendForce, Yole, SK Group and industry commentary (2024–2026).
How the chokepoints connect
The same constraints, drawn as a supply chain instead of a list. At the center sit the buyers, the frontier labs and the hyperscalers that host them. They buy accelerators; the accelerators are printed by a foundry and fed by stacked memory; the foundry runs on lithography, masks and materials; the racks need boards, optics and power; the sites need grid, water and people. Each bubble is one market. Its color is how binding that link is in the year you pick below, anywhere from 2024 to 2030; its size is how concentrated the market is, the share held by the single largest supplier. Tap any bubble to see who dominates it.
A schematic of the primary buy-and-supply links, not every relationship. Color follows the selected year's column of the trajectories above; concentration is the estimated share of the largest supplier in each chokepoint, an order of magnitude rather than a precise split. Dashed links (capital, export controls) gate the whole flow rather than feeding one node.
What the bottlenecks paid
A thought experiment to close on. Take the flagship company behind each of the hardest chokepoints above, one name per bottleneck, put an equal amount of money into each a year ago and hold. Here is how that basket of picks-and-shovels would have done against the S&P 500 over the last twelve months.
Equal-weight basket · 1yr
+141%
7 bottleneck bellwethers, held 12 mo
S&P 500 · same window
+19.5%
the basket beat it by ~7×
Leader · Micron
+628%
the HBM / DRAM squeeze
Laggard · Nvidia
+11%
the one name below the S&P
Hypothetical and illustrative, not investment advice. Equal-weight means an equal dollar amount in each of the seven names a year ago, held without rebalancing; figures are price return only (excluding dividends) over the 52 weeks to Jul 31, 2026. The average is pulled sharply upward by Micron's memory-shortage run: the median name returned about +68%, still well ahead of the S&P 500's +19.5% (the Nasdaq-100 returned about the same). The line worth staring at is at the bottom. Nvidia, the face of the whole trade, trailed the index, because over this particular year the binding constraint, and the money, moved downstream to memory, power and the tools. Which is the point of the section above: the bottleneck keeps moving. Source: 52-week price change per stockanalysis.com, as of Jul 31, 2026.