AI Capex Peak: Demand and Contract Commitments 2026

The post-Q3 2026 demand picture is real, but it is not one number. The hard commitments are multi-year volume contracts with deposits and price bands at the memory makers. The “sold out through 2029” and “$1 trillion visibility” lines mix those contracts with negotiations and customer forecasts. Hyperscaler capex levels are still rising into 2027; what is peaking, on Goldman’s reading, is the growth rate of that spending as a share of GDP.

Memory contracts are binding; the 2029 sellout is only partly so

Micron’s book is the cleanest contractual evidence in the industry. As of its September 30, 2026 fiscal Q4 call, it had 26 strategic customer agreements, up from 16 a quarter earlier, covering more than 35% of estimated revenue through 2030, with some deals and extensions running into 2031. All 26 include take-or-pay volume commitments. Remaining performance obligations tied to those agreements were about $150 billion, calculated at minimum prices, so recognized revenue over the life of the deals is expected to be higher. Customer financial commitments reached $32 billion, mostly cash deposits, and contract liabilities on the balance sheet were $12.9 billion, up from $568 million in May. Three-quarters of expected SCA revenue sits inside a defined pricing framework, mostly floor-and-ceiling bands; the rest is repriced periodically at market. Management said that even at floor prices, gross margins on the banded agreements would be meaningfully above prior-cycle quarterly peaks. Combining SCAs with other customer commitments, more than 75% of fiscal 2027 output was already secured. That is prepayment, volume obligation, and a price floor—not a verbal claim. [1] [2] [3] [4]

SK hynix’s October 28 call is stronger on volume coverage and weaker on enforceability disclosure. The company has signed long-term agreements with 14 key customers, including global cloud providers, up from 10 in Q2. Those LTAs are typically five years, cover more than 50% of planned 2027 and 2028 production capacity, and use a price range that reflects market conditions rather than a single fixed price. The company said it has included safeguards such as deposits so that purchase plans become orders and shipments. The headline—“DRAM and HBM volumes through 2029 are effectively sold out”—explicitly combines already-signed LTA volumes with demand still under detailed discussion. Management said the volumes under discussion are based on specific purchasing plans and have a high likelihood of materializing. That second half is not yet a contract. Separately, CFO Kim Woo-hyun projected that supply will lag demand through 2030 because of process complexity and fab lead times, and the company said customer volume requirements are more than double what it can supply today. Those are outlook statements, not take-or-pay. SK hynix has not disclosed a Micron-style remaining-performance-obligation dollar figure or a cash-deposit total. [5] [6] [7] [8] [9]

For anyone trying to underwrite the cycle, the distinction matters. Micron has put a floor under a minority of revenue (a bit over a quarter through 2030 once the market-priced quarter of SCA revenue is stripped out) and collected cash against it. SK hynix has locked more than half of 2027–28 capacity into volume agreements with deposit language and a price band, then described 2029 as sold out only after adding negotiations. Neither has contracted the entire industry’s output, and neither’s price mechanism fully freezes today’s spot price for the whole book.

Nvidia’s “backlog” is mostly other people’s plans, plus its own supply bets

Nvidia has not yet reported the quarter that covers calendar Q3. Fiscal Q3 FY2027 is scheduled for November 17, 2026. The latest official visibility statements are from the August 26 fiscal Q2 call. [10] [11]

Three different things are often collapsed into “Nvidia backlog”:

• Customer demand visibility. Jensen Huang has described “$500 billion of very high confidence demand and purchase orders” for Blackwell and Rubin through 2026, and “at least $1 trillion” of cumulative Blackwell and Rubin revenue from calendar 2025 through calendar 2027. CFO Colette Kress has said the company has “full confidence” in that $1 trillion figure. Investor materials treat this as a forward-looking estimate, not GAAP backlog, not recognized revenue, and not a fully non-cancellable order book. How much is shipped, firm, or still a customer plan is not broken out. [12] [13]
• Cloud industry backlog, which is not Nvidia’s order book. On the August call Kress said cloud industry backlog was greater than $2 trillion, and that capex by the top five hyperscalers was expected to reach nearly $800 billion in 2026 and $1.3 trillion in 2027. That is a statement about customers’ contracted cloud demand and their spending plans. [14] [15]
• Nvidia’s own upstream commitments. As of July 26, advance purchase orders and pledges to suppliers—dominated by high-bandwidth memory—stood at $279 billion, up from $119 billion a quarter earlier. Some of those supply commitments can be adjusted or canceled. This is Nvidia locking memory and components, not customers locking Nvidia. [16] [17] [18]

What is closer to a purchase order: production shipments of Vera Rubin began in August 2026, management said it already had purchase orders from every major hyperscaler, AI cloud, and system maker, and it expected Rubin to be about 20% of data-center revenue in fiscal Q3. AWS is deploying an additional 2 million Nvidia GPUs from fiscal Q3 2027 through fiscal Q2 2029. Management guided roughly 70% revenue growth in fiscal 2028 and said customers’ own forecasts imply faster growth, with supply—especially memory—the constraint. Huang has said demand is higher than the 70% figure. [19] [20] [18]

The implication for a competitor or a supplier: Nvidia’s revenue path is still gated by memory and power, not by a lack of stated customer intent. The $1 trillion and $2 trillion figures should not be modeled as firm, non-cancellable chip orders.

Capex levels are still going up; Microsoft’s lower guide is a timing slip

The four companies do not report capex the same way. Amazon guides cash purchases of property and equipment. Alphabet reports purchases of property and equipment. Microsoft and Meta include finance-lease principal in the figure they discuss as capex. None publishes a clean AI-only line. Adding the latest 2026 guides produces about $720 billion to $740 billion: Amazon about $220 billion, Alphabet $195–205 billion, Microsoft about $170 billion for the calendar year, Meta $135–145 billion. That is roughly 78% above combined 2025 spending of about $410–414 billion, depending on the compilation. It is a level comparison, not a claim that the growth rate is still accelerating. [21] [22] [23]

Company by company after the October prints:

• Amazon reaffirmed about $220 billion of 2026 cash capex. Q3 purchases of property and equipment were $77.3 billion, versus $35.1 billion a year earlier. On the October 29 call, CEO Andy Jassy said the company expects to spend “meaningfully more in 2027,” with a line of sight to returns, and that AWS can grow north of 40% in both 2027 and 2028. There is no 2027 dollar guide. A separate, earlier verbal claim—on an October 23 podcast—was that 2027 AWS capacity is “largely sold out” for the large blocks, with a good chunk of 2028 also spoken for, while some capacity is held back for on-demand EC2 and Bedrock. That is a utilization statement, not a disclosed take-or-pay schedule. [24] [25] [26]
• Alphabet held 2026 capex at $195–205 billion. Q3 purchases of property and equipment were $51.4 billion, versus $24.0 billion a year earlier. CFO Anat Ashkenazi said capex will “increase significantly in 2027,” with detail deferred to the Q4 call. Alphabet has also disclosed $924 billion of future purchase commitments; those are maximum contractual amounts, and the company says the final bill can be lower because of variable pricing and volume flexibility. [27] [21] [28]
• Meta narrowed 2026 capex to $135–145 billion from $130–145 billion, raising the floor. Q3 capex including finance-lease principal was $34.91 billion. CFO Susan Li said the 2027 budget is still being built and that the company expects to keep investing aggressively in the core business and AI. No 2027 number. [29] [30] [28]
• Microsoft is the only one that cut the calendar-2026 figure, and the cut is not a demand cut. The path was about $190 billion in April, about $175 billion on the July 29 call after more leases were classified as operating leases (Hood said underlying investment plans were unchanged), then about $170 billion on October 28 “due to the 3P capacity delays.” Fiscal Q1 capex including finance leases was $45.2 billion, below the more-than-$50 billion the company had expected; cash additions to property and equipment were $39.4 billion. Hood said some GPU-as-a-service deliveries slipped into the second half of Microsoft’s fiscal year (January–June 2027), that December-quarter capex should exceed $50 billion, and that spending should accelerate in that second half on CPUs, GPUs, higher memory and storage costs, and the shifted deliveries. She also said customer demand continues to exceed available supply. [31] [32] [33] [34] [35]

Quarterly cash spend is already outrunning operating cash flow at several of these companies. In calendar Q3, purchases of property and equipment (Microsoft: additions) were about $202 billion against operating cash flow of about $176 billion across the four, on one compilation. Alphabet’s quarterly free cash flow was negative $9.1 billion; Amazon’s trailing-twelve-month free cash flow was an outflow of $42.4 billion. The 2027 story from the companies themselves is “higher level, no number yet,” constrained by third-party data-center delivery and components, not by a stated intention to stop. [27] [36] [37]

Outside estimates of the 2027 level are higher still, and they are forecasts, not guides. Nvidia management’s “nearly $800 billion / $1.3 trillion” for the top five in 2026 and 2027 is one such statement. A Goldman research note reported in late September had the largest U.S. hyperscalers at $800 billion in 2026, $1.2 trillion in 2027, and $1.4 trillion in 2028, with the growth rate slowing even as the level rises. Moody’s has said capex at the five largest U.S. hyperscalers plus CoreWeave could approach $1 trillion in 2027. These ranges should not be stacked as if they measured the same set of companies. [14] [38] [39]

Hatzius is calling a peak in the growth impulse, not in the dollars spent

On October 26, before Amazon and several peers had reported, Goldman chief economist Jan Hatzius wrote that the growth impulse from the AI boom was set to peak in late 2026 or early 2027, “even before concerns around the sustainability of the AI investment boom intensified.” AI investment is still rising rapidly in dollars. What he expects to slow over the next year is the increase in that investment as a share of GDP. A secondary summary of the same note said the year-over-year change in hyperscaler investment as a share of U.S. GDP should peak in the fourth quarter of 2026 at about 1.5%. He also pointed to a fading boost from restored bonus depreciation and a cooling equity wealth effect (Goldman had put that wealth effect at about 0.25% of GDP over the past year). Goldman has separately put recent U.S. AI-related capex at roughly $600 billion, and 2026 AI investment at 1.9% of GDP in one related brief. [40] [41] [42] [43]

That is compatible with Amazon spending “meaningfully more” and Alphabet spending “significantly” more in 2027. A rise from, illustratively, $730 billion to something above $900 billion or $1 trillion is still a higher level. It is a slower growth rate, and a smaller incremental contribution to GDP growth, than the jump from roughly $410 billion in 2025 to roughly $730 billion in 2026. Hatzius has been consistent on the mechanism since at least September: even if the buildout is productive, an investment phase in which the volume rises sharply gives way to an exploitation phase in which investment growth slows or the level eventually falls. He has not said the level has peaked. [44] [44]

Apollo’s Torsten Slok, writing around the same weekend, made a different claim: “zero financial payoff to corporate America outside of tech,” with margins and revenue per worker up at the largest tech firms and flat for the rest of the S&P 500. That is a return argument, not a capex-level argument. It does not cancel the memory contracts. It does say the handoff from capex to broad productivity, which would be needed to justify another leg of spending growth, is not yet in the data. [42] [45]

Robot and physical-AI memory is a content story, not a contracted book

Two estimates are in the market, and they do not describe the same machine.

Micron, on the September 30 call, said Level 4 and higher autonomous vehicles typically carry more than 200 GB of DRAM and several terabytes of storage, and that humanoid robots are expected to have comparable content. It said physical AI can become a significant driver of DRAM and NAND demand by the end of the decade, and that several physical-AI customers are already sampling next-generation products. That is an analogy plus early sampling, not a volume contract and not a shipment forecast. [46] [47] [48]

Counterpoint Research, on October 11, projected DRAM demand for humanoid computing systems rising from about 8,300 terabits in 2026 to about 172,000 terabits in 2030, roughly 20.7 times, while average DRAM per humanoid only rises from 19 GB to 39 GB. Most of the growth in that forecast is more robots, not more memory per robot. One reading of those two Counterpoint figures implies on the order of 550,000 humanoids in 2030 and total robot DRAM equal to a few hundredths of one percent of 2026 industry DRAM output. Counterpoint also argued that battery limits favor LPDDR and NAND over HBM. [49] [50] [51] [52]

The gap is the trade. Nvidia’s own robot modules sit in between: Jetson Thor at 128 GB, a July T3000 module at 32 GB that Nvidia pitched in part as a way to reduce cost amid high memory prices, and an entry module at 16 GB. Hold Counterpoint’s implied unit count and substitute Micron’s 200 GB content, and 2030 demand is several times the Counterpoint total—and still small next to AI-server DRAM unless unit forecasts move from hundreds of thousands toward the multi-million or, on Morgan Stanley’s 2050 scenario, hundreds of millions. None of this is in the LTA or SCA books that cover 2027–2030 server memory. [51] [53]

What the evidence does and does not support

Contractual demand that can be pointed to in filings and calls: Micron’s 26 take-or-pay agreements, $150 billion of minimum-priced remaining obligations, $32 billion of customer financial commitments, and price floors on most of that contracted revenue through 2030; SK hynix’s 14 LTAs covering more than half of 2027–28 capacity, with deposit safeguards and a market-linked price band; Nvidia’s purchase orders for the Rubin ramp and its $279 billion of supplier commitments, heavily memory. Hyperscaler 2026 guides of roughly $720–740 billion are company plans, not customer contracts with the chipmakers, though Alphabet’s $924 billion purchase-commitment ceiling shows how large the contractual maximums have become.

Verbal or forecast demand that should not be treated as firm: SK hynix’s “sold out through 2029” once negotiations are included; the shortage-through-2030 projection; Nvidia’s $1 trillion cumulative visibility and the $2 trillion cloud-industry backlog; Jassy’s “largely sold out through 2027”; every 2027 hyperscaler dollar figure that is not yet a company guide; and both robot memory estimates.

The growth-versus-level point is the one that reconciles Hatzius with the earnings calls. A peak in the GDP impulse in late 2026 or early 2027 can coexist with a higher capex level in 2027, with Microsoft’s $5 billion calendar-2026 trim (a delivery delay, with spend expected to reaccelerate into the first half of 2027), and with memory suppliers that have already sold, under contract, a large minority to a majority of near-term bits. The risk to that setup is not that 2027 capex has been guided down. It is that the contracts cover only part of the book, that price bands still move with the market inside a range, that third-party data-center delays are already slipping spend across the year boundary, and that the productivity payoff outside the builders themselves is not yet visible in the data Hatzius and Slok are using.

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Recent Findings Supplement (November 2026)

SK Hynix reported record Q3 2026 results on October 28, 2026, with DRAM and HBM volumes described as “effectively sold out” through 2029. This combines secured long-term agreement (LTA) volumes with customer demand under active negotiation, supported by contracts with 14 major customers (including cloud service providers), up from 10 in Q2. These LTAs cover more than 50% of planned 2027–2028 production capacity, typically span up to five years (with some extensions under discussion), include deposits, and feature pricing mechanisms that reflect market conditions within agreed ranges rather than fixed prices.[1][2][3]

• HBM demand is stated as roughly double available supply; a structural supply-demand imbalance is expected to persist through 2030.[1]
• The company plans significantly higher capex in 2027 to expand advanced DRAM/NAND capacity.[1]
• Record quarterly operating profit reached KRW 83.33 trillion (~$62B at then-prevailing rates) on revenue above KRW 100 trillion for the first time, with an ~80% operating margin.[1]

These LTAs provide more durable visibility than prior verbal outlooks, though pricing flexibility within bands means revenue remains sensitive to market conditions. For competitors or entrants, this underscores the challenge of securing multi-year supply commitments from hyperscalers amid tight HBM/DRAM availability.[4]

Micron’s Q4 FY2026 results (reported around November 9, 2026) showed 26 Strategic Customer Agreements (SCAs) covering more than 35% of expected revenue through 2030 (with some extending into 2031). These are take-or-pay contracts with binding volume commitments, backed by ~$32 billion in customer financial commitments (mostly cash deposits) and ~$150 billion in remaining performance obligations (RPO) calculated at minimum pricing. Three-quarters of the SCA revenue has defined pricing frameworks, often with floor/ceiling bands; management expects gross margins at floor prices to exceed prior cycle peaks.[5][6]

• SCAs span data center, consumer, and automotive segments; terms are generally five years (calendar 2026–2030) for most, shorter for automotive.
• This builds on 16 SCAs disclosed in Q3 FY2026 (~$100 billion minimum revenue at the time).[7]
• Physical AI applications (e.g., self-driving cars) are flagged as a substantial demand driver starting around 2030.[8]

The contractual structure (take-or-pay + deposits + pricing bands) differentiates these from purely verbal claims and aims to stabilize earnings in a cyclical industry. New entrants or rivals face high barriers to replicating this locked-in visibility and customer pre-commitments.

Nvidia’s recent Q3 results (period ended ~October 26, 2026) highlighted continued strong AI demand visibility, with data center revenue at $51.2 billion (up 66% YoY) and cloud GPUs described as sold out. Blackwell Ultra is now the leading architecture, with Rubin ramping and expected to contribute meaningfully; hyperscalers and partners (including Google, Microsoft, Oracle) have multi-year infrastructure commitments.[9]

• Management noted accelerating and compounding demand across training and inference, with an expanding ecosystem of model makers, startups, and sovereign customers.
• Production and supply chain planning reflect multi-year visibility, though specific backlog dollar figures were not newly quantified in the latest reports.

Verbal statements on sold-out status and backlog are supported by ongoing hyperscaler capex and partnerships but lack the detailed take-or-pay or deposit disclosures seen from memory suppliers. This reinforces Nvidia’s position while highlighting supply constraints that benefit memory makers with contracted volumes.

Big Tech capex guidance updated in late October 2026 shows sustained high levels with some 2027 increases signaled, though Microsoft’s calendar-2026 figure was trimmed due to timing delays rather than reduced plans. Growth rates in spending may be peaking even as absolute levels remain elevated or rise further.

• Microsoft: Calendar 2026 capex guidance lowered to ~$170 billion (from ~$175 billion previously) due to third-party capacity delivery delays now expected in H1 FY2027 (Jan–Jun 2027); Q1 FY2027 spend was $45.2 billion. Plans call for acceleration in H2 FY2027 driven by CPUs/GPUs, higher memory costs, and shifted deliveries. Earlier reductions partly reflected accounting shifts to operating leases.[10][11]
• Alphabet: 2026 capex guidance held at $195–205 billion (Q3 spend $51.4 billion, contributing to negative FCF). Expects a significant increase in 2027 (analyst estimates often $285 billion+, with some projections exceeding $300 billion).[12][13]
• Amazon: 2026 cash capex guidance held at ~$220 billion (majority for AWS); expects to spend “meaningfully more” in 2027. Strong visibility into 2027–2028 (and some of 2029) demand, with AWS projected to grow >40% in both years; capacity described as largely sold out through 2027 in some commentary.[14][15]
• Meta: 2026 capex guidance $135–145 billion (low end raised); non-cancelable commitments and leases total ~$825 billion in future obligations. Equity raises planned to fund AI buildout; S&P revised outlook to negative citing FCF deficits (forecast ~$22 billion in 2026, peaking higher in 2027).[16][17]

These figures represent capex levels that are high and, in most cases, still rising into 2027; they differ from growth rates, which Goldman Sachs economist Jan Hatzius flagged as peaking in late 2026/early 2027. Hatzius noted AI-related capex (estimated ~$600 billion annualized recently) will continue rising in absolute terms but its marginal contribution to GDP growth will slow as the share of GDP stabilizes, alongside fading wealth effects and other factors.[18][19]

Physical-AI/robotics memory demand remains a longer-term qualitative driver rather than a near-term quantified surge in recent reports. SK Hynix highlighted enterprise/personal AI in the short term and physical AI (autonomous driving, robotics) over the mid-to-long term as sustaining growth. Micron echoed substantial demand from physical AI applications starting around 2030. No new specific market size estimates or revised forecasts for robot/physical-AI memory appeared in the latest earnings or analyses reviewed.[20][8]

Implications for competitors/entrants: Contractual commitments (take-or-pay LTAs/SCAs with deposits and pricing bands) from SK Hynix and Micron provide stronger demand evidence than verbal “sold out” statements and create stickiness that is hard to displace. Big Tech capex remains demand-led and elevated into 2027 despite some timing shifts and growth-rate peaking signals, supporting memory visibility through the decade but pressuring FCF for spenders. Hatzius’s view suggests the investment boom’s incremental economic boost is maturing, which could eventually moderate growth rates even if absolute spending stays high. New players would need differentiated technology, cost advantages, or alternative supply models to compete in this contracted, capacity-constrained environment.