← Back to the map

Topic board2Map station ②|Supply and spendingIn progressPrototype, pending review

Compute Supply and the Cost Line: Can Supply Keep Up, and When Does It Pay Off

This board answers four things: is there enough compute, where new supply comes from, where the cost per chip is heading, and who ends up holding the compute.

Read from the map: In progress and heading the right way; crosses the breakeven line in mid-2027

Revenue per H100e

$4,040

3Q26|five model companies' ARR ÷ market-wide compute

Cumulative compute

34.9M

3Q26|million H100e, coverage-adjusted

Purchase price per H100e

$12.2k

3Q26|quarterly chip spend ÷ new compute

Marginal ÷ average

3.4×

3Q26|above 1 = squeeze tightening

How to read this board

Core view: Validate the yardstick on history first, then project. Annualized revenue per H100e jumped 84% from $1,318 to $2,430 between the fourth quarter of 2025 and the second quarter of 2026, exactly when public-cloud GPU prices and the B300 went up, proving that a surge in the yardstick means supply short of demand and real price increases. By the third quarter of 2026 it reached $4,040. Projected forward on the base case, the line crosses the $4.5k breakeven of a new site with depreciation in mid-2027 and the $5.6k key threshold in mid-2028; beyond that, new compute earns a positive return at a 10% cost of capital, and additional capex turns from faith into arbitrage.

  1. Supply is bracketed by two estimates: the lower edge is the completion schedule of sites Epoch has seen break ground, the upper edge is chip-shipment trend extrapolation; from 2028 Epoch's coverage thins, so read toward the lower edge.
  2. The marginal yardstick turns before the average one: new ARR per new chip above the average means the squeeze continues; falling below it is the early warning that the yardstick is topping.
  3. The cost line is falling too: new-generation sites cost about 40% less than H100-era ones, so with revenue rising and cost falling, the crossing comes earlier than a static estimate. The dominant variable is depreciation life; three versus seven years moves every threshold by about 45%.
  4. Epoch's chip coverage thins in the latest quarters, so the rightmost bars understate rather than show falling demand; the dashed adjusted series assumes missing chips kept the prior quarter's pace, and the conclusion does not change.

Term: H100e is Epoch AI's unit for converting every vendor's chips into H100-equivalent compute, covering the whole market: Nvidia, Google TPU, AMD, Amazon Trainium, Huawei and others. Annualized revenue per H100e = the observable combined run rate of five model companies (OpenAI, Anthropic, xAI, Mistral, Zhipu) ÷ cumulative H100e market-wide, a yardstick for whether end AI revenue can carry new compute, not the rent cloud providers actually collect. The breakeven lines convert a 1GW data center's annualized total cost of ownership to each H100e: a new site with depreciation $4.5k, with cost of capital $5.6k (the key threshold), full annualized cost $6.5k.

Question 1Where supply comes from

1Supply timetable: how many GW come online each half year, and whose

This is the key chart for the whole supply side. IT power coming online each half year, stacked by owner; past dates are verified from satellite imagery, future dates are Epoch’s estimated completions. Every half year from 2026 to 2028 brings 3 to 7 GW online, and in the second half of 2028 Oracle alone is most of it. The drop after 2029 is because Epoch only records sites that have broken ground, with two to three years of visibility, not a real supply cliff.

When Supply Arrives: New IT Power per Half Year (GW, Stacked by Owner)#

How to read this chart

Dates are when each block of capacity comes online: past dates are verified by satellite imagery, future dates are estimated completion. Only sites under construction are included, with visibility of about two to three years, so the drop after 2029 is not a real supply cliff.

Source: Epoch AI (CC BY 4.0); FinSight compilation and estimates · Updated 2026-10-01

2Chip shipments: new compute and chip spend each quarter

Left: new H100e compute each quarter stacked by chip model, with the B300 now the largest block. Right: Epoch’s cost estimates summed, which is the implied chip purchase spend. Coverage follows Epoch’s own description: only Nvidia, Google TPUs, Amazon Trainium, AMD Instinct and Huawei Ascend, which Epoch considers the large majority of global AI compute; custom chips from Microsoft, Meta and Tesla and consumer GPUs are not included. Nvidia data starts in 2022, the other four only in 2024; Nvidia estimates are the most confident, Amazon the least. Some quarters are incomplete and drawn translucent, so the rightmost quarters are understated rather than falling demand.

New H100e Compute per Quarter (Stacked by Chip Model)#

How to read this chart

Median estimates; translucent quarters have incomplete coverage.

Source: Epoch AI (CC BY 4.0); FinSight compilation and estimates · Updated 2026-10-01

Estimated Chip Spend per Quarter ($B, by Maker)#

Source: Epoch AI (CC BY 4.0); FinSight compilation and estimates · Updated 2026-10-01

3All sites combined, and the build trajectories of the largest

Left: the sum of 71 tracked sites, where a steeper slope means faster build-out; the dashed line is cumulative capital cost. Right: the ten largest sites by peak power, each line one site’s IT-power build-out, with future dates as planned values. Use the left chart for the pace of supply growth and the right one for individual projects.

All Sites Combined: IT Power and Capital Cost#

Source: Epoch AI (CC BY 4.0); FinSight compilation and estimates · Updated 2026-10-01

Large Data Centers: IT Power Built Out (MW)#

How to read this chart

The ten largest sites by peak power; future dates are plans.

Source: Epoch AI (CC BY 4.0); FinSight compilation and estimates · Updated 2026-10-01

Question 2Is there enough compute

4The tightness gauge: revenue per H100e, history and projection

The solid line is actual: from $1,318 in the fourth quarter of 2025 to $2,430 in the second quarter of 2026, coinciding with public-cloud GPU price increases and the B300 markup; a surging gauge means supply short of demand. Dashed lines are projections: scenario revenue divided by Epoch's data-center completion supply. The green band from $4.5k to $6.5k is the target range, its floor the breakeven of a new site with depreciation and its ceiling the full annualized cost of ownership; the thick orange dashed line at $5.6k is the key threshold, beyond which new compute earns a positive return at a 10% cost of capital; the diamond marks when the base case crosses. The numerator is model companies' ARR, not the rent cloud providers collect.

Tightness Gauge: Annualized Revenue per H100e (History Plus Projection)#

How to read this chart

The orange zone is the price-increase test window. The green band, $4,500 to $6,500, is the target range: the lower edge is the breakeven line for a new site including depreciation, the upper edge a simplified annual total cost of ownership. The thick orange dashed line at $5,600 is the key threshold, above which incremental CapEx has positive NPV. The red dashed line at $9,500 is full breakeven on the installed base including cost of capital. The gold line at $1,400 is cash operating breakeven, already crossed.

Source: Epoch AI (CC BY 4.0); FinSight compilation and estimates · Updated 2026-10-01

5Compute supply versus compute demand, same unit

Compute demand = scenario revenue ÷ efficiency-adjusted revenue per H100e, anchored to the second quarter of 2026. The gap between the two lines is how loose or tight the market is; demand hugging or crossing supply means tight. The blue dashed band is supply under two estimates: the lower edge is the completion schedule of sites Epoch has seen break ground, the upper edge is chip-shipment trend extrapolation covering future sites.

Compute Supply vs Compute Demand (Same Units, Millions of H100e)#

How to read this chart

Demand compute = revenue ÷ efficiency-adjusted revenue per chip, anchored to 2Q26. The blue dashed band shows two supply estimates: the lower edge from known sites, the upper edge from extrapolating chip shipments.

Source: Epoch AI (CC BY 4.0); FinSight compilation and estimates · Updated 2026-10-01

6The marginal yardstick: new ARR carried by each new chip

The average yardstick = total ARR ÷ cumulative compute; the marginal yardstick = new ARR in the quarter ÷ new compute in the quarter, increment against increment with no stock inertia, so it turns before the average does. On history: in the fourth quarter of 2024 the marginal figure was only $52, as new compute went into training and monetization lagged; by the fourth quarter of 2025 it was back to $1,850 and above the average, so while the market read percentages as stagnation the marginal curve was already announcing 2026; in the second quarter of 2026 it was $5,814, 2.4 times the average, and higher again in the third. Marginal above average means the squeeze continues; falling below average is the early warning of a top. The latest quarter includes a run-rate estimate and is drawn translucent.

ARR per Chip: Average vs Marginal ($/Chip/Year)#

How to read this chart

Marginal = new ARR ÷ new compute. Average = ARR ÷ cumulative compute.

Source: Epoch AI (CC BY 4.0); FinSight compilation and estimates · Updated 2026-10-01

Marginal ÷ Average (x)#

Source: Epoch AI (CC BY 4.0); FinSight compilation and estimates · Updated 2026-10-01

New ARR per Quarter ($B) = the Demand-Side Dollar Increment#

How to read this chart

Percentages feed the stock narrative; dollar amounts are what capacity planning has to work with. The translucent latest quarter includes a run-rate estimate.

Source: Epoch AI (CC BY 4.0); FinSight compilation and estimates · Updated 2026-10-01

New H100e per Quarter (Millions) = the Supply-Side Increment#

Source: Epoch AI (CC BY 4.0); FinSight compilation and estimates · Updated 2026-10-01

Question 3The cost line is moving

7Purchase price per unit of compute: the fall has stopped

Left: the blended purchase price = market-wide chip spend in the quarter ÷ new H100e in the quarter, down from $38k in 2022 to $13.5k in the third quarter of 2025, then the decline stopped and the price rose to $14.1k in the first quarter of 2026, consistent with B300 volume and HBM price increases; the dashed line is the coverage-adjusted series. Right: price per unit of compute by chip generation; B200 to B300 is the first time in the data that a new generation costs more per unit of compute; H20 and Ascend look expensive because their compute is constrained, not because they are premium.

Blended Purchase Price: Cost per H100e (US$ Thousands)#

How to read this chart

Quarterly chip spend divided by quarterly new compute; translucent points are quarters with incomplete coverage.

Source: Epoch AI (CC BY 4.0); FinSight compilation and estimates · Updated 2026-10-01

Chip Generations: Price per H100e vs Launch Date (log)#

Source: Epoch AI (CC BY 4.0); FinSight compilation and estimates · Updated 2026-10-01

8Price times quantity against revenue: the monetization rate

Left: market-wide cumulative chip spend against the combined run rate of five model companies. Right: the monetization rate = annualized revenue ÷ cumulative chip spend, how much annualized revenue each dollar of chip capital supports. Reading: with the price per unit of compute no longer falling, a monetization rate still sliding would be evidence of oversupply, revenue failing to keep up after price increases; a rising rate means demand is keeping up. Today the price has stopped falling and the monetization rate is still rising.

Cumulative Chip Spend vs AI Companies' Annualized Revenue#

Source: Epoch AI (CC BY 4.0); FinSight compilation and estimates · Updated 2026-10-01

Monetization Rate: Annualized Revenue ÷ Cumulative Chip Spend (%)#

How to read this chart

Annualized revenue per dollar of chip capital. If this line falls during a price-increase period, that is evidence of oversupply.

Source: Epoch AI (CC BY 4.0); FinSight compilation and estimates · Updated 2026-10-01

Question 4Who gets the compute

9Who is locking in compute, who owns it

Left: by user attribution of Epoch's data centers, the trajectory of capacity online plus planned completions, where the slope is how hard each player is grabbing compute; "unlabeled" is mostly sites with undisclosed customers, and coverage thins after 2028. Right: cumulative H100e stock by owner through the first quarter of 2026, in-house chips included (Google TPU and Amazon Trainium under their own names), showing how capex turns into compute assets and who is gaining: Oracle and xAI surging, China held back by export controls.

Compute by User: Who's Locking It Up (Millions of H100e, Including Scheduled Completions)#

How to read this chart

Allocated by each data center's user field, split evenly where there are several users; unlabeled is mostly sites whose customers are undisclosed. The path combines capacity already online and scheduled completions; coverage thins after 2028.

Source: Epoch AI (CC BY 4.0); FinSight compilation and estimates · Updated 2026-10-01

Compute by Owner: Cumulative H100e Stock (Millions)#

How to read this chart

Stacked area, 1Q22 to 1Q26; in-house chips (Google TPU, Amazon Trainium) are counted under their owners.

Source: Epoch AI (CC BY 4.0); FinSight compilation and estimates · Updated 2026-10-01

10Latest shares: owners and users

Left: owners' share of cumulative stock as of the first quarter of 2026, in-house chips included. Right: users' share, counting only capacity online, not future plans. The two differ in definition: owners are who bought the chips, users are who runs the data centers.

Latest Share: Compute Owners (Cumulative Stock, Q1 2026)#

Source: Epoch AI (CC BY 4.0); FinSight compilation and estimates · Updated 2026-10-01

Latest Share: Compute Users (Mid-2026, Online)#

Source: Epoch AI (CC BY 4.0); FinSight compilation and estimates · Updated 2026-10-01

11Model-company economics: compute cost as a share of revenue, and token volume

Left: compute cost as a share of revenue; above 100% means compute costs exceed all revenue, and dropping below 100% is the turning point of the business model; Anthropic is already around 20%, OpenAI was still above 70% in 2025. Right: tokens processed per day on a log axis, where the gap between exploding volume and revenue growth is revenue deflation per token; different definitions are drawn separately and absolute levels cannot be compared across lines.

Compute Cost as a Share of Revenue (%)#

How to read this chart

Above 100% means compute spending exceeds total revenue.

Source: Epoch AI (CC BY 4.0); FinSight compilation and estimates · Updated 2026-10-01

Tokens Processed per Day (Trillions, log)#

How to read this chart

Different scopes (all products, API only, single company) are drawn separately; absolute values are not comparable across lines.

Source: Epoch AI (CC BY 4.0); FinSight compilation and estimates · Updated 2026-10-01

Question 5Method

12Method: how the breakeven lines are derived

Based on Epoch AI's total-cost-of-ownership model for a 1GW data center: $38B of upfront capex, $0.9B a year of operating cost, $8.5B a year of annualized total cost, with servers at 60%; five-year IT equipment life, fourteen-year buildings, 71% utilization, a 10% discount rate. Converted per H100e: 1GW is about 1.24 million chips, existing sites cost $30.6k per chip, new-generation sites only $13k to $19k. The table lists the formula, key assumptions and range for every threshold line.

Model Basis: How the Threshold Line and Projections Are Derived (For Reference)#

ThresholdHow it is builtKey assumptionRange
現金營運損平 $1.4k$0.9B/GW ÷ 1.24M 顆電力+維運,不含資本攤提$0.7k,保守自估 $1.4k:已越過
新建含折舊 $4.5k新世代 capex $13k:19k/顆 ÷ 5 年 + opex5 年直線折舊;新世代晶片組合$4.0k:5.2k,中位 $4.5k
新建含資金成本 $5.6k ★關鍵($13k:19k) × CRF 26.4% + opexCRF=5 年、WACC 10% 年金法;過線=新建算力在 10% 資金成本下 NPV 轉正,追加 capex 從信仰變成套利:本模型最關鍵的分水嶺$4.8k:6.4k,中位 $5.6k
邊際含資金成本 $6.5kEpoch 1GW 年化 TCO 直接換算($8.5B/年 ÷ 1.24M 顆,簡化法)與 CRF 法獨立推導收斂$6.2k:6.9k,取 $6.5k 為目標區間上緣
存量含折舊 $7.5k存量 capex 中位 $30.6k ÷ 5 年 + opex存量含較貴的 H100 世代$7.5k(3 年折舊 → $11.6k)
存量含 WACC $9.5k$30.6k × CRF 26.4% + opex完整經濟損平(存量全回收)~$9.5k

Source: Epoch AI (CC BY 4.0); FinSight compilation and estimates · Updated 2026-10-01