Drinking AI
Asking ChatGPT 30 questions a day for a year uses about a fifth of the water behind one beer — counting data-center cooling plus the water used to generate the query's electricity, the closest AI analog to how the drink figures count the water behind the crops. Pick a drink, shift the scope, or count by agentic tasks; then compare whole US drink categories with the modeled water footprint of all AI in 2025, and with a 2026 extrapolation (a Claude estimate).
Sam Altman's September 2026 line — one California almond takes the water of 38,000 queries — works out at OpenAI's 0.32 mL per query and the California-specific almond footprint: 12.2 L against 12.3 L. At this page's default scope, one almond ≈ 9,660 queries, and a glass of almond milk, about four almonds, ≈ 38,100.
One drink, or one almond, in ChatGPT queries
One beer is about 53,300 average ChatGPT queries, enough water for 30 queries a day for 5 years.
Enough water for 30 queries a day for 5 years.
All scopes: 2,370–331,000 queries.
A year of US drinks vs a year of global AI
A 2026 Patterns paper models the water footprint of all AI systems worldwide at 312.5 billion liters to 764.6 billion liters in 2025. The bars share one linear scale.
Annual water footprints on one scale: global AI 312.5 billion liters to 764.6 billion liters in 2025, projected 468.8 billion liters to 1.1 trillion liters in 2026 (extrapolation); US coffee 24.9 trillion liters (33–80× AI); US milk 19.8 trillion liters (26–63× AI); US soda 15.3 trillion liters (20–49× AI); US beer 7 trillion liters (9.2–22× AI); US wine 2.9 trillion liters (3.8–9.3× AI); US orange juice 2.8 trillion liters (3.7–9.1× AI); US tea 1.1 trillion liters (1.4–3.4× AI); US plant-based milk 402.4 billion liters (0.5–1.3× AI); US bottled water 88.4 billion liters (0.1–0.3× AI).
The nine categories sum to 74.4 trillion liters a year — 97–238× the 2025 AI range, or 65–159× the projected 2026 range. The AI estimate covers the world; the drink totals cover the US only, so world drink totals would sit further right.
The 2026 projection, and the shift from queries to tasks
Extrapolating to 2026
No one publishes a 2026 AI-water figure, so this is a Claude estimate. The Patterns model is mechanically AI power × a fixed water intensity, and AI power grew 2.45× from 2024 to 2025. Published rates for 2025→2026 run from ~1.3× (IEA accelerated servers) up to that 2.45× pace; scaling the 2025 range by a central 1.5× gives roughly 468.8 billion liters to 1.1 trillion liters for 2026. A UN University study puts the water footprint of data centers' 2025 electricity at 4.5 trillion liters with AI about 20% of that electricity — roughly 900 billion liters, 18% above de Vries-Gao's high estimate. At the 2.45× pace, the nine categories are still 40–97× the 2026 AI range.
A query is becoming a task
The published per-query figures describe one short text prompt (OpenAI's average, Google's median). Reasoning models emit far more tokens, and agents chain many calls per task, so the unit is shifting from query to task. At the default 2 mL scope, one beer is:
Multipliers from Epoch, Jegham et al., and Anthropic (multi-agent ≈ 15× a chat's tokens). Per-task water rises with the multiplier: at the default 2 mL scope one beer is 3,550 agentic tasks; at Mistral's 45 mL, 158.
What's measured, and what isn't
The per-query figure is a range
Published water-per-query numbers span more than 100×, almost entirely because of where the boundary is drawn. OpenAI and Google report 0.32 mL and 0.26 mL. OpenAI's post states no boundary; Google defines its figure as on-site data-center cooling water only, so the page treats both as the cooling-only scope. Add the water used to generate the electricity and a modeled short GPT-4o query lands near 2 mL (Jegham et al., preprint). A life-cycle assessment of one 400-token Le Chat response — cooling, upstream electricity, and hardware manufacturing, no training — reaches 45 mL (Mistral). The selector shows all three and defaults to the middle scope — the closest match to the drinks' upstream accounting; the crop tables also count rain and pollution-dilution water, which have no AI analog. Even at 45 mL, one beer still equals more than 2,000 queries. Sam Altman's September 2026 comparison — 38,000 queries per California almond, cited from memory — pairs OpenAI's 0.32 mL figure with the full California almond footprint (Fulton et al. 2019: 12 L per kernel). On the middle scope the same almond is about 6,140 queries, or 9,660 on the global-average table this page uses. The "Almond" selector runs the numbers.
The AI annual figure
de Vries-Gao (Patterns, 2026) models AI worldwide at 312.5–764.6 billion liters consumed in 2025, built up from data-center disclosures rather than a directly reported total. LBNL separately puts all US data centers near 17 billion gallons on-site in 2023. A competing projection from Li & Ren reaches 4.2–6.6 billion m³ by 2027, but measures withdrawal, not consumption — a different quantity, so it is not charted here.
Drink footprints
Beer, wine, juice, coffee, tea, and milk use the canonical peer-reviewed crop and animal water tables (Mekonnen & Hoekstra 2011, 2012) — full green, blue, and grey water. Coffee and tea are set by bean and leaf mass, not cup volume. Almond and oat milk apply the same tables to what is in the carton — 2% almonds and 10% oats by weight, from the Almond Breeze and Oatly labels — so a richer recipe scales the figure in proportion. The widely cited Poore & Nemecek milk comparison (371 L almond, 48 L oat, 628 L dairy per liter) counts irrigation and processing water only, no rain, and does not publish recipes, so it is not charted with the crop-table figures. Soda uses the low end of the 169–309 L range (Ercin et al. 2011). Bottled water is a 1.39 L/L facility ratio and tap water is just the glass, so both understate next to the crop-based drinks. Spirits (spiritsEUROPE) and bottled water (IBWA) are the two industry figures; the ethanol crop-water tables (Gerbens-Leenes & Hoekstra 2009) imply 24–50 L for the spirit alone, above the 18 L used here.
US volumes
Each category uses its latest public total: beer and wine from NIAAA (2023), orange juice from USDA ERS (2022, the latest in the series), milk from USDA ERS (2025), coffee from USDA FAS (2024/25, by bean mass), bottled water and soda from IBWA (2025). Soda has no published total, so it comes from IBWA's own per-capita figure and implied population; IBWA's own market-share split (29% bottled water, 21% soda) independently gives about 12.2 billion gallons, within 1.5%. Two figures are soft: tea is priced by leaf mass from an industry import projection (Tea Association: 265–270 million lb for 2024), and plant-based milk is a retail-scan total (Circana, via NMPF) priced at the almond-milk footprint for its 63% almond share and the oat-milk footprint for the rest — a Claude simplification. Andy Masley's post prompted the question.
All linked
AI water
OpenAI / Sam Altman
Average ChatGPT query: 0.34 Wh and 0.000085 gallons (0.32 mL) of water; the post states no boundary. June 10, 2025.
Sam Altman on Sources, Sept 2, 2026
"For every 38,000 ChatGPT queries, that is the same amount of water that is used in the production of a single almond in California" — cited from memory. Quoted by Tom's Hardware.
Google Cloud
Median Gemini Apps text prompt: 0.24 Wh and 0.26 mL of water, defined as data-center cooling only. 2025.
Jegham et al. 2025
"How hungry is AI?" (arXiv preprint, v6 Nov 2025). Adds power-plant water: a short GPT-4o query (ChatGPT's default until Aug 2025), about 300 output tokens, lands near 2 mL; a 1,000-token response near 6 mL.
Mistral AI
Life-cycle assessment, ISO 14040/44-compliant and reviewed by the audit consultancies Resilio and Hubblo: 45 mL of water per 400-token Le Chat response, marginal inference only. July 2025.
Li, Yang, Islam & Ren — "Making AI less thirsty"
GPT-3 on 2023 hardware at US-average WUE: a 500 mL bottle per 10–50 medium-length responses; 2027 global AI withdrawal projected at 4.2–6.6 billion m³. Communications of the ACM 68(7), July 2025; arXiv copy linked.
de Vries-Gao, Patterns 2026
AI's modeled global water footprint reaches 312.5–764.6 billion liters in 2025.
LBNL 2024 data-center report
US data centers consumed 66 billion liters (17.4 billion gallons) on-site in 2023, plus ~800 billion liters via electricity at 4.52 L/kWh. The latest LBNL water figures; the June 2026 update covers electricity only.
Workload & growth
Anthropic engineering
Multi-agent systems used about 15× the tokens of a chat interaction; single agents about 4×.
Epoch AI
A typical query is ~0.3 Wh; reasoning models emit ~2.5× the tokens. Feb 2025.
Epoch AI data insight
AI data-center power capacity reached about 30 GW in the last quarter of 2025. Jan 2026.
IEA — Energy and AI
Data-center electricity 415 TWh (2024) to ~945 TWh by 2030; accelerated servers grow ~30% a year. April 2025.
IEA — Key questions on energy and AI
April 2026 update: data-center electricity 485 TWh (2025) to ~950 TWh (2030); AI-focused data centers triple to ~465 TWh.
UN University (UNU-INWEH)
The water footprint of data centers' 2025 electricity (448 TWh) was 4.5 trillion liters, heading toward 9.3 trillion by 2030; AI was ~20% of that electricity, implying ~0.9 trillion liters. June 2026.
Drink footprints
Mekonnen & Hoekstra 2011
The canonical crop-water table: beer 298, wine 869, orange juice 1,018, coffee 18,925, tea 8,856 L/kg.
Mekonnen & Hoekstra 2012
Farm-animal products: milk at 1,020 L/kg.
Fulton, Norton & Shilling 2019
California almonds, 2004–2015: 10,240 L per kg of kernel, about 12 L per almond, against 16,095 L per kg in the global table. Ecological Indicators, open access.
Poore & Nemecek 2018
Freshwater withdrawals per liter of milk: almond 371, oat 48, soy 28, dairy 628 — irrigation and processing water only, no rain. Via Our World in Data.
Almond Breeze label
Ingredients: "Spring water, almonds (2%)…" — the almond share behind the almond-milk figure.
Oatly label
Ingredients: "Water, oats 10%…" — the oat share behind the oat-milk figure.
USDA FoodData Central
One almond kernel weighs 1.2 g; 23 kernels to the ounce.
Chapagain & Hoekstra 2007
The classic study: 140 liters per 125 mL cup of coffee (7 g roasted); 34 liters per 250 mL cup of tea (3 g), 17 for weak tea (1.5 g).
Ercin, Aldaya & Hoekstra 2011
Sugar-containing carbonated beverage: 169–309 liters per 0.5-liter bottle; 99.7–99.8% in the supply chain.
IBWA 2024 benchmarking
Bottled water facilities used 1.39 liters of water per liter bottled in 2022.
spiritsEUROPE 2020
Industry figure: about 18 liters of water per serving of spirits. Not peer-reviewed.
US volumes
NIAAA Surveillance Report 122
US beer (6.17 billion gallons) and wine (0.89 billion gallons), 2023.
USDA ERS fruit-juices table
US orange juice: 707.9 million gallons in 2022, the latest year in the series.
USDA ERS dairy data
US fluid milk sales: 42.8 billion pounds in 2025.
USDA FAS coffee report
US green-coffee consumption: 26.1 million 60-kg bags in 2024/25 (July 2026 edition).
Tea Association of the USA
Americans drank about 86 billion servings of tea in 2024, about 4 billion gallons; black and green tea imports ran 265–270 million lb.
IBWA 2026 progress report
Preliminary 2025: 16.8 billion gallons of bottled water; 47.5 gallons per person of bottled water and 33.9 of soda.
NMPF, citing Circana
US plant-based milk alternatives: 358.4 million gallons at retail in 2025, down 6%; almond drinks are 63% of the category.