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Calculator

Your AI footprint

Estimate the water, energy and carbon behind your AI use, with sources for every number.

Type it the way you'd say it. The dials below follow.

Model

frontier class · 2 Wh per 1,000 tokens (mid benchmark)

How much do you use it?25 prompts/day
Show results
What gets counted

The same prompt can be “five drops” or “a bottle of water” depending on what you count: just data-center cooling (Low), the water behind the electricity (Mid), or training and hardware too (High).

Read the methodology
WaterMid: + electricity

16.9gallons

= 63.9 liters

Grok, 25 prompts/day · per year, Mid scenario

Energy

12.8 kWh

Carbon

4.5 kg CO₂e

That's about…

Sized to your result, Mid scenario
  • 128water bottles
  • 16almonds' worth of water
  • 0.98showers
  • 0.49cups of coffee (grown and brewed)
  • 116kettle boils
  • 11.2miles in a gas car
ShareDownload image
  1. 01

    Say it or set it

    Describe your use in a sentence, or set the model, usage and timeframe by hand. Both drive the same dials.

  2. 02

    Tokens become energy

    Each model sits in a benchmarked energy class, or uses its official figure where one is published.

  3. 03

    Energy becomes water

    Multiplied by the factor for the boundary you pick: cooling only, plus electricity, or the full lifecycle.

How we calculate thisWhere do I find my token count?

Sources

Cited on this page, in order of appearance.

  1. 1Jegham, N., Abdelatti, M., Elmoubarki, L., & Hendawi, A. (2025). How Hungry is AI? Benchmarking Energy, Water, and Carbon Footprint of LLM Inference. arXiv preprint arXiv:2505.09598 (v6, Nov 2025). (accessed 2026-06) preprint
  2. 2Altman, S. (2025). The Gentle Singularity. blog.samaltman.com: 0.34 Wh and 0.000085 gal of water per average ChatGPT query. (accessed 2026-06) official disclosure
  3. 3Siddik, M. A. B., Shehabi, A., & Marston, L. (2021). The environmental footprint of data centers in the United States. Environmental Research Letters 16(6): watershed-scale direct + indirect water footprint. (accessed 2026-06) peer-reviewed
  4. 4US Environmental Protection Agency (2024). Emissions & Generation Resource Integrated Database (eGRID). US EPA: grid carbon intensity by region. (accessed 2026-06) government
  5. 5AIWaterUse (2026). AIWaterUse methodology: disclosed site assumptions and derivations. aiwateruse.org/methodology: blended tokens per exchange, input/output split, unit definitions and arithmetic derivations, reviewed quarterly. (accessed 2026-06) site assumption
  6. 6Water Footprint Network (Mekonnen, M. M., & Hoekstra, A. Y.) (2011). Product water footprint database. Water Footprint Network: agricultural water footprints (coffee, beef, cotton, almonds). (accessed 2026-06) peer-reviewed
  7. 7US Environmental Protection Agency (2024). WaterSense: residential water use and fixture flow rates. US EPA: 82 gal/person/day household use; fixture flow rates. (accessed 2026-06) government
  8. 8US Environmental Protection Agency (2024). Greenhouse gas emissions from a typical passenger vehicle. US EPA: ~404 g CO₂ per mile for an average US gasoline car. (accessed 2026-06) government