What Your Digital Life Uses

How much energy and water does it take to scroll TikTok, watch YouTube, join a Zoom call, or prompt ChatGPT?

Calculate Your Digital Habits

Digital inventory

Calculator overview

Use this tool to estimate a typical day of digital activity. Enter prompts, streaming time, meetings, or browsing, and the totals update as you go. Some streaming rows also let you choose a device because phones, laptops, and TVs can change total energy a lot. If you want a quick example, start with a starter mix and adjust from there. You will see four measures: server and network energy, total energy, direct water, and total water. For more detail on where the calculations come from, see the Sources & Method page.

How to use it

  • Enter rough amounts for the activities you actually use in a typical day.
  • Watch the summary cards update as you add prompts, streaming, meetings, or social-media time.
  • Use the quick anchors to translate the totals into everyday reference points.

Calculate Your Digital Habits

Start with a mix

1AI tasks0 active
prompts
prompts
images
hours
Laptop
2Media and search0 active
hours
Phone
hours
Phone
hours
Phone
hours
hours
daily blocks
Laptop
3Gaming0 active
hours
4Meetings0 active
hours
Laptop
meetings
Meeting bundle

Assumptions and sources

The lower table shows each activity's current row values, confidence label, and source links.

ActivityQtyStatusCloud/source-sideBroader-systemDirect waterTotal water
AI text promptsUses an everyday text-prompt estimate of about 0.3 Wh while keeping a separate prompt-specific water estimate of 0.26 mL direct and 1.3 mL total.
SourcesEpoch AI (2025)Jegham et al. (2025)
0 promptsEstimated0 Wh0 Wh0 mL0 mL
High-reasoning promptsUses the long high-reasoning 33.8 Wh benchmark rather than the much smaller medium-query comparison value, so this row stays an intentional outlier.
SourcesJegham et al. (2025)Internal synthesis (2026)
0 promptsInferred0 Wh0 Wh0 mL0 mL
AI image generationUses the IEA's 1.7 Wh SD-XL 1.0-base benchmark from controlled H100 testing. Jon Ippolito's What Uses More? comparison prompted the review; the adopted value comes from the underlying IEA report. The benchmark covers GPU electricity only and is carried through both energy columns as a conservative floor. Water remains an internal conversion rather than an image-specific measurement.
SourcesCozzi et al. (2025)Ippolito (2025)Internal synthesis (2026)
0 imagesInferred0 Wh
GPU electricity only; excludes network energy, facility overhead, and the end-user device.
0 Wh
Carries the 1.7 Wh GPU-only benchmark through as a conservative floor; this is not a measured total-system value.
0 mL0 mL
Coding-agent useUses the current one-hour coding-agent benchmark and adds a 30 Wh device allowance in the total-system column.
SourcesSimon P. Couch (2026)Internal synthesis (2026)
0 hoursEstimated0 Wh0 Wh0 mL0 mL
TikTok or short-video scrollingBuilt from device-side social-video measurement plus streaming-style infrastructure assumptions; keep this row estimated until a platform-specific cloud-side benchmark exists.
SourcesGreenspector (2021)Adam Holter (2025)Kamiya (2020)Internal synthesis (2026)
0 hoursEstimated0 Wh0 Wh0 mL0 mL
Instagram scrollingThis remains an analogy-based estimate built from social-media measurement plus streaming comparisons, useful for relative scale rather than platform accounting.
SourcesGreenspector (2021)Kamiya (2020)Internal synthesis (2026)
0 hoursEstimated0 Wh0 Wh0 mL0 mL
SnapchatAnother low-confidence social-media estimate built from broader comparison logic rather than a platform disclosure.
SourcesGreenspector (2021)Internal synthesis (2026)
0 hoursEstimated0 Wh0 Wh0 mL0 mL
YouTube watchingUses the same CDN-style video benchmark as Netflix so the calculator keeps an apples-to-apples streaming anchor for the cloud-side and total-system columns.
SourcesKamiya (2020)Internal synthesis (2026)
0 hoursInferred0 Wh0 Wh0 mL0 mL
Netflix streamingUses the IEA/Kamiya 22 Wh cloud-side and 77 Wh total benchmark used throughout the site's streaming comparisons.
SourcesKamiya (2020)Internal synthesis (2026)
0 hoursInferred0 Wh0 Wh0 mL0 mL
Email, cloud docs, and browsingThis is a teaching bundle for light browsing, email, and cloud documents rather than a per-click benchmark.
SourcesInternal synthesis (2026)
0 daily blocksEstimated0 Wh0 Wh0 mL0 mL
Zoom as participantUses a one-hour participant meeting estimate in which network plus platform routing form the cloud-side figure and participant device energy is added back for the total-system column.
SourcesDavid Mytton (2023)Verdecchia et al. (2022)Internal synthesis (2026)
0 hoursEstimated0 Wh0 Wh0 mL0 mL
Zoom as hostUses a hosted Zoom estimate that counts all participant devices in the total-system column.
SourcesDavid Mytton (2023)Verdecchia et al. (2022)Internal synthesis (2026)
0 meetingsEstimated0 Wh0 Wh0 mL0 mL
Gaming Console (Xbox Series X + TV)Locally rendered online multiplayer, not cloud gaming. The central estimate includes the console, reference TV, allocated home networking, fixed access and core transport, modeled game-server IT, and data-center overhead. Downloads, patches, manufacturing, standby, and optional texture streaming are excluded.
SourcesMicrosoft Xbox (2026)Microsoft Xbox (2026)Activision Publishing (2024)Mytton et al. (2024)U.S. Environmental Protection Agency (2024)Lyu et al. (2024)Microsoft PlayFab (2026)Lawrence Berkeley National Laboratory (2024)Internal synthesis (2026)
0 hoursEstimated0 Wh
Off-prem fixed access and core transport plus modeled game-server facility electricity; excludes the allocated home gateway.
0 Wh
Console, reference TV, allocated home gateway, fixed access and core transport, modeled game-server IT, and PUE overhead for one player-hour.
0 mL
Modeled direct cooling and humidification water for the game-server data center only; telecom-facility water is unquantified.
0 mL
U.S.-average operational water consumption: electricity-generation water for quantified components plus modeled direct game-server data-center water.

Method note: The first energy column is a cloud-side view that usually combines server and network demand, not a pure server-only accounting. The tool keeps direct-versus-total water explicit, but many non-AI rows still use broader electricity-based water conversions because most platforms do not disclose their own water use.