The CO₂ of your AI use
ai-co2 turns your use of Claude Code or ChatGPT into a CO₂ range, then looks for ways to cut it.
Your data
Choose Claude Code or ChatGPT. The page then works with the one you pick.
A token is a piece of a word. AI tools count their work in tokens.
Claude Code
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Copy this prompt into Claude Code
Paste it into Claude Code, in the terminal, your IDE or the desktop app. Start a fresh conversation first, so a long one is not read again. Claude runs a short script that reads Claude Code’s own log files on this computer and replies with a few lines of totals.
Before you paste
- The script is 120 lines. It reads log files and prints totals. It has no network code and writes no file. Read it before you paste it.
- The log files hold your conversations. The script keeps only token counts and model names. No conversation text is printed.
- Want to see and approve the command yourself? Switch Claude Code to Manual mode first: Shift+Tab in the terminal, the mode indicator in VS Code, the mode selector in the desktop app. Then choose plain Yes.
- It counts all projects on this computer, in any folder you run it from. It does not count other computers, cloud sessions or SSH sessions.
- The run itself uses tokens too: about 7,000 for the prompt and the script, and more for Claude Code’s own instructions.
- If your Mac offers to install developer tools, you can cancel. Claude can then write the count in another language.
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Copy Claude’s whole reply. The page reads it here in your browser and checks that the numbers add up. Nothing is uploaded.
- Menu names and commands as they were on 7 Oct 2026.
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Ask ChatGPT for your data export
In ChatGPT, open Settings › Data controls › Export data and choose Export.
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Wait for the message
ChatGPT sends an email or a text message when the export is ready. That can take up to 7 days. The download link works for 24 hours.
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Drop the ZIP here
It’s read in your browser, and nothing is uploaded. If your export came as several files, drop them together.
- Business, Enterprise and Healthcare workspaces can’t make this export.
- If the export never arrives, OpenAI’s Privacy Portal can send it too. That download is a ZIP with the export inside. Drop it as it is.
- Menu names and commands as they were on 7 Oct 2026.
Your result
Your result, as a range. It moves whenever you change anything on this page, and a small copy stays on screen while you scroll.
Your range will land here
Likely range: to about –
Middle estimate:
You have set every assumption that changes your result, so there is one outcome and no range. Reset the sliders to see the range again.
Like driving a new petrol car
Likely to .
.
How to read it. Each dot is one possible outcome out of 100, and each stands for the same chance. Where the dots pile up is where your footprint most likely sits. The 5 lowest and the 5 highest are drawn hollow: 90 of 100 land between them. The line marks the middle estimate: half of the dots are below it, half above. Each dot is one possible outcome out of 100. Nothing in your estimate varies any more, so all 100 land on the same value. The line marks it.
Ways to cut
Picked from your own numbers, ordered by their middle saving.
Each saving is a range too. It is worked out for that tip on its own. Apply a tip and your range for these days changes on the page. Each saving is worked out for that tip on its own. Apply a tip and your result changes on the page. Switch it off to go back. Menu names and commands as they were on 7 Oct 2026.
Three ways to contribute
Cutting comes first. If you also want to give money, here are three different ways. None of them undoes your emissions.
How it’s calculated
The assumptions behind the estimate, where each comes from, and a slider for every number in the list. The model sizes share one slider.
Show every assumptionHide the assumptions
Your footprint is worked out with one formula: tokens × weight × energy per token × data-centre overhead × grid × hardware. Weight says how much energy reading a token takes compared with writing one. The result is in CO₂e: CO₂ and the other greenhouse gases, counted as CO₂.
Your tokens are counted.The tokens in your export are counted. Hidden work is estimated on top. The other numbers are not known exactly. For each of them, the list of assumptions below gives a low, a typical and a high value.
- Low and high are the lowest and the highest value we take seriously. The page never uses a value outside them.
- Typical is the middle. We treat a lower value and a higher value as equally likely.
The page works out your footprint 10,000 times. Each time it uses a different combination of values, taken from a fixed pattern that spreads the combinations evenly. For every assumption you have not set yourself, half of the 10,000 runs use a value below typical and half a value above it. Positions near the middle of each slider are used most often. Positions near the two ends are used least often. That shape is our choice. No data can settle it.
The energy values for the model sizes move together: a run that is high for one size is high for all. Every other assumption varies on its own.
The page sorts the 10,000 results and cuts the list into 100 groups of 100. Each dot in the chart is the middle of one group. The middle estimate lies between group 50 and group 51, so half of the results are below it and half above. The likely range leaves out the 5 lowest and the 5 highest groups, so 90 of 100 results land inside it.
The extreme range is the formula with every assumption you have not set at its low value, and again with each at its high value. No result can fall outside it.
Nothing here is random. The same data always gives the same result.
The range is only as good as that list. If a real value lies below our low or above our high, your real footprint can lie outside the range too.
“Saves roughly A to B” under a tip means this. If the days counted here had been the same except for this one change, your footprint would have been A to B lower in 90 of 100 possible outcomes. The tips are ordered by the middle of each saving, which can differ from the order of the ranges.
The car figure counts only what leaves the exhaust: about 160 g of CO₂ per km for a new petrol car in Europe in real driving.
Giving money does not undo emissions. We follow the idea of a contribution claim from a 2024 paper by the University of Oxford: what you give is a contribution to climate work, and your estimate stays what it is.
A cost range under “Three ways to contribute” means this. In at least 90 of 100 possible outcomes, funding that many kilograms with this provider would cost between the two figures.
Source for the car figure: EEA provisional 2025 data (opens in a new tab), new petrol cars without hybrid drive (136.6 g/km, our own average of the EEA’s table), times the ICCT’s 19% real-world gap (opens in a new tab) for cars registered in 2023. Checked 7 Oct 2026.
Source for the places beside the car figure: drives by the fastest route on OpenStreetMap (opens in a new tab) (© OpenStreetMap contributors), between main stations or city centres; courts, pools, pitches, tracks, bridges and avenues by their official lengths; the Moon at 384,400 km on average, from NASA (opens in a new tab). Checked 7 Oct 2026.
Counted
Left out
For your result
Source for the clean-power figure: Worked out from Google’s and Microsoft’s 2026 environmental reports (65 and 73). The figure swings from year to year: one year earlier it was 91 and 9. Checked 7 Oct 2026.
The assumptions
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Estimates, not measurements. Every CO₂ figure on this page is an estimate. The extreme range is what the formula gives with every assumption that still varies at its low value, and again with each at its high value.