# What your AI costs the planet

*Every token costs electricity. How much depends on the model you choose — and ownAI lets you see it.*

A million output tokens are roughly ten novels' worth of text. Generated by a
small open model in France, they cause about 120 grams of CO2e — one
kilometer of driving, less than a cup of coffee. Generated by a large closed
frontier model in the United States, our estimate puts them at roughly 17,000
grams — about 140 kilometers. More than a hundred times as much, for the same
amount of text.

## Where the spread comes from

The arithmetic behind our estimates is short: tokens × energy per token ×
carbon intensity of the electricity where the model runs. The last two
factors vary enormously. Energy per token grows with the model's size — more
precisely, with the number of parameters doing work on each token. Between
the smallest and the largest model in ownAI, that is a factor of about
twenty. Then comes the grid: the US electricity mix is four to seven times
more carbon-intensive than the French or Swiss one. Multiplied, the two
produce the hundredfold spread.

For scale: a single answer stays tiny — a few grams even on the largest
model, less than a hundred meters of driving. But tokens add up. Agents
working on their own, long documents, a full workday — answers quickly become
millions of tokens.

## Seeing and choosing

ownAI keeps a running estimate of your emissions. You find it in the app
behind the credits icon at the top right, and in your [dashboard](/dashboard)
under "Climate Impact" — together with the receipts for the carbon removal
(more on that below).

The most effective decision is the choice of model. European-hosted open
models are by far the cleanest per token — and usually the cheapest, too. A
small model is enough for many everyday tasks; the large one can be picked
deliberately when it is needed. And a local model on your own machine runs on
your own electricity — how clean that is, your power contract decides.

## What we do

For the usage that runs through ownAI Credits, we estimate the emissions
every day and buy the permanent removal of at least that much CO2 from the
atmosphere through Ecologi: biochar and enhanced rock weathering. Removal
costs about seventeen times as much as avoidance certificates — the
difference is that the CO2 is actually taken back out of the air, rather than
someone else promising to emit less in the future. This is paid from our
margin; it does not affect your prices.

Because no provider discloses how much energy a request actually uses, we
estimate from token counts and published energy models. Wherever a number is
uncertain, we pick the assumption that raises the estimate: the grid's actual
carbon intensity instead of an operator's renewable claims, deliberately high
size estimates for models whose makers disclose nothing.

## What is still missing

This account is incomplete, and that belongs here. It is an estimate, not a
measurement. It covers only the electricity of inference — the manufacturing
of chips and servers, the water consumption of data centres, and the training
of the models are not included. Requests through your own API keys or local
models never touch our proxy and do not appear in this account. And the
17,000 grams from the opening rest on a deliberately high size estimate; the
true value is probably lower.

We are working on making the estimate more complete, and we update the
methodology as better data becomes available. The full calculation — every
constant, every source, every limitation — is public:
[carbon-methodology.md](/agents/carbon-methodology.md). Our public removal receipts: [Ecologi profile](https://ecologi.com/ownai).