ClimateLevel 6 of 6 territoryTerritory, level 6 of 6Used to calculate 1 entry, level 6Calculated with 4 entries, levels 1 and 3Database structure 
5Organisations
4Occupations and activities
3Uses
2Machine operations
1Calculation factorsChatGPT, 1 day
The electricity of the messages sent to ChatGPT in one day, calculated by ADEME.
- "Conversation of 10 exchanges" accounts for 45% of the database's calculation, not of the selected value.
- The selected value comes from publications; the database's calculation is used to assess the effect of the parameters, not to break down the selected value.
- Out of scope: in the selected value, images and videos; model training and server manufacturing.
Sentence to citeChatGPT, 1 day: 410 tCO2e per day, for 880 MWh of electricity, servers worldwide (458 gCO2e/kWh).
- Calculated with
- Used to calculate
Estimated breakdown of emissions by item
410 tCO2e in total: 880 MWh of electricity × 458 gCO2e/kWh (servers worldwide).
Shares calculated by the database from its items: the selected value remains the published value, whose breakdown these shares do not measure.
Origin of the value
2.6 billion messages (July 2025 volume according to ADEME) multiplied by the average consumption announced by OpenAI. A control recipe, which also counts reasoning, web searches and images, gives 2.2 times more: the gap exceeds the database's review threshold and remains to be explained.
Comparison with other territories
Characteristics
| Unit | 1 day |
|---|---|
| Default location | world, 458 gCO2e/kWh (Ember 2025, life cycle); 11 other locations to choose from |
| Counted | the queries sent to ChatGPT, based on the average consumption announced by OpenAI |
| Not counted | in the selected value, images and videos; model training and server manufacturing |
| Status | published, 1 reading with the same scope |
All the characteristics
| Identifier | IA-0103, projetcelsius.com/en/ai/database/IA-0103/ |
|---|---|
| Version | 0.3 of 2 November 2026 |
| Category | Territories, cities, territories, global services |
| Choice of the selected value | production measurements and models with the same scope; the database calculation from its factors serves as a check |
| Sources | ADEME, 2026 |
| Licence | CC BY 4.0 |
Usage parameters
Advanced settings
Result for the chosen case
Breakdown by item
Quantity, unit value, contribution and nature of the data for each item
| Item | Quantity | Unit value | Contribution | Share | Nature of the data |
|---|---|---|---|---|---|
| Web search with an AI | × 263,000,000 | 2.7 Wh | 720 MWh | 38 % | assumption |
| Conversation of 10 exchanges | × 200,000,000 | 3.5 Wh | 700 MWh | 37 % | assumption |
| Create an image | × 105,000,000 | 3.2 Wh | 340 MWh | 18 % | assumption |
| Conversation of 10 exchanges (medium reasoning) | × 26,300,000 | 6.1 Wh | 160 MWh | 8 % | assumption |
The database's calculation gives 1.9 GWh; the selected value, 880 MWh, comes from published measurements. This calculation cross-checks it and varies it with the parameters.
Entries that use it (1)
Sources of the calculation
10 publications, for this entry and those used to calculate it, with the chosen parameters.
Uses and assumptions
These publications shed light on AI tasks and uses. They do not measure the carbon footprint of the case calculated.
Epoch AI · February 2025
Role and limits : Epoch AI
What the publication covers. the calculation from the hardware and the assumed size of the model
What it does not cover. actual measurements
Reading by the database. A public, transparent calculation
Conversation of 10 exchanges → : Re-read from cache →
The context re-read from cache at each turn: the previous exchanges, and the document already in the conversation if there is one
Scope of the figure used. server, convention C4
Limit. The quantity and the share entrusted to AI are database assumptions, not a measured footprint.
OpenAI · September 2025
How People Use ChatGPT (NBER Working Paper 34255) ↗ (new tab)
Role and limits : OpenAI
Author. Aaron Chatterji, Tom Cunningham, David Deming, Zoë Hitzig, Christopher Ong, Carl Shan, Kevin Wadman (OpenAI, Duke, Harvard)
What the publication covers. exact message volumes of the consumer plans; classification of a sample of about 1.1 million conversations by topic, intent and link to work
What it does not cover. enterprise plans, under-18s, logged-out users
Reading by the database. The only published measurement of the volumes and uses of a major assistant; internal data, automatic classification
ChatGPT, per day → : Conversation of 10 exchanges →
76% of messages: an ordinary exchange, one tenth of a ten-exchange conversation
Scope of the figure used. messages, context re-read from cache, responses, data centre
Limit. The quantity and the share entrusted to AI are database assumptions, not a measured footprint.
ChatGPT, per day → : Conversation of 10 exchanges →
10% of messages with reasoning
Scope of the figure used. messages, context re-read from cache, responses, data centre
Limit. The quantity and the share entrusted to AI are database assumptions, not a measured footprint.
ChatGPT, per day → : Web search with an AI →
10% of messages that launch a web search
Scope of the figure used. searches, pages read, response, data centre
Limit. The quantity and the share entrusted to AI are database assumptions, not a measured footprint.
ChatGPT, per day → : Create an image →
4% of messages that create an image, out of the 7% of "multimedia" messages
Scope of the figure used. server and data centre
Limit. The quantity and the share entrusted to AI are database assumptions, not a measured footprint.
Projet Celsius · November 2026
Tokens per word, per line of code and per cell, measured with 7 public tokenisers
Role and limits : Projet Celsius
What the publication covers. 479,888 words from 196 blog articles and their English translation, code from the site and the Python library, a table of measurements; tokenisers of GPT-4o, GPT-4, Llama 3, Gemini (via Gemma 3), Mistral, DeepSeek and Qwen
What it does not cover. the Claude tokeniser, not public
Reading by the database. A measurement on technical texts, figures included; to be repeated if publishers change their tokeniser
Projet Celsius measurement, repeated on request with the public tokenisers
Conversation of 10 exchanges → : Re-read from cache →
Length convention: one page
Scope of the figure used. A report page, headings and paragraphs included: between the 1,500-character sheet (250 words) and a full A4 page in single spacing (about 550 words, at 6.1 characters per word measured on our articles)
Limit. This publication supports the quantity of text or content processed, not its carbon footprint.
Zhang and Nam · June 2026
HANSEL: Extracting Breadcrumbs from Web Agent Trajectories for Interactive Verification ↗ (new tab)
Role and limits : Zhang and Nam
Author. Yujin Zhang and Daye Nam
What the publication covers. 45 web agent trajectories: 13.16 steps and 6.02 pages visited per task on average
What it does not cover. electricity
Reading by the database. A small sample, which gives the order of magnitude of an agent's steps
Web search with an AI → : Read 1,000 tokens →
The 5 pages found, read by the model, and the question: web agents visit 6 pages per task on average
Scope of the figure used. server, excluding the data centre
Limit. The quantity and the share entrusted to AI are database assumptions, not a measured footprint.
Energy and factors
The references of the selected values and of the entries used in this calculation.
ADEME · July 2026
Role and limits : ADEME
Reading by the database. A public calculation
Reference of the selected value
Scope of the figure used. ChatGPT, one day, queries
Limit. A calculation, not a measurement published by OpenAI
Google · January 2009
Role and limits : Google
What the publication covers. a search, data centre
Reading by the database. Never remeasured
Reference of the selected value
Scope of the figure used. A search, data centre included
Limit. Never publicly remeasured; Google's AI answers are not published
Luccioni et al. · October 2024
Role and limits : Luccioni et al.
Author. Luccioni, Jernite and Strubell
What the publication covers. GPU, processor, memory
What it does not cover. data centre
Reading by the database. Open models only
Create an image → : Generate an image →
One image, of the chosen size: standard by default
Scope of the figure used. GPU, processor, memory; excluding the data centre
Limit. This figure covers part of the calculation; it does not measure the whole entry.
Reference for the variant "Standard image, from 512 to 1,024 pixels per side"
Scope of the figure used. Average of the open models tested, 1,000 images; median 1.35 Wh, maximum 11.49 Wh
Limit. Open models only; closed generators publish nothing
Role and limits : PEReN
Author. PEReN, published by Arcep
What the publication covers. GPU energy at inference, 22 open models, 6 question sets
What it does not cover. cooling, manufacturing, training
Reading by the database. Open models
Reference for the variant "With reasoning, medium effort"
Scope of the figure used. + 92% on average with reasoning, effect estimated by regression on 22 open models and 6 question sets; 95% interval from - 21% to + 348%
Limit. Open models, varied tasks
Watershed · Aug. 2026
Estimating GHG Emissions from AI Use: Framework for Corporate-Level Measurement ↗ (new tab)
Role and limits : Watershed
Author. Bistline, Ulissi, Davis, Glidden, Joyce, Li, Mohsenin and Suh (Watershed)
What the publication covers. factors per 1,000 tokens read and written at the server before PUE (host and standby machines included), PUE separate (1.10 for a large operator, 1.56 for an unknown operator)
What it does not cover. clean measurements, the model and the hardware
Reading by the database. Default factors proposed for review (public data as of June 2026); for a large operator, taken from Google's measurement published in 2025 (Elsworth et al.), which already contains the data centre overhead; constant per token, they underestimate long contexts and agents according to the authors
Reference for the variant "Medium model, Watershed default factor"
Scope of the figure used. Default factor for 1,000 tokens read, medium model, large operator, at the server before PUE (Watershed table 2, public data as of June 2026)
Limit. A default value that Watershed derives from Google's measurement (0.24 Wh for the median text query of the Gemini app), with about 500 tokens per query and a written token costing 3 times a read token; Watershed does not give the split between read and written tokens. The 0.24 Wh already include the overhead of Google's data centre (0.02 Wh, 8%): with 375 tokens read and 125 written, the simplest reading, the factor contains it, and the PUE of 1.10 applied afterwards counts it a second time (about 9%). Values proposed for review, final at the next version of the framework
Reference for the variant "Medium model, Watershed default factor"
Scope of the figure used. Default factor for 1,000 tokens written, medium model, large operator, at the server before PUE (Watershed table 2, public data as of June 2026)
Limit. 3 times the reading factor, based on the ratio between writing and reading selected by Watershed (Patel et al., Splitwise, 2024). Same derivation and same caveat as for reading: Google's 0.24 Wh already include about 8% of data centre. Values proposed for review, final at the next version of the framework
Conversation of 10 exchanges → : Data centre PUE →
The data centre, convention C3
Scope of the figure used. building cooling and losses
Limit. This figure covers part of the calculation; it does not measure the whole entry.
Reference of the selected value
Scope of the figure used. Default factor for a large operator, from the server to the data centre; 1.56 for an unknown operator
Limit. A default value, not a measurement
Web search with an AI → : Data centre PUE →
The data centre, convention C3
Scope of the figure used. building cooling and losses
Limit. This figure covers part of the calculation; it does not measure the whole entry.
Create an image → : Data centre PUE →
The data centre, convention C3
Scope of the figure used. building cooling and losses
Limit. This figure covers part of the calculation; it does not measure the whole entry.
Conversion into carbon
The source of the electricity factor of the selected location.
Worldwide: 458 gCO2e/kWh, life cycle.
Role and limits : Ember
Author. Ember, Our World in Data
What the publication covers. electricity generation over the life cycle, by country
What it does not cover. guarantees of origin
Reading by the database. The same source for all countries
Conversion of electricity into carbon: worldwide
Scope of the figure used. the production of electricity over the life cycle, including power plant construction and fuels
Limit. An average for the chosen country, not the electricity contract or the data centre of a specific service.
Published values
1 figure for the same operation, each within its own scope.
| Source | Date | Electricity | What the figure measures | Scope | Status |
|---|---|---|---|---|---|
| ChatGPT, per dayselected by the database, v0.3 | 2026 | 884 MWh | the value selected by the database | same scope | published |
| ADEME ↗Avis sur l'impact de l'IA générative | Jul. 2026 | 884 MWh | ChatGPT, one day, queries | same scope | computation |
The published figures do not all count the same scope; the scope of each figure is written next to it. Why do the estimates diverge?
Calculation assumptions
Quantities, nature and source of each assumption
Conversation of 10 exchanges : depending on the settings
76% of messages: an ordinary exchange, one tenth of a ten-exchange conversation
Conversation of 10 exchanges : depending on the settings
10% of messages with reasoning
Web search with an AI : × 263,000,000
10% of messages that launch a web search
Create an image : × 105,000,000
4% of messages that create an image, out of the 7% of "multimedia" messages
Methodology conventions
With their alternatives
| The standard query | A query counts 100 tokens read and 400 written |
|---|---|
| The data centre | Server electricity is multiplied by 1.10 for the data centre |
| The cache | A token re-read from the cache costs 10% of a token read |
| The default location | Without other information, the servers are in the world, at the world average electricity |
| Electricity, location-based, on a life cycle basis | The kilowatt-hour is that of the servers' country, on a life cycle basis, from a single source for all countries |
| Two significant figures | A calculated value is rounded to two significant figures, a published value is reproduced with the precision of its source; the calculation keeps full precision |
| The formula | the measured value, adjusted to the case settings in the proportion in which they change the database calculation, then the CO2e: electricity (Wh) multiplied by the carbon intensity of the server location (gCO2e/kWh), divided by 1,000 |
| Calculate a case without an entry | The formula, the default values and a step-by-step example |
Uses in the hub
Charts, figures, analyses and articles that cite this entry
History
Entry in version 0.3 of 2 November 2026, in the database in version 0.4
- 13 November 2026Description : June 2025 volume becomes July 2025 volume according to ADEME.The ADEME opinion (July 2026) says "in July 2025" for the 2.6 billion daily queries; the value (884 MWh) does not change.
- 2 November 2026Designation : ChatGPT, per day becomes ChatGPT, daily consumption.More precise designation: the object first, the specification after the comma, the quantity or period at the end; the former title remains searchable.
- 2 November 2026Calculation : recorded value becomes published measurements.The ADEME record remains the selected one; a control recipe redoes the count by type of message.
- 2 November 2026Designation : ChatGPT, daily consumption becomes ChatGPT, 1 day.The duration becomes a reading setting.
- 31 October 2026Creation of the database, in its first version (0.1).
