UsesLevel 4 of 6 occupation or activityOccupation or activity, level 4 of 6Calculated with 9 entries, levels 1 and 3Database structure 
6Territories
5Organisations
3Uses
2Machine operations
1Calculation factorsMistral Vibe Pro, 1 year
One year of a Vibe Pro subscription (formerly Le Chat Pro, renamed in May 2026): about 10 deep research runs, 1,900 quick questions, 150 conversations of 10 exchanges, and 5 other tasks. Projet Celsius estimate.
- Text and conversation account for 92% of emissions: "Deep research" weighs as much as 330 quick questions.
- About 2,400 requests to AI over the year, or 6.6 per working day.
- An estimate: the frequencies and the share done with AI are our assumptions.
Sentence to citeMistral Vibe Pro, 1 year, Projet Celsius estimate: 1.2 kgCO2e per subscription per year, for 2.6 kWh of electricity, servers worldwide (458 gCO2e/kWh).
Breakdown of emissions by item
1.2 kgCO2e in total: 2.6 kWh of electricity × 458 gCO2e/kWh (servers worldwide).
Inputs of the calculation
PUE of the data centre, Read 1,000 tokens, Write 1,000 tokens, Re-read from cache, Write, with reasoning, Quick question, Conversation of 10 exchanges, Deep research
How the calculation is built
One year of a Vibe Pro subscription (formerly Le Chat Pro, renamed in May 2026): questions, images, deep research, translations, code. Mistral AI publishes 150 quick answers a day and up to 40 times the free plan's images (November 2026); typical use is a small fraction of that, an assumption.
Comparison with other occupations and activities
Characteristics
| Unit | 1 subscription, 1 year : 365 days |
|---|---|
| Default location | world, 458 gCO2e/kWh (Ember 2025, life cycle); 11 other locations to choose from |
| Counted | the tasks done with AI over a year, including data centre cooling |
| Not counted | server manufacturing, model training, the person's device and the subscription price |
| Status | estimated |
All the characteristics
| Identifier | IA-0324, projetcelsius.com/en/ai/database/IA-0324/ |
|---|---|
| Version | 0.1 of 2 November 2026 |
| Category | Occupations and activities, one person, one year |
| Choice of the selected value | database calculation from the entries this one is made of, at the quantities of the unit |
| Sources | calculation of the database |
| Licence | CC BY 4.0 |
Usage parameters
Advanced settings
Tasks and frequencies
Frequency and share done with AI, task by task · typical use
Adjust each task
| Task | Frequency | Share with AI | Per year | Electricity | Share |
|---|---|---|---|---|---|
| Quick question | 1,920 | 570 Wh | 22 % | ||
| Conversation of 10 exchanges | 146 | 510 Wh | 19 % | ||
| Create an image | 46.8 | 150 Wh | 6 % | ||
| Deep research | 10.4 | 1 kWh | 39 % | ||
| Proofread a page | 146 | 88 Wh | 3 % | ||
| Translate a page | 52 | 31 Wh | 1 % | ||
| Generate a function | 46.8 | 55 Wh | 2 % | ||
| Query a PDF | 41.6 | 200 Wh | 7 % |
Result for the chosen case
365 days, servers worldwide: 1.2 kgCO2e, 2.6 kWh.
For a carbon footprint
| Item | purchases of services (GHG Protocol scope 3, category 1); regulatory BEGES, category 4 |
|---|---|
| Quantity | 1 subscription over a year |
| Factor | 1.2 kgCO2e per subscription over one year, IA-0324 version 0.1, using the local grid mix (location-based), servers worldwide |
| Total | 1.2 kgCO2e · not counted: server manufacturing, model training, the person's device and the subscription price |
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 |
|---|---|---|---|---|---|
| Deep research | 10 times | 99 Wh | 1 kWh | 39 % | assumption |
| Quick question | 1,900 times | 0.3 Wh | 570 Wh | 22 % | assumption |
| Conversation of 10 exchanges | 150 times | 3.5 Wh | 510 Wh | 19 % | assumption |
| Query a PDF | 42 times | 4.7 Wh | 200 Wh | 7 % | assumption |
| Create an image | 47 times | 3.2 Wh | 150 Wh | 6 % | assumption |
| Proofread a page | 150 times | 0.6 Wh | 88 Wh | 3 % | assumption |
| Generate a function | 47 times | 1.2 Wh | 55 Wh | 2 % | assumption |
| Translate a page | 52 times | 0.6 Wh | 31 Wh | 1 % | assumption |
Entries that use it
No other entry in the database is calculated from this one.
Sources of the calculation
13 publications, for this entry and those used to calculate it, with the chosen parameters.
The result is calculated by Projet Celsius. The sources below support its uses, its factors and its conversion; they do not all measure this total.
Uses and assumptions
These publications shed light on AI tasks and uses. They do not measure the carbon footprint of the case calculated.
Anthropic · June 2025
Role and limits : Anthropic
What the publication covers. an agent uses about 4 times the tokens of a conversation, a multi-agent system about 15 times
What it does not cover. electricity
Reading by the database. Publisher orders of magnitude, with no absolute value
Deep research → : Re-read from cache →
The context re-read from cache at each of the 40 steps, 40,000 tokens on average
Scope of the figure used. server, convention C4
Limit. The quantity and the share entrusted to AI are database assumptions, not a measured footprint.
Apec · June 2025
Role and limits : Apec
What the publication covers. frequency of generative AI use at work, 2,000 private-sector managers surveyed in March 2025
What it does not cover. non-managers and the number of requests
Reading by the database. Recent French survey on frequency of use at work; copy read on a specialist press site
Support for the "Typical use" setting
Scope of the figure used. The median user among those who use AI, end of 2026: they turn to it every working day for part of their questions, writing and reading, about 5 to 15 requests per day in an office job. In an organisation or a territory, it also sets the share of employees who use it (25%).
Limit. This setting remains an assumption of the database, not a measurement of the occupation.
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
Reference of the selected value
Scope of the figure used. GPT-4o, 500 tokens written, full scope
Limit. A public calculation, from the hardware and the assumed size of the model
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.
Google · 2026
Role and limits : Google
What the publication covers. up to hundreds of sites browsed and pages processed per search
What it does not cover. electricity
Reading by the database. A presentation page: a ceiling, not an average
Deep research → : Read 1,000 tokens →
The web pages read, about a hundred by default: Google announces up to hundreds of sites
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.
Mistral AI · November 2026
Role and limits : Mistral AI
What the publication covers. plan prices, 150 quick answers a day on Pro, images up to 40 times the free plan
What it does not cover. messages and deep research, described without figures
Reading by the database. Page read on 2 November 2026; prices shown in US dollars
Published observation on uses
Scope of the figure used. Le Chat Pro at $14.99 a month excluding tax: 150 quick answers a day, up to 40 times the free plan's images
Limit. The only numerical cap among the consumer assistants reviewed
Vibe Pro, 1 year → : Quick question →
About 15 occasions to ask a question per day, i.e. at the typical level about 3% of the 150 quick answers per day of the plan (Mistral AI, 2026); calculated as a quick question, the Mistral AI life cycle assessment giving only carbon.
Scope of the figure used. computation of the response, data centre
Limit. The quantity and the share entrusted to AI are database assumptions, not a measured footprint.
Vibe Pro, 1 year → : Create an image →
About 3 image requests per week, assumption; the plan gives up to 40 times the images of the free plan (Mistral AI, 2026).
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.
Vibe Pro, 1 year → : Deep research →
About 1 topic per week that lends itself to in-depth research, assumption; cap not quantified by the provider.
Scope of the figure used. searches, pages read, context re-read, report, data centre
Limit. The quantity and the share entrusted to AI are database assumptions, not a measured footprint.
The other publication in this section
Projet Celsius · November 2026
Tokens per word, per line of code and per cell, measured with 7 public tokenisers
Role and limits
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.
Deep research → : Write 1,000 tokens →
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.
Proofread a page → : Read 1,000 tokens →
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.
Proofread a page → : Write, with reasoning →
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.
Translate a page → : Write, with reasoning →
The translated page, counted as a French page
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.
Translate a page → : Read 1,000 tokens →
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.
Translate a page → : Write, with reasoning →
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.
Query a PDF → : Read 1,000 tokens →
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.
Energy and factors
The references of the selected values and of the entries used in this calculation.
Role and limits : Google
What the publication covers. chips, host, standby machines, data centre, on-site water
What it does not cover. manufacturing, training
Reading by the database. The only production measurement published by a provider
Reference of the selected value
Scope of the figure used. Median of a text prompt; chips, host, standby machines, data centre
Limit. The only production measurement published by a provider, not audited by a third party
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
Microsoft Research · 2026
Estimation de l'énergie des requêtes en production (Joule) ↗ (new tab)
Role and limits : Microsoft Research
Author. Microsoft Research, Oviedo et al.
What the publication covers. H100 nodes, production
Reading by the database. Calibrated on production
Reference of the selected value
Scope of the figure used. Median, 500 tokens read and 300 written, H100 nodes
Limit. Not a measurement, but calibrated on production; judges public estimates to be 4 to 20 times too high
OpenAI · June 2025
Role and limits : OpenAI
Author. Sam Altman, OpenAI
What the publication covers. an average query
What it does not cover. method, scope
Reading by the database. One sentence, no method
Reference of the selected value
Scope of the figure used. "An average query", with no published method
Limit. No published scope; consistent with Google
The other publication in this section
Watershed · Aug. 2026
Estimating GHG Emissions from AI Use: Framework for Corporate-Level Measurement ↗ (new tab)
Role and limits
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
Quick question → : 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
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.
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.
Deep research → : 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.
Proofread a page → : 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.
Translate a page → : 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.
Generate a function → : 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.
Query a PDF → : 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.
Nature of the data
Published readings, conventions, assumptions
- Projet Celsius assumptions 100 %
Usage assumptions
Frequency, share done with AI according to adoption, source of each assumption
Quick question : 15 per day, 35% with AI in typical use
About 15 occasions to ask a question per day, i.e. at the typical level about 3% of the 150 quick answers per day of the plan (Mistral AI, 2026); calculated as a quick question, the Mistral AI life cycle assessment giving only carbon.
Conversation of 10 exchanges : 1 per day, 40% with AI in typical use
About 1 piece of practical advice per day, assumption.
Create an image : 3 per week, 30% with AI in typical use
About 3 image requests per week, assumption; the plan gives up to 40 times the images of the free plan (Mistral AI, 2026).
Deep research : 1 per week, 20% with AI in typical use
About 1 topic per week that lends itself to in-depth research, assumption; cap not quantified by the provider.
Proofread a page : 1 per day, 40% with AI in typical use
About 1 text to rework per day, assumption.
Translate a page : 2 per week, 50% with AI in typical use
About 2 pages to translate per week, assumption.
Generate a function : 3 per week, 30% with AI in typical use
About 3 functions to write per week, assumption.
Query a PDF : 2 per week, 40% with AI in typical use
About 2 long documents per week, assumption.
Published figures in support
Mistral AI (2026): 150 quick answers a day
Le Chat Pro at $14.99 a month excluding tax: 150 quick answers a day, up to 40 times the free plan's images
Methodology conventions
With their alternatives
| The working day and year | A working year counts 220 days and 44 weeks, a personal year 365 days; the task lists of occupations give, as a median, about 2 requests to AI per working day at low adoption, 6 at standard adoption, 21 at intensive adoption, excluding code suggestions |
|---|---|
| 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 sum of what makes up the entry, then 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 |
History
Entry in version 0.1 of 2 November 2026, in the database in version 0.4
- 2 November 2026Version 0.1 of the entry, as of the date of its current value.
- 31 October 2026Creation of the database, in its first version (0.1).
