UsesLevel 2 of 6 machine operationMachine operation, level 2 of 6Used to calculate 24 entries, levels 2 and 3Calculated with 1 entry, level 1Database structure Read 1,000 tokens
The server electricity needed to read 1,000 tokens, the word fragments the model reads.
- Selected reference: Medium model, Watershed default factor.
- CO2e is calculated from electricity and the worldwide grid; it is not a direct measurement of carbon.
- Out of scope: data centre cooling, counted separately (Google's measurement, from which Watershed derives the factor, already includes about 8%), server manufacturing and model training.
Sentence to citeRead 1,000 tokens: 0.15 gCO2e per 1,000 tokens, for 0.32 Wh of electricity, servers worldwide (458 gCO2e/kWh).
- Calculated with
- Used to calculate
Origin of the value
The question, an attached document, the history of a conversation. The medium model keeps Watershed's default factor for a large operator (2026), derived from the median query of the Gemini app measured by Google; the small and large models are derived from it using the gaps measured on the ML.ENERGY benchmark.
Comparison with the other machine operations
Characteristics
| Unit | 1,000 tokens |
|---|---|
| Default location | world, 458 gCO2e/kWh (Ember 2025, life cycle); 11 other locations to choose from |
| Counted | the computation on the server to read these words |
| Not counted | data centre cooling, counted separately (Google's measurement, from which Watershed derives the factor, already includes about 8%), server manufacturing and model training |
| Status | published, 1 reading with the same scope |
All the characteristics
| Identifier | IA-0010, projetcelsius.com/en/ai/database/IA-0010/ |
|---|---|
| Version | 0.4 of 12 November 2026 |
| Category | Machine operations, what the server computes |
| Class | Small model, about 8 billion parameters (0.024 gCO2e), Medium model, Watershed default factor (0.15 gCO2e), Large frontier model (0.59 gCO2e) |
| Choice of the selected value | value taken as it stands from its source, without calculation |
| Sources | Watershed, 2026 |
| Licence | CC BY 4.0 |
Result for the chosen case
This block is made of no other: its value is read from its sources.
Entries that use it (24)
Re-read from cache, Analyse an image, Quick question, Conversation of 10 exchanges, Write an email, Write a page, Article of 1,000 words, Proofread a page, Translate a page, Query a PDF, Summarise 30 pages, Analyse a spreadsheet, Deep research, Web search with an AI, Retouch a photo, Visual in 4 attempts, Voice mode, 1 minute, Summarise a meeting, Code suggestion, Generate a function, Have code reviewed, Coding agent hour, Browser agent, Automated workflow and
Sources of the calculation
2 publications, for this entry and those used to calculate it, with the chosen parameters.
Energy and factors
The references of the selected values and of the entries used in this calculation.
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
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 quantity, each within its own scope.
| Source | Date | Electricity | What the figure measures | Scope | Status |
|---|---|---|---|---|---|
| Read 1,000 tokensselected by the database, v0.4 | 2026 | 0.32 Wh | the value selected by the database | same scope | published |
| Watershed ↗Estimating GHG Emissions from AI Use: Framework for Corporate-Level Measurement | August 2026 | 0.32 Wh | 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) | 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?
Methodology conventions
With their alternatives
| 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 |
| 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 0.4 of 12 November 2026, in the database in version 0.4
- 12 November 2026Status : working value becomes published.Source check of 12 November 2026: 0.32 Wh consistent with the factor published by Watershed (2026); scope gap noted, since Google's data centre is already in the 0.24 Wh from which the factor is derived.
- 11 November 2026Watershed reading, nature : A default value, calibrated on non-production services becomes A default value that Watershed derives from Google's measurement.Watershed derives its per-token factors from the median query measured by Google (0.24 Wh); the value does not change.
- 2 November 2026Designation : 1,000 tokens read becomes 1,000 input tokens.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 2026Designation : 1,000 input tokens becomes Read 1,000 tokens.In people's own words.
- 2 November 2026Short title : Input tokens becomes Read 1,000 tokens.In people's own words.
- 2 November 2026Address : tokens-en-entree becomes lire-1-000-tokens.Address in people's own words; the old one redirected.
- 2 November 2026Selected value (0.32).The value 0.32 moves to the default row (medium class), unchanged.
- 31 October 2026Creation of the database, in its first version (0.1).

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5Organisations
4Occupations and activities
3Uses
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