CarbonWatch
A 500-token answer produced by DeepL costs about 0.25 Wh, or 0.063 gCO₂e. DeepL is a chat service whose inference runs in the European Union, where power is worth 250 gCO₂e per kilowatt-hour.
What CarbonWatch records
| Kind of use | Chat |
|---|---|
| Inference region | European Union EU |
| Grid intensity | 250 gCO₂e/kWh |
| Energy rate | 0.5 Wh / 1 000 tokens — rate specific to this service, declared in the registry: the model served is not a frontier one |
| Bytes per token | 25 |
Three reference points
The estimate is linear: these three rows are the same calculation at three scales. They are orders of magnitude, not measurements.
| One 500-token answer | 0.25 Wh | 0.06 gCO₂e |
|---|---|---|
| A hundred answers — a working day with an assistant | 25 Wh | 6.25 gCO₂e |
| A thousand answers | 250 Wh | 62.5 gCO₂e |
The same usage elsewhere
The same exchange, the same model, billed at another region's grid. This is the point in the calculation where the choice of provider weighs heaviest — more than the length of the answers.
| Switzerland | 40 g/kWh | 0.01 gCO₂e |
|---|---|---|
| France | 50 g/kWh | 0.01 gCO₂e |
| European Union this service | 250 g/kWh | 0.06 gCO₂e |
| United States | 380 g/kWh | 0.1 gCO₂e |
| World | 480 g/kWh | 0.12 gCO₂e |
| China | 580 g/kWh | 0.15 gCO₂e |
How it is detected
Outgoing connections to these domains, resolved into addresses. The comparison is made on the address, never on the hostname: nothing is decrypted, nothing is read.
- api.deepl.com
- www.deepl.com
What this figure does not say
The scope is operational: the electricity of inference, and nothing else. Not the manufacturing of the servers, not the training of the model amortised over requests, not the transport network.
The rate is the one for the service type, not for the exact model you called: CarbonWatch does not read content and cannot tell whether an answer came from a small model or a large one. A long chain of reasoning costs more than what is counted here.
The ratio between bytes received and tokens produced is the most uncertain parameter of the model. It is adjustable, service by service, in the registry.