Transparency
How We Calculate AI Impact
AIrth estimates the energy, carbon, and water footprint of your AI usage using published research and industry data. This page explains our methodology in full.
Version 2025-10-v1 · Last updated October 2025
Core Formula
Every AI interaction produces three impact metrics:
Energy = Energy_raw × PUE
CO₂e (g) = Energy_kWh × Grid_Intensity (g/kWh)
Water (L) = Energy_kWh × WUE (L/kWh)
Where:
- PUE (Power Usage Effectiveness) — ratio of total facility power to IT equipment power. Default: 1.56 (industry average).
- Grid Intensity — carbon intensity of the electricity grid. Default: 124 gCO₂/kWh (UK average 2024).
- WUE (Water Usage Effectiveness) — litres of water per kWh of IT power. Default: 1.9 L/kWh.
Energy Per Action
Text LLM (token-aware)
| Model Class | J/token (mid) | Overhead (J) | Range |
|---|---|---|---|
| Small (≤8B) | 1.0 | 50 | 0.5–1.5 |
| Medium (8–30B) | 2.2 | 100 | 1.5–3.0 |
| Large (30–70B) | 4.0 | 150 | 3.0–6.0 |
| Frontier (≥100B / MoE) | 9.0 | 250 | 6.0–15.0 |
When token counts are unavailable, we use a conservative default of 0.30 Wh per text prompt (before PUE).
Image Generation
Standard image generation (512–768 px, ~30–50 steps): ~0.50 Wh/image before PUE. High-quality or large canvas generation can reach up to 3 Wh/image.
Concrete Examples
Using UK defaults: PUE = 1.56, Grid = 124 gCO₂/kWh, WUE = 1.9 L/kWh
Typical text prompt (no tokens)
Energy
0.000468 kWh
CO₂
0.058 g
Water
0.89 mL
Long reasoning (Large model, ~2,000 tokens)
Energy
0.00353 kWh
CO₂
0.44 g
Water
6.7 mL
1 image @ 768px, 40 steps
Energy
0.00078 kWh
CO₂
0.097 g
Water
1.5 mL
Platform Mapping
Each AI platform is mapped to a default model class based on their publicly known model sizes:
User Overrides
For more accurate estimates, users can override the following defaults in the extension settings:
- PUE — if your provider publishes region-specific PUE (e.g. 1.1–1.3 for hyperscale facilities)
- Grid Intensity — varies significantly by country (e.g. France ~50 g/kWh vs Poland ~650 g/kWh)
- WUE — some facilities achieve lower WUE depending on climate and cooling technology
Versioning
Every carbon log stores a factors_version identifier. When we update our coefficients, we bump the version (e.g. 2025-10-v1 → 2025-11-v1) to preserve reproducibility. Historical data always reflects the factors version used at the time of calculation.
Limitations
- Estimates are approximations based on published averages, not direct measurements from AI providers
- Token counts may be estimated when not directly available from the platform
- Model class assignments are based on publicly known information and may not reflect real-time model routing
- Water usage includes both direct cooling water and water embodied in electricity generation
We are committed to improving accuracy as more provider-specific data becomes available.
References
- Uptime Institute, Global Data Center Survey (PUE trends)
- Carbon Intensity (GB) API and UK electricity analyses (grid intensity)
- Data center WUE guides and operator disclosures (typical WUE ranges)
- Academic and industry measurement of LLM inference energy (token-wise energy, GPU power studies)
Glossary
- PUE
- Power Usage Effectiveness — ratio of total facility power to IT equipment power.
- WUE
- Water Usage Effectiveness — litres of water per kWh used by IT equipment.
- Grid Intensity
- Carbon intensity (gCO₂/kWh) of the electricity grid supplying compute.
- kWh
- Kilowatt-hour, a unit of energy.
- MoE
- Mixture of Experts — an architecture where only a subset of model parameters are active per query.