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Berget AI released an open-source method for calculating the carbon emissions of individual AI inference requests, developed with the Stockholm Environment Institute, WattTime and Klimatkollen. The Swedish AI infrastructure provider has added per-request emissions tracking to its customer console and published its calculator and methodology under an MIT licence. The method follows the Green Software Foundation’s SCI for AI specification and accounts for infrastructure energy use, cooling and hardware manufacturing, while excluding model training. Using identical hardware, Berget AI estimates that a typical Kimi K3 request emits 0.38 grams of CO₂e in Sweden, 1.6 grams in Ireland, 2.5 grams in Germany and 3.2 grams in Texas. The Texas estimate is 8.5 times Sweden’s, chiefly because of differences in grid emissions intensity. The example request uses about 4 Wh of energy, consists of 5,000 input and 387 output tokens, and is measured on a shared B300 deployment. Hardware manufacturing represents 89% of the Swedish result, while electricity represents 90% of the Texas result; the Texas request also uses about 6 mL of cooling water. The calculator applies location-based average grid emissions and can estimate any model and region. Berget AI said it will add marginal-emissions estimates next month and expand coverage to chip-manufacturing water and energy impacts. The company corrected earlier Ireland, Germany and Texas estimates on 21 October 2026 after reviewing its grid-intensity sources.