This was then scaled by the ratio of the training time to the GPU lifespan (1082 hours/1.5 years = 0.08238). This gave an embodied carbon of 12.439 kg CO2e, which was then amortized over the 300000000 monthly queries to give an embodied carbon-per-query of 4.1465 g/query.
ok, so they basically allocate the share of lifecycle emissions for the training run