The part that surprised me most was not the energy per token, which the paper says clusters around 0.1J across languages, but how much of the gap comes from output length: token explosion and models looping and repeating the same text, sometimes 45 times, in the worst cases. That makes this a fairness problem as well as an efficiency one, since per-token pricing means non-English users can pay more for a worse answer. I would like to see the benchmark rerun on current models, though, since the ones tested here are already about 18 months old.