I have a computer with a 5090 on a smart plug at home running Qwen3.8 27B for agentic coding. On a busy day it can use around 5kWh, though on most days it is around 2kWh. I am sure cloud is more efficient because there is probably efficiency in running many parallel streams, some of the models have fever than 27B active parameters and the power draw of the non-GPU components is also spread over more GPUs. But still I also believe that the energy use numbers you get from the inference providers are a bit "beautified". After all, they still fight a political battle and have to show that it isn't all so bad.
Having said that, seeing the incredible progress of models throughout this year, I also strongly believe that the planned buildout is overeager. Even I with my gaming hardware often run out of instructions to give. And the smarter the models get that I can run, the less I will be able to saturate my hardware. Is it because of my lack of creativity of which kinds of tasks I can give to AI? Maybe a bit, but currently I can't believe that I am that far away.
Having said that, seeing the incredible progress of models throughout this year, I also strongly believe that the planned buildout is overeager. Even I with my gaming hardware often run out of instructions to give. And the smarter the models get that I can run, the less I will be able to saturate my hardware. Is it because of my lack of creativity of which kinds of tasks I can give to AI? Maybe a bit, but currently I can't believe that I am that far away.