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Working on a new blog post about local LLMs today! While running one of the tasks against llama 3.1 on my blazing fast M1 Max, I took a mactop snapshot. It's interesting to see the energy and GPU usage.

Interesting difference. The table below shows idle vs. maxed out doing work/inference, not just a loaded model. Before inference, only memory spiked as the model was loaded into memory. Not GPU or CPU. As an infrastructure person and toolmaker newish to AI, I find this all fascinating!

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