Megadose AI progress, ranked and analyzed.

Intelligence per Watt: Measuring Intelligence Efficiency of Local AI

· HN · ArXiv ·
The paper argues that local AI should be judged by accuracy per watt, not capability alone.

The authors test 20-plus local language models across eight accelerators on 1 million real-world single-turn chat and reasoning queries. They report that local models successfully answer 88.7% of those queries, with results varying by domain. From 2023 to 2025, their “intelligence per watt” measure improved 5.3x, while locally serviceable query coverage rose from 23.2% to 71.3%. They also find local accelerators still trail cloud accelerators on the same models, leaving room for hardware optimization. HN · ArXiv's note

score 5

Categories: Research

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