💻 **Tom Tunguz: Local AI Models Now Match Frontier Models on 89% of Everyday Queries**

Theory Ventures' Tom Tunguz argues the AI compute story is shifting from the cloud to the edge, echoing the mainframe-to-PC transition.
• Local models now match or beat frontier cloud models on **71.3%** of everyday queries solo — and **89%** when routed across 20+ local models.
• That win rate has risen from just **23.2%** in 2023, adding roughly 20 percentage points a year.
• Intelligence-per-watt improved **5.3x** in two years — 3.1x from better models, 1.7x from better chips.
• Running locally cuts energy **80%**, compute **77%**, and cost **74%** versus an all-cloud baseline — though cloud still holds a _40% efficiency edge_ per query for the hardest reasoning tasks.

**💡 Why it matters:** If local inference keeps closing the gap, the economics of AI shift away from hyperscaler data centers for routine work — a structural risk to cloud-compute revenue models and a tailwind for on-device chip and local-model plays.

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