Twitter/X

The tweet (2026-04-08) cites a Stanford HazyResearch 'Intelligence per Watt'…

2026-04-08 · 17:03 UTC ·@alexocheema ·0 min read

Brief

Alex Ocheema (@alexocheema) highlights that 'intelligence per Joule' rose 18× in 16 months (Stanford HazyResearch 'Intelligence per Watt' chart), arguing it’s the key metric for local AI on phones, MacBooks and mini PCs. He says co-design of harness × inference engineering × models × hardware (via @exolabs) will accelerate progress; @fromamine predicts SOTA LLMs at home in ~18 months.

Why it matters

The tweet (2026-04-08) cites a Stanford HazyResearch 'Intelligence per Watt' chart showing intelligence-per-Joule increased 18× over a 16-month period.

Key details

@alexocheema (from @exolabs) calls 'intelligence per Joule' THE metric for local AI progress across phones, MacBooks and mini PCs and argues co-design of harness × inference engineering × models × hardware will accelerate gains.
Listener @fromamine (at an aiDotEngineer / swyx talk) interprets this trend to mean a SOTA LLM could run on consumer hardware at home in roughly 18 months.

Source evidence

title: @alexocheema: Intelligence per Joule increased 18x in 16 months.

This is THE metric to track for local AI progres...
author: @alexocheema
contenttype: tweet
publication: Twitter/X
published: 2026-04-08T17:03:22+00:00
sourceurl: https://x.com/alexocheema/status/2041924875816751197

word_count: 86

Intelligence per Joule increased 18x in 16 months.

This is THE metric to track for local AI progress (including phones, macbooks, mini pc’s).

This will accelerate with co-design of harness x inference eng x models x hardware for local AI (@exolabs).

The chart is from the Stanford @HazyResearch paper, Intelligence per Watt (h/t @JonSaadFalcon, @Avanika15, @krypticmouse).

Amine (@fromamine)

Listening to @alexocheema from @exolabs talking about running LLMs locally at @aiDotEngineer @swyx

18 months before we get a SOTA LLM at home with consumer hardware?

— https://nitter.net/fromamine/status/2041865182134100153#m