Reasoning models that run on 96 GB

72 models with published weights that fit in 96 GB — a MacBook Pro with 96. Counted at four-bit quantisation, weights only, leaving the machine about a third of its memory and a gigabyte for context: room for roughly 102 billion parameters. A mixture of experts is counted in full, because it is held in full even though only a few experts compute.

An Apple configuration for people who intend to run models rather than occasionally try one. Comfortably holds the seventy-billion class with a very long context, or a mixture-of-experts model whose active parameters are few but whose weights are all resident.

Models that plan before they answer, spending extra tokens on working the problem through. They win on mathematics, hard code and anything with several steps, and they are measured on boards like GPQA, AIME and ARC-AGI. The catch is what the thinking costs: reasoning is billed as output tokens, so the same model can cost several times more per answer at a high effort than a low one, and for a question that needed one turn you have paid for a monologue.

Wider

Reasoning models Models that run on 96 GB