Pass IndexThe State of AISign in

Reasoning models that run on 36 GB

60 models with published weights that fit in 36 GB — a MacBook Pro with 36. Counted at four-bit quantisation, weights only, leaving the machine about a third of its memory and a gigabyte for context: room for roughly 37 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, and a comfortable one: it holds what 32 GB holds without the machine feeling tight, which in practice means a longer context or a browser you do not have to close first.

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 modelsModels that run on 36 GB