Transcription models that run on 32 GB

39 models with published weights that fit in 32 GB — a well-specified laptop. Counted at four-bit quantisation, weights only, leaving the machine about a third of its memory and a gigabyte for context: room for roughly 33 billion parameters. A mixture of experts is counted in full, because it is held in full even though only a few experts compute.

Enough for a thirty-billion-parameter model at four-bit with a long context, or a smaller one at higher precision if quality matters more than size. A practical ceiling for a laptop that also has to be a laptop.

Models that turn recorded speech into text. They are metered by the minute or the second of audio, so cost follows the length of the recording and not the difficulty of it. What separates them is languages covered, whether they mark who is speaking, and whether they run in real time or only on a finished file — a model that is excellent on a podcast may be unusable on a live call.

Wider

Transcription models Models that run on 32 GB