Quill transcribes an hour of audio offline in 20 seconds

Quill transcribes an hour of recorded audio in about 20 seconds, running entirely on a Mac's own chip, according to its GitHub repository.

That speed makes cloud transcription optional for anyone recording meetings, podcasts, or lectures. Audio never leaves the machine, so there's no upload step and nothing to trust to a remote server.

The repo went up July 24, per GitHub. It picked up roughly 3,000 stars in its first week, a sign developers want transcription that stays local.

The app is a single Swift binary that lives in the menu bar. It captures microphone and system audio as two separate tracks, using Core Audio's process taps and AVAudioEngine.

Transcription runs through Parakeet TDT 0.6B v2, a speech model FluidAudio ported to Core ML. Setup costs one thing: a roughly 600MB model download, after which everything runs offline.

It needs macOS 15 or later. A Whisper fallback is planned. The project is MIT-licensed.

None of the individual pieces here are new. Parakeet TDT and its Core ML port already existed, and so did Core Audio's process-tap APIs. Quill's contribution was wiring them into something a non-developer could run without touching a terminal. That reception measures pent-up demand for the integration, not a new model breakthrough.

Watch whether forks add features cloud transcription services charge for, like speaker diarization or search across old recordings. A free, on-device base changes what those subscriptions are actually selling.