Can You Transcribe Audio Offline? Free Options
Yes: Whisper models run on your own computer with no upload. The ready-made apps and tools, their licences, and what offline costs you in speed.
The Scriptorium team ·
Yes. Whisper-family speech models run on your own computer, so once a model is downloaded the audio never leaves it. The easiest way is a desktop app such as Buzz, which describes itself as transcribing "audio offline on your personal computer"; developers can run whisper.cpp or faster-whisper directly. All of these show the MIT licence. The price of going offline is speed and setup, and on a plain CPU a larger model can take about as long as the recording or longer.
The offline options, side by side
| Option | What it is | What it needs | Source |
|---|---|---|---|
| Buzz | A desktop app for transcribing audio and video files offline, with TXT, SRT and VTT export | macOS (the page says it now requires Apple silicon), Windows (installer unsigned, so expect a warning) or Linux (Flatpak, Snap, AppImage); MIT licence | GitHub |
| whisper.cpp | A C/C++ port of Whisper with no dependencies | Command-line use; the page lists macOS, iOS, Android, Linux, Windows, Raspberry Pi and several kinds of GPU; MIT licence | GitHub |
| faster-whisper | A Python reimplementation that its authors say is up to four times faster than openai/whisper for the same accuracy | Python and some comfort with a terminal; MIT licence | GitHub |
| OpenAI Whisper | The original Python implementation | Python; the README lists the GPU memory each model size needs; MIT licence | GitHub |
| Self-hosted Scriptorium | Our web app running on your own hardware | A server or computer you manage; see the self-hosted page | Self-hosted transcription |
What does offline cost you?
- Speed. On our CPU-only server, the small model processed English at a real-time factor of 1.25 (about 75 minutes for an hour of audio) and Arabic at 1.27; a faster computer or a graphics card changes that. See how long an hour of audio takes.
- A model download. It is one-time. In our app the approximate download sizes are 75 MB for tiny, 480 MB for small and 3 GB for large-v3.
- Accuracy depends on the model you can run. A bigger model is slower. In our measurement on three Arabic clips, tiny's word error rate was about twice small's (64.4% against 31.8%), so do not pick the smallest model for Arabic just to save time.
- No cloud features. There is no shared library, no search across a team and no sync unless you build them.
- You do the setup and the updates. That is the trade for control.
Is offline the same as private?
It keeps the file off someone else's server, which is the main privacy gain. It does not protect the file on your own computer: a laptop that is lost or shared is still a risk, and a transcript saved to a cloud folder is no longer offline. The hosted site on the other hand processes uploads on our server and deletes guest files after a set time; our private transcription tools guide compares the options.
A quick way to decide
- Is the recording something that must not leave your machine (a legal, medical or confidential file)? Use an offline route.
- Not comfortable with a terminal? Try Buzz first.
- A short, non-sensitive clip? The hosted free preview is quicker, with no install.
- Many files regularly? Compare the time an offline machine needs with the cost of a plan.
Checked on 2026-10-26. The GitHub pages of Buzz (offline wording, operating systems, MIT, unsigned Windows app), whisper.cpp (platforms, MIT), faster-whisper (MIT, speed sentence) and OpenAI Whisper (MIT, VRAM column). Not read: Buzz's release notes or whether its YouTube-link feature needs the internet (the page does not say). Not measured: how any of these runs on your hardware. Menus, prices and limits change; confirm on the vendor's page before you rely on them.