Whisper
The model that changed the category. MIT, and free to run forever.
94
sovereigntyWhisper is OpenAI's speech-recognition model, released openly under MIT — weights included. It handles around a hundred languages, is robust to accents and background noise, and does translation as well as transcription. Releasing it is what collapsed the economics of this category: a model competitive with the commercial APIs became something anyone could download. The reference implementation is slower than the optimised runtimes, but it is the simplest thing that works and the baseline everything else is measured against.
OPEN SOURCEMITSELF-HOSTLOCAL-FIRST
LicenseMIT
PricingFree — model weights and code both MIT.
Open sourceYes
Self-hostableYes
Local-first dataYes
What it does well
- +Genuinely open weights under MIT, not a restricted community licence
- +About a hundred languages, robust to noise and accent
- +Reference implementation — simplest possible starting point
- +Translation to English included
Where it falls short
- −Slower and hungrier than faster-whisper for identical output
- −Weak word-level timestamps without help
- −No speaker diarization
Whisper as an alternative to
Where Whisper shows up in our comparisons, and how it ranked.
Whisper head-to-head
Straight comparisons against the tools people weigh it against.