Different models.
Different jobs.
Dessa targets spoken conversation. Whisper recognizes speech. A useful comparison starts with the task, not a synthetic score.
| Question | Dessa | Whisper |
|---|---|---|
| Primary task | Full-duplex speech-to-speech conversation | Speech recognition and translation |
| Public code / weights | Not verified on the checked release page | Published in the linked repository |
| License | Not verified | Code and weights released under MIT |
| Mac guidance | MacBook Pro M4 Max or better, per Block | whisper.cpp provides a local runtime; performance depends on configuration |
| Our prototype | Planned adapter only | Local speech-to-text adapter |
Choose by the output you need
For a transcript of your recording, a recognition model is the relevant starting point. For a live system that speaks while listening, recognition alone is not the complete task. Do not infer conversation quality from transcription accuracy or infer transcription quality from a conversation demo.
No speed or quality ranking
We have not run a shared benchmark on these models. We do not publish a latency, accuracy, memory or price comparison. The release facts above come from each publisher’s linked material and were checked 2026-10-24; they can change.
Local Voice Dock’s current scope
The Mac prototype manages a local Whisper runtime and transcribes a selected recording. Dessa integration is planned, contingent on access and license. There is no claim that an available Whisper adapter solves the same problem as Dessa.
See the prototype’s actual scope →