Whisper
OpenAI's open-source speech-to-text model, the default starting point for transcription.
Whisper is an open-source automatic speech recognition model from OpenAI. It is robust across accents, background noise, and dozens of languages, and it can run entirely on your own hardware.
Because the weights and code are open, Whisper became the base that much of the open transcription ecosystem builds on: faster runtimes and diarisation tools all start here.
Where it fits
The default when you need solid, multilingual transcription you can run yourself, with no audio leaving your environment.
Where it does not fit
The base implementation is not tuned for real-time, low-latency streaming: for live captioning, reach for a derivative or a streaming API.
Alternatives to Whisper
The closest options on the map, and where each fits instead.
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faster-whisper Speech-to-text runtime
The default when you want Whisper-quality transcription self-hosted, but the reference implementation is too slow or memory-hungry.
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Deepgram Speech-to-text API
Best when transcription is on the critical path (real-time or high-volume) and a managed, low-latency API is worth paying for.
Unlike Whisper ProprietaryNot self-hostableHosted API
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AssemblyAI Speech-to-text API
A fit when a product needs transcription plus higher-level audio understanding from one managed API.
Unlike Whisper ProprietaryNot self-hostableHosted API
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WhisperX Transcription pipeline
A fit when a transcript needs precise timing or speaker labels: captions, multi-speaker meeting notes, audio search.
How it compares
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Comet Lab take on faster-whisper
What we actually run when a project needs self-hosted Whisper. Same transcript, a fraction of the cost. There is rarely a reason to run the reference code in production.
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We recommend Deepgram when latency and uptime on transcription are non-negotiable and the data policy allows a hosted service. Otherwise it is self-hosted Whisper.
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An open-source extension of Whisper adding accurate word-level timestamps and speaker diarisation.
Pairs with
Commonly used alongside it.