Whisper overview and key facts (October 2026)

Whisper is OpenAI's open source speech recognition model and Python package. Teams with technical staff run it on their own hardware to transcribe recordings in many languages, translate speech into English and detect the spoken language.

The GitHub repository contains the code and model weights of a Transformer model trained on a large, diverse audio dataset. It is installed with pip, requires ffmpeg and runs from the command line or in Python. Six model sizes range from tiny with about 1 GB of video memory to large with about 10 GB; turbo is an optimized large-v3.

The repository has more than 109,000 GitHub stars and is published under the MIT license. Many commercial transcription tools and local apps build on it.

• Transcribes recordings locallyWhisper converts audio files such as interviews, podcasts or meetings into text on your own machine. Content and research teams keep sensitive recordings inside their network and avoid per-minute fees, provided someone maintains the setup.
• Translates speech into EnglishA translation task outputs English text directly from speech in other supported languages. International communication teams can get an English working version of foreign-language audio, such as an interview, without a separate translation step.
• Detects the spoken languageLanguage identification tells which language a recording uses before transcription starts. Teams processing mixed archives of interviews or calls can route files to the right workflow automatically instead of sorting them by ear.

• MIT license allows commercial use, modification and redistribution without license fees.
• Runs fully offline on your own hardware, so audio does not leave your infrastructure.
• English-only model variants are available for four of the six sizes.

Whisper is an open source project by OpenAI under the MIT license and runs on your own hardware in any country.

Whisper is a code repository, not a managed service: your IT team installs, secures and updates it, and larger models need a GPU. There is no vendor support, SLA or data processing agreement, but data stays wherever you run it. Accuracy varies widely by language according to the README, so test with your own recordings. The MIT license permits commercial use.

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