faster-whisper
Speech recognition with Whisper – up to four times faster, for your own scripts.
DifficultySome experience
HardwareCPU works (int8), NVIDIA GPU is much faster
LicenseMIT
LinksGitHub
faster-whisper transcribes audio with high accuracy in almost any language. Ideal when you want to process lots of files automatically.
How to try it
Commands from the official guides – just copy them.
Google Colab
- Download the notebook: colab.ipynb
- Open colab.research.google.com → File → Upload notebook
- Runtime → Change runtime type → GPU (T4)
- Runtime → Run all
Linux
# One-time setup: install uv (Python package manager, no sudo needed)
curl -LsSf https://astral.sh/uv/install.sh | sh && source $HOME/.local/bin/env
uv venv --python 3.12 whisper-env && source whisper-env/bin/activate
uv pip install faster-whisper "av<19" # av 19 is incompatible with faster-whisper 1.2
python -c "
from faster_whisper import WhisperModel
m = WhisperModel('large-v3-turbo', device='cpu', compute_type='int8')
segs, info = m.transcribe('aufnahme.mp3', language='de')
print(''.join(s.text for s in segs))"
# aufnahme.mp3 = your file (mp3, wav, m4a, mp4 …). The first run downloads about 1.6 GB.macOS
# One-time setup: install uv (Python package manager, no sudo needed)
curl -LsSf https://astral.sh/uv/install.sh | sh && source $HOME/.local/bin/env
uv venv --python 3.12 whisper-env && source whisper-env/bin/activate
uv pip install faster-whisper "av<19" # av 19 is incompatible with faster-whisper 1.2
python -c "
from faster_whisper import WhisperModel
m = WhisperModel('large-v3-turbo', device='cpu', compute_type='int8')
segs, info = m.transcribe('aufnahme.mp3', language='de')
print(''.join(s.text for s in segs))"
# aufnahme.mp3 = your file (mp3, wav, m4a, mp4 …). The first run downloads about 1.6 GB.Windows (PowerShell)
# One-time setup: install uv (Python package manager)
powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex"
$env:Path = "$HOME\.local\bin;$env:Path"
uv venv --python 3.12 whisper-env
uv pip install --python whisper-env faster-whisper "av<19"
.\whisper-env\Scripts\python.exe -c "from faster_whisper import WhisperModel; m = WhisperModel('large-v3-turbo', device='cpu', compute_type='int8'); segs, info = m.transcribe('aufnahme.mp3', language='de'); print(''.join(s.text for s in segs))"
# aufnahme.mp3 = your file (mp3, wav, m4a, mp4 …). The first run downloads about 1.6 GB.Ask the AI assistant
Questions about faster-whisper, installation or background? Our assistant knows this page and runs on our own machine, not in someone else's cloud.
The Assistant is an AI (Gemma 4) and can make mistakes – please check important details against the source. Questions are used only to generate an answer and are deleted after one hour. Please don't enter any personal data.
Comments
What do you think? Already tried it? Write it here, no sign-up needed.
Comments are public. Links aren't allowed, and we delete abusive posts. You can delete your own comment at any time in this browser. Learn more in the Privacy Policy.