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Prerequisites

Before installing Whisper, ensure your system meets these requirements:
  • Python: Version 3.8 or higher (3.8-3.13 supported)
  • PyTorch: Recent versions (developed with PyTorch 1.10.1+)
  • FFmpeg: Required for audio processing

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Installation Steps

1

Install Whisper via pip

The easiest way to install Whisper is via pip. This will install the latest stable release:
pip install -U openai-whisper
The -U flag ensures you get the latest version if Whisper is already installed.

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Alternative: Install from GitHub

To get the latest development version directly from the repository:
pip install git+https://github.com/openai/whisper.git
2

Install FFmpeg

FFmpeg is required for audio file processing. Install it using your system’s package manager:
sudo apt update && sudo apt install ffmpeg
Make sure FFmpeg is accessible from your command line by running ffmpeg -version after installation.
3

Verify Installation

Verify that Whisper is installed correctly:
whisper --help
You can also verify the installation in Python:
import whisper
print(whisper.available_models())
This should display a list of available model names without errors.

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Dependencies

Whisper automatically installs the following Python dependencies:
  • more-itertools: Utilities for working with iterables
  • numba: JIT compiler for numerical functions
  • numpy: Numerical computing library
  • tiktoken: Fast tokenizer implementation by OpenAI
  • torch: PyTorch deep learning framework
  • tqdm: Progress bar library
  • triton: GPU programming (Linux x86_64 only)

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Troubleshooting

If you see installation errors related to tiktoken, you may need to install Rust:
  1. Visit the Rust installation page
  2. Follow the installation instructions for your platform
  3. Configure your PATH: 
    export PATH="$HOME/.cargo/bin:$PATH"
  4. Retry the Whisper installation
If installation fails with No module named 'setuptools_rust', install it explicitly:
pip install setuptools-rust
Then retry installing Whisper.
If you get an error that FFmpeg is not found:
  1. Verify FFmpeg is installed: ffmpeg -version
  2. Ensure FFmpeg is in your system PATH
  3. On Windows, you may need to restart your terminal or add FFmpeg to PATH manually
Whisper will automatically use CUDA if available. To verify GPU support:
import torch
print(f"CUDA available: {torch.cuda.is_available()}")
print(f"CUDA device: {torch.cuda.get_device_name(0) if torch.cuda.is_available() else 'N/A'}")
If CUDA is not detected but you have an NVIDIA GPU, reinstall PyTorch with CUDA support following the PyTorch installation guide.
If you encounter SHA256 checksum errors when downloading models:
  1. Delete the cached model files in ~/.cache/whisper
  2. Retry loading the model
  3. Check your internet connection for stability
The models are downloaded on first use and cached locally for future use.

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System Requirements by Model

Ensure your system has sufficient VRAM for your chosen model:
ModelVRAM RequiredBest For
tiny~1 GBFast transcription, limited resources
base~1 GBBalanced speed and accuracy
small~2 GBBetter accuracy, moderate speed
medium~5 GBHigh accuracy, translation tasks
large~10 GBMaximum accuracy
turbo~6 GBFast with high accuracy (recommended)
CPU inference is supported but will be significantly slower than GPU inference, especially for larger models.

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Next Steps

Quickstart Guide

Start using Whisper with practical examples for both CLI and Python API

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