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Faster-Whisper

Fast Whisper transcription with CTranslate2 — 4x faster than OpenAI Whisper with lower memory usage

★ 23,921 GitHub MIT transcriptionspeech-recognitionwhisperctranslate2asr Image & Video

Overview

Faster-Whisper is a reimplementation of OpenAI's Whisper model using CTranslate2, a fast inference engine for Transformer models. With over 23,000 GitHub stars, it delivers up to 4x faster transcription than the original Whisper while using less memory. It supports 90+ languages, offers int8 and int16 quantization for reduced VRAM usage, and provides both Python API and CLI. Faster-Whisper maintains the same accuracy as vanilla Whisper while running efficiently on consumer GPUs with as little as 2GB VRAM. It includes batched processing, VAD-based segmentation, and word-level timestamps. The tool is widely used as the backbone engine in other transcription tools like WhisperX and WhisperDesktop.

Requirements

Min vCPU
2
Min RAM
4096 MB
Min Disk
10 GB
Rec vCPU
4
Rec RAM
8192 MB
Rec Disk
20 GB

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Docker Compose

# Generated by Run This Ai — docker-compose.yml
services:
  faster-whisper:
    image: linuxserver/faster-whisper:latest
    restart: unless-stopped
    ports:
      - 8080:8080
    volumes:
      - ./data/faster-whisper:/data

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