While technically a full subtitle editing suite, the latest versions of Subtitle Edit have integrated Whisper. This is ideal if you are making captions for YouTube or social media.
| Model | VRAM (GPU) | RAM (CPU) | Speed (1 hour audio) | Accuracy | |-------|------------|-----------|----------------------|-----------| | tiny | ~1 GB | ~2 GB | 5–10 min | Good for clean speech | | base | ~1 GB | ~3 GB | 10–15 min | Better | | small | ~2 GB | ~4 GB | 20–30 min | Great for podcasts | | medium| ~3 GB | ~6 GB | 40–60 min | Excellent | | large | ~5 GB | ~10 GB | 90–120 min | Best (near human) | whisper gui windows
GPU (NVIDIA) can be 3–5x faster than CPU. While technically a full subtitle editing suite, the
Solution: The small "tiny" and "base" models often strip punctuation. Switch to small model or larger. If using WhisperDesktop, check "No Timestamps" might affect formatting—keep timestamps on. Pros: Best-in-class tools for fixing timing errors after
Best for: Video editors and YouTubers who need to create subtitles.
While primarily a subtitle editing software, the latest versions of Subtitle Edit have integrated Whisper directly into the app. You don’t need to install Python or Whisper separately; the app handles the bridge.
Verdict: If your end goal is subtitles for videos, skip the standalone transcription tools and use Subtitle Edit.