SyncWords vs Whisper
SyncWords
syncwords.com
Whisper
github.comSide by side
| Figure | SyncWords | Whisper |
|---|---|---|
| Price from | $135/mo | $0.01/mo |
| Free plan | — | Yes |
| Free trial | Yes | — |
| Open source | — | Yes |
| Web | Yes | — |
| Windows | — | Yes |
| macOS | — | Yes |
| Linux | — | Yes |
| API | Yes | Yes |
| Self-hosted | — | Yes |
| Plans published | 14 | 3 |
| Spec score · AI Video Caption Generators | 8.8 (#12) | 9.5 (#1) |
| Rating on G2 | 4.9 out of 5 from 25 reviews | 4.4 out of 5 from 52 reviews. |
| What it does | SyncWords provides cloud software for live translation, foreign subtitles, real-time AI voice dubbing, automatic transcription and closed-caption editing. | Whisper is a general-purpose speech-recognition model that supports multilingual transcription, speech translation and language identification. |
Plans
SyncWords
- Standard — 60 hours$1,620 a year
- Standard — 500 hours$11,250 a year
- Advanced — 2,500 hours$37,500 a year
- Advanced — 9,000 hours$81,000 a year
- AI captions pay-as-you-go$30, paid once
- 60 hours / year — Standard$1,620 a year
- Standard tier — 60 hours / year$1,620 a year
- 500 hours / year — Standard$11,250 a year
- Standard tier — 500 hours / year$11,250 a year
- 2,500 hours / year — Advanced$37,500 a year
Whisper
- Self-hosted WhisperFree
- Whisper (open-source code and model weights)Free
- Whisper API$0.01 a month
In their own words
Whisper
Whisper is an open-source speech recognition model for transcription, speech translation, language identification, and voice activity detection. Its documented command-line and Python interfaces process audio files, and it can translate speech from multiple languages into English. The repository lists six model sizes—tiny, base, small, medium, large, and turbo—with different speed and memory tradeoffs; stated VRAM needs range from about 1 GB to 10 GB, depending on size. Installation is documented through pip and requires the ffmpeg command-line tool. Rust may be needed if a prebuilt tiktoken wheel is unavailable. The code and model weights are released under the MIT License, with local installation using Python and ffmpeg. Whisper is listed for Linux, macOS, Windows, and self-hosted deployment. OpenAI says it was trained on 680,000 hours of multilingual and multitask supervised data collected from the web. Performance varies widely by language, and it does not outperform models specialized for LibriSpeech. Turbo is not trained for translation; multilingual models are recommended for translating non-English speech into English.