Two transcription engines. One choice.
convert.express lets you pick the AI model behind your transcription. Choose Whisper for maximum language coverage, or MAI-Transcribe 1.5 for best-in-class accuracy and speed. Same price either way.
Side-by-side comparison
Whisper | MAI-Transcribe 1.5Preview | |
|---|---|---|
| Word Error Rate | ~5–8% | ★2.4% (#3 globally) |
| Speed (1 hr audio) | ~60–90 s | ★< 15 s |
| Languages supported | ★57 | 43 |
| Translation | ★English only | Not supported |
| Entity biasing | Vocabulary hints (free text) | ★Up to 200 phrases |
| Speaker labeling | Yes | Yes |
| Status | ★Generally available | Public preview ★ |
| Price | €0.02 / min | €0.02 / min |
Whisper
- Word Error Rate~5–8%
- Speed (1 hr audio)~60–90 s
- Languages supported57
- TranslationEnglish only
- Entity biasingVocabulary hints (free text)
- Speaker labelingYes
- StatusGenerally available
- Price€0.02 / min
MAI-Transcribe 1.5Preview
- Word Error Rate2.4% (#3 globally)
- Speed (1 hr audio)< 15 s
- Languages supported43
- TranslationNot supported
- Entity biasingUp to 200 phrases
- Speaker labelingYes
- StatusPublic preview ★
- Price€0.02 / min
When to use each model
Whisper
- Rare or regional languages not covered by MAI
- Mixed-language audio including languages outside MAI's 43
- Production workflows where you need a GA-stable model
- Languages like Hebrew, Persian, Swahili, Welsh, and more
MAI-Transcribe 1.5
Preview- Maximum accuracy — 2.4% WER, #3 globally
- Speed-critical workflows — 1 hr of audio in under 15 s
- Professional use cases: medical, legal, research (entity biasing)
- Word-level timestamps for precise subtitle generation
About the MAI-Transcribe Preview status
MAI-Transcribe 1.5 is currently in Microsoft's public preview programme — it has no formal SLA. If the model is unavailable, convert.express automatically falls back to Whisper so your job always completes. We will promote it to default once it reaches general availability.
Model selection is in Advanced Options on the upload form — free to try.
Try it now →See also: language coverage by model · model recommendations by use case