Model comparison
Compare Muse Voice Transcribe and MAI-Transcribe-2 using the same provider-sourced speech recognition & transcription rubric. No mystery score and no invented benchmark ranking.
Facts checked September 4, 2026
Set your usage. Your estimate updates as you type.
Uses the recording length in hours: 30 minutes = 0.5 hours. Extra features and minimum charges may change the bill.
Estimates exclude taxes, tools, cache storage/writes, free allowances and custom discounts. Image estimates cover output only, not prompt or reference-image charges. Quality modes differ by model. Unlisted settings are not treated as free.
| Model | Access | Estimated total (USD) |
|---|---|---|
| MAI-Transcribe-2Microsoft | Microsoft | No reviewed rate |
| Muse Voice TranscribeMeta | Meta | No reviewed rate |
Quick take
Meta's streaming speech-recognition model for live captions, long audio, many speakers, code-switching, and domain-aware transcription.
The Model API is in public preview, and the public demo's privacy statement is not a complete API data policy. Confirm endpoint regions, retention, training use, and the exact supported language list before launch.
Microsoft's fast batch transcription model for long recordings, speaker labels, word timing, keyword biasing, and clean or verbatim transcripts.
Microsoft's one-hour-in-about-ten-seconds figure is a provider claim, not a guaranteed SLA. Benchmark your own audio and confirm the post-preview price, deployment region, quotas, and retention configuration.
Compare the published facts
Values use each provider's own published units and limits. A blank means the provider did not publish a directly comparable value in the sources reviewed.
| Speech recognition & transcription | Muse Voice Transcribe | MAI-Transcribe-2 |
|---|---|---|
| Transcription priceCurrent provider price per audio hour or minute for the listed processing route. | $0.18 / audio hour | $0.10 / audio hour limited-time rate |
| Live or batchWhether the model handles realtime streams, uploaded recordings, or both. | Realtime streaming and long-form audio | Fast batch and long-form transcription |
| LanguagesProvider-published language coverage, separating trained or advertised coverage from specifically verified languages where needed. | Trained on 70+ languages; 25 specifically verified | 60 languages |
| Speaker labelsWhether the model identifies who spoke and any published speaker limit. | Yes; more than 20 speakers advertised | Yes |
| TimestampsAvailable word-, segment-, or utterance-level timing information. | Streaming transcript timing and endpointing | Word-level timestamps |
| Vocabulary controlKeyword boosting, custom spelling, context, prompting, or other ways to improve domain terms. | Language, keyword, and context biasing; code-switching | Keyword biasing, clean/verbatim output, automatic language detection |
| Where to use itDirect API, cloud catalog, application, or regional endpoint documented by the provider. | Meta Model API, Meta AI for Mac, Muse Code | Microsoft Foundry / Azure |
How to choose
Start with the job you need to complete, then validate cost, access, and policy details on your exact provider route.
Meta's launch page describes privacy for its public demo, not a complete Model API retention or training-use commitment. Review current Model API terms and enterprise controls before sending sensitive audio.
Provider and API links
Microsoft says prompts, outputs, embeddings, and training data submitted to Foundry Models are not available to model providers and are not used to train foundation models without permission. Retention and abuse-monitoring details depend on the deployed service.
Frequently asked questions
Muse Voice Transcribe: Meta's streaming speech-recognition model for live captions, long audio, many speakers, code-switching, and domain-aware transcription. MAI-Transcribe-2: Microsoft's fast batch transcription model for long recordings, speaker labels, word timing, keyword biasing, and clean or verbatim transcripts.
Consider Muse Voice Transcribe when your priority is Live captions and conversational interfaces. Consider MAI-Transcribe-2 when your priority is High-volume recorded calls and meetings. Test both with your own data and provider route before committing.
No. This comparison aligns provider-published facts for the Speech recognition & transcription category. It does not claim a universal winner or combine incompatible third-party benchmark scores.
