Microsoft MAI-Transcribe-1.5
B Tier · 7.9/10
Microsoft's in-house speech-recognition model -- MAI-Transcribe-1.5 launched 2026-06-02 at Build: 43 languages (up from 25), best-in-class FLEURS WER, transcribes 1hr of audio in under 15s (was 53s), and new keyword-biasing cuts WER ~30%. #3 on Artificial Analysis at 2.4% WER. Now integrated into Copilot, Teams, GitHub, and Dynamics 365 Contact Center. Original MAI-Transcribe-1 shipped 2026-04-02 at $0.36/hr
Score Breakdown
The Good and the Bad
What we like
- +#1 on FLEURS WER overall is a genuinely significant benchmark result -- beats Whisper-large-v3, ElevenLabs Scribe v2, OpenAI gpt-4o-transcribe, and Gemini 3.1 Flash-Lite per Microsoft's published comparisons. Expect third-party verification through Q2 2026
- +Handles noise, overlapping speech, and accented / code-switched audio noticeably better than Whisper in Microsoft's published evaluations -- the real-world robustness story matters more than the headline WER for meeting transcription and IVR workflows
- +Pricing at $0.36/hour of audio is competitive with Whisper-as-a-service pricing on most providers and substantially cheaper than ElevenLabs Scribe v2 for high-volume use cases
- +25 language support with #1 WER in 11 top languages means this is a real global product, not just an English-first model with a long tail of poorly-supported locales
What could be better
- −Competes with the raw-model tier (Whisper, gpt-4o-transcribe, Scribe v2, Gemini Flash-Lite) -- NOT with meeting apps like Otter, Fireflies, or Descript, which sit higher in the stack and would likely adopt MAI-Transcribe-1 as a backend option rather than compete with it. If you want a meeting UX, stay with your current app
- −Foundry-only at launch means you need an Azure account and engineering work. No consumer-facing UI. Otter.ai, Fireflies, and Descript remain the right answer for end-user transcription workflows
- −Microsoft's published benchmarks are self-reported. Independent FLEURS-leaderboard confirmation is still pending -- third-party verification typically lags announcement by 4-8 weeks
- −MAI Playground access is US-only during public preview. International evaluators must use the API
Pricing
MAI-Transcribe-1.5 (Azure Foundry, launched 2026-06-02)
- ✓43 supported languages (up from 25)
- ✓Best-in-class FLEURS WER; #3 on Artificial Analysis at 2.4% WER
- ✓Transcribes 1 hour of audio in under 15s (was 53s)
- ✓Keyword biasing: ~30% WER reduction on FLEURS for domain terms
- ✓Microsoft: 'most cost-effective transcription model of any hyperscaler'
MAI-Transcribe-1 (original, 2026-04-02)
- ✓25 supported languages
- ✓~3.8% average WER across FLEURS benchmark
- ✓2.5x faster than Azure Fast transcription
- ✓Reference price point for the 1.5 generation pending vendor disclosure
MAI Playground (Free preview)
- ✓US-only web playground for testing
- ✓Rate-limited preview
- ✓Evaluation only -- no commercial use
Known Issues
- VERSION BUMP (2026-06-02, Microsoft Build): MAI-Transcribe-1.5 launched in the 'seven new MAI models' wave. Vendor-published changes vs 1.0: language coverage expanded from 25 to 43; speed improved to under 15 seconds per hour of audio (from 53s); new keyword-biasing feature delivers a ~30% WER reduction on the FLEURS multilingual benchmark by applying domain terminology intelligently (context-aware, not blind keyword forcing). Microsoft claims 'best-in-class Word Error Rate across 43 languages' and #3 on the Artificial Analysis leaderboard at 2.4% WER, describing it as 'the fastest, most efficient and most cost-effective transcription model of any hyperscaler.' Now being integrated into Copilot, Teams, GitHub, and Dynamics 365 Contact Center; available through Foundry. Per-hour pricing not disclosed at launch.Source: Microsoft AI (microsoft.ai/news/mai-transcribe-1-5more-accurate-context-aware-and-built-for-production/, microsoft.ai/news/building-a-hillclimbing-machine-launching-seven-new-mai-models/) · 2026-06-02
- Public preview in US only for MAI Playground. Foundry API works globally but you need an Azure subscription to evaluateSource: Microsoft AI launch post · 2026-04
- Competitor positioning on the site: MAI-Transcribe-1 is a backend model, not a meeting-transcription product. Do not position it as an Otter.ai competitor -- it competes with Whisper and would typically be adopted BY meeting apps, not replace themSource: Microsoft model card + tech analysis · 2026-04
Best for
Developers and enterprises who need best-in-class multilingual speech-to-text for high-volume use cases (meeting recording pipelines, call-center transcription, accessibility captioning at scale, multilingual audio indexing). Especially relevant for Azure shops already on Microsoft infrastructure.
Not for
End-user meeting transcription -- use Otter.ai, Fireflies, or Descript for that. Also not the right answer for on-device / edge transcription -- use Whisper-tiny or a compressed local model there. MAI-Transcribe-1 is a cloud-API tier-1 accuracy play.
Our Verdict
MAI-Transcribe-1.5 (2026-06-02) widens the lead Microsoft opened in April. Going from 25 to 43 languages while pushing transcription speed to under 15 seconds per audio hour -- a 3.5x speedup -- and adding context-aware keyword biasing (a ~30% WER cut on domain terms) makes this a serious production backend, not just a benchmark flex. The #3 Artificial Analysis placement at 2.4% WER and the 'most cost-effective of any hyperscaler' framing position it as the default speech-to-text layer for Azure shops. It is now baked into Copilot, Teams, GitHub, and Dynamics 365 Contact Center, so most Microsoft customers get it without a separate integration. For consumer meeting transcription, Otter/Fireflies/Descript remain the right end-user products -- but their Whisper-based backends now have a faster, cheaper, more multilingual alternative to evaluate. Per-hour pricing for 1.5 is still undisclosed; that is the one open question.
Sources
- Microsoft AI: MAI-Transcribe-1.5 -- more accurate, context-aware, built for production (2026-06-02) (accessed 2026-06-02)
- Microsoft AI: Launching seven new MAI models (2026-06-02) (accessed 2026-06-02)
- Microsoft AI: State-of-the-art speech recognition with MAI-Transcribe-1 (accessed 2026-04-17)
- Microsoft AI: 3 new MAI models in Foundry (accessed 2026-04-17)
- MAI-Transcribe-1 model card PDF (accessed 2026-04-17)
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