Fireflies.ai vs Microsoft MAI-Transcribe-1
Which one should you pick? Here's the full breakdown.
Fireflies.ai
AI meeting notetaker with 6,000+ integrations that records, transcribes, and summarizes your calls
Microsoft MAI-Transcribe-1
Microsoft's first in-house speech-recognition model -- launched 2026-04-02. #1 on FLEURS WER overall, #1 by FLEURS WER in 11 of the top 25 global languages. Beats Whisper-large-v3, Scribe v2, GPT-Transcribe, Gemini 3.1 Flash-Lite. $0.36/hour of audio on Azure Foundry
| Category | Fireflies.ai | Microsoft MAI-Transcribe-1 |
|---|---|---|
| Ease of Use | 7.5 | 6.0 |
| Output Quality | 7.0 | 9.5 |
| Value | 7.5 | 9.0 |
| Features | 9.0 | 7.0 |
| Overall | 7.8 | 7.9 |
Pricing Comparison
| Feature | Fireflies.ai | Microsoft MAI-Transcribe-1 |
|---|---|---|
| Free Tier | Yes | Yes |
| Starting Price | $0 | $0.36 |
Which Should You Pick?
Pick Fireflies.ai if...
- ✓Easier to use (7.5 vs 6)
- ✓More features (9 vs 7)
Sales teams that need CRM-integrated call recording, remote teams that want searchable meeting archives, and managers who sit in too many meetings to take notes manually.
Visit Fireflies.aiPick Microsoft MAI-Transcribe-1 if...
- ✓Higher output quality (9.5 vs 7)
- ✓Better value for money (9/10)
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.
Visit Microsoft MAI-Transcribe-1Our Verdict
Fireflies.ai and Microsoft MAI-Transcribe-1 are extremely close overall. Your choice comes down to specific needs -- Fireflies.ai is better for sales teams that need crm-integrated call recording, remote teams that want searchable meeting archives, and managers who sit in too many meetings to take notes manually, while Microsoft MAI-Transcribe-1 works 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).