Lyria 3 Pro (Google) vs Microsoft MAI-Transcribe-1

Which one should you pick? Here's the full breakdown.

Lyria 3 Pro (Google)

B
7.8/10

Google DeepMind's music generation model -- 3-minute structured songs with intro, verse, chorus, and outro control

Our Pick

Microsoft MAI-Transcribe-1

B
7.9/10

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

CategoryLyria 3 Pro (Google)Microsoft MAI-Transcribe-1
Ease of Use8.06.0
Output Quality8.09.5
Value7.09.0
Features8.07.0
Overall7.87.9

Pricing Comparison

FeatureLyria 3 Pro (Google)Microsoft MAI-Transcribe-1
Free TierYesYes
Starting Price$0$0.36

Which Should You Pick?

Pick Lyria 3 Pro (Google) if...

  • Easier to use (8 vs 6)
  • More features (8 vs 7)

Content creators who already pay for a Gemini or Google AI subscription and want longer, more structured AI music. Also great for developers building music features into their own apps via the $0.08/song API.

Visit Lyria 3 Pro (Google)

Pick Microsoft MAI-Transcribe-1 if...

  • Higher output quality (9.5 vs 8)
  • 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-1

Our Verdict

Lyria 3 Pro (Google) and Microsoft MAI-Transcribe-1 are extremely close overall. Your choice comes down to specific needs -- Lyria 3 Pro (Google) is better for content creators who already pay for a gemini or google ai subscription and want longer, more structured ai music, 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).