Medical ASR comparison

Omi vs Azure speech-to-text for healthcare.

Azure recorded the lowest overall word error on Omi's clinical board. Omi recorded the stronger medical-term, drug-name and dosage results.

The direct comparison

Criterion
Omi
Azure tested model
Medical-term error
0.94%
1.43%
Drug-name error
0.00%
0.90%
Dosage F1
97.7%
83.3%
Overall word error
5.99%
5.97%
Product breadth
Medical voice infrastructure
Broad Azure speech platform
Open local model
Available under CC-BY-4.0
Not part of the tested managed model

The evaluated Azure MAI-Transcribe-1.5 row was a preview model when tested. Its tiny overall WER lead over Omi should not be treated as a material clinical difference without your own acceptance set.

Overall WER is not the whole record

Azure's 5.97% overall WER is fractionally lower than Omi's 5.99%. Omi nevertheless leads on the domain-specific measures: medical terms, drug names and aligned dosage events. This is exactly why the benchmark separates common words from clinically consequential tokens.

Choose the weighting that matches the product. A generic call transcript may value overall WER; a medication workflow should give much more weight to drugs and dosages.

Platform versus focused layer

Azure is compelling for companies already standardised on Microsoft identity, cloud procurement, monitoring and data services. It offers realtime, fast and batch transcription plus custom speech tooling. Omi offers a narrower integration surface, transparent audio-hour rates and a medical-first benchmark and support motion.

Deployment and pricing

Azure pricing and model availability vary by region, tier and model, and the tested preview row did not have a stable public rate in the comparison snapshot. Omi publishes $0.29 batch and $0.45 live after 25 recurring hours. Enterprise customers can contract capacity or private deployment; builders can also run the open edge model locally.

Sources

Review the full Omi benchmark, Azure speech-to-text documentation and the current Azure pricing page for your region.

Decide on your own acceptance set.

25 audio-hours every month.