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Azure Mekdes Neural
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Azure Mekdes Neural is a closed-weights text-to-speech model from Microsoft, released October 2021.
Catalogue identity notes
Exact model am-ET-MekdesNeural; voice am-ET-MekdesNeural. Dataset label Azure Mekdes Neural. No API immutable build/weight SHA supplied.
Model information sources
Score within the Vapi Humanness · Bradley–Terry rating, 2026-09-25 snapshot comparison set only.
$ how it compares
The text-to-speech models ranked either side of Azure Mekdes Neural, out of 148 with a score, then more from Microsoft.
| # | model | score | where | ||
|---|---|---|---|---|---|
| 80 | 51±5 | api $100.00/M chars | |||
| 81 | 50±16 | comparison only | |||
| 82 | 50±16 | comparison only | |||
| 83 | 50±16 | comparison only | |||
| 84 | 50±6 | local | |||
| more from Microsoft | |||||
| 70 | 53±6 | local | |||
| 140 | 23±3 | local | |||
see all text-to-speech models · find the ones that fit your machine
$ what it's good at
other tests1 not in a task · 0.2% of its score
| test | result | vs the others in its run | counts |
|---|---|---|---|
| Amharic TTS · 87-prompt CER (Chirp 3 judge) | 4.1% ✎ | ▄·····▄·▄·██ beats 4/6 | 0.2% |
$ where to run it
No verified API or download recorded yet · add one
$ how the score was worked out · Addis AI Amharic TTS benchmark 0%
Each result implies a score on its own, after adjusting for how hard its test is and who ran it. The score is their weighted average, with a small pull toward the middle for thinly tested models. Each test's weight is its counts column above; here it's added up by who ran the tests. How it works
| source | results | share of the score |
|---|---|---|
| 1 | 0% | |
| prior · pull toward the middle | 100% | |
| weighted average | = 50.2 |
$ improve this page
Use a short GitHub form or edit the data through a pull request. Every number needs a source; here's which ones we can use.
data updated · sources and licences · json