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MiMo v2.5 TTS
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MiMo v2.5 TTS is a closed-weights text-to-speech model from Xiaomi MiMo, released April 2026.
Catalogue identity notes
Source product model mimo-v2.5-tts; voice 白桦. June 2026 invocation. Do not map Azure Neural to Azure HD or Polly Neural to Polly Generative.
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 MiMo v2.5 TTS, out of 148 with a score.
| # | model | score | where |
|---|---|---|---|
| 92 |  Orpheus TTS 3B 0.1 (finetune-prod) | 47±5 | api $15.00/M chars +local |
| 93 |  Kyutai TTS 1.6B en/fr | 47±5 | local |
| 94 | MiMo v2.5 TTS | 47±4 | comparison only |
| 95 |  Amphion VALL-E (LibriLight 6k) | 47±14 | local |
| 96 |  Piper (en_US lessac medium) | 47±5 | 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 · 93% of its score
| test | result | vs the others in its run | counts |
|---|---|---|---|
| CN-NewsTTS v0.1 · strict pronunciation accuracy | 27.5% ✎ | █··▄·█··▄··▄ beats 1/6 | 93% |
$ where to run it
No verified API or download recorded yet · add one
$ how the score was worked out · CN-NewsTTS Bench v0.1 93%
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 |
|---|---|---|
 CN-NewsTTS Bench v0.1 | 1 | 93% |
| prior · pull toward the middle | 7% | |
| weighted average | = 46.7 |
$ 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