whatmodel.sh / tts / KittenTTS Nano 0.8

KittenTTS Nano 0.8 is an open-weights text-to-speech model from KittenML, released February 2026. Its published size is 0.014B parameters. Licence: apache-2.0.

Catalogue identity notes

Comparison-only. Paradee Table 3 row 'KittenTTS nano 0.8 (Bella)', 14.0M params, 56.8 MB fp32 file; KittenML/kitten-tts-nano-0.8-fp32 @7a1db64 (created 2026-02-19, Apache-2.0) ships kitten_tts_nano_v0_8.onnx of 56,767,095 bytes. Distinct from kitten-tts-mini-0-8 (80M) and the int8 nano repo. Needed so the two new Paradee benchmarks reach 3 catalogue models; the run itself already has Kokoro-82M and Piper lessac medium.

44.4±4.9comparison only: no current run option verifiedfrom 2 benchmark results across 1 source* thinly tested, treat the rank as provisional

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 KittenTTS Nano 0.8, out of 148 with a score.

#modelscorewhereRAMreleased
99Dia2 2B Nari Labs45±6local~8.1GB2025-11
100Amazon Polly Neural Amazon Web Services45±4api $16.00/M chars
101KittenTTS Nano 0.8 KittenML44±5comparison only2026-02
102GPT-SoVITS v2 RVC-Boss44±4local~1.1GB2024-08
103MeloTTS English MyShell44±5local~0.7GB2024-02

see all text-to-speech models · find the ones that fit your machine

$ what it's good at

other tests2 not in a task · 90% of its score
testresultvs the others in its rundifficultycountswhy
Paradee small-TTS comparison · 200 WikiText-103 sentences · UTMOS (utmos22_strong)4.01 / 5 ✎█······█···█ beats 0/2easy · avg 4.39 / 5▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 57%small run
Paradee small-TTS comparison · 200 WikiText-103 sentences · Whisper-base WER5.5% ✎▄··········█ beats 2/2avg 5.6%▇▇▇▇▇▇▇▇▇▇▇▇▇ 34%small run

$ where to run it

No verified API or download recorded yet · add one

Official weights and documentation: huggingface.co/KittenML ↗

$ how the score was worked out · Paradee: Distilling Kokoro-82… 90%

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

sourceresultsshare of the scorelicence
Paradee: Distilling Kokoro-82M into an 8M-Parameter Single-Voice TTS Model (arXiv:2610.06817v1), Table 3 small-model comparison2▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 90%CC BY 4.0
prior · pull toward the middle▇▇▇ 10%
weighted average= 44.4

$ 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