whatmodel.sh / tts / Gemini 3.8 Flash-Lite TTS

Gemini 3.8 Flash-Lite TTS

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Gemini 3.8 Flash-Lite TTS is a closed-weights text-to-speech model from Google, released September 2026. Licence: proprietary.

37.1±2.9#94 of 118 text-to-speech modelsfrom 2 benchmark results across 2 sources* 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 Gemini 3.8 Flash-Lite TTS, out of 148 with a score, then more from Google.

#modelscorewhereRAMreleased
117Pheme 300M PolyAI37±3local~3.6GB2024-01
118VoiceCraft 830M TTSEnhanced Puyuan Peng et al. (UT Austin)37±8local~4.5GB2024-04
119Gemini 3.8 Flash-Lite TTS Google37±3api price unknown2026-09
120Eleven v4 ElevenLabs37±4api $80.00/M chars2026-09
121Amphion VALL-E v2 recipe (MLS) Amphion (CUHK-Shenzhen)36±3local~2.9GB2024-06
more from Google
3Gemini 2.5 Flash Preview TTS Google72±3comparison only2025-05
6Gemini 2.5 Pro Preview TTS Google69±3comparison only2025-05
8Gemini 3.1 Flash TTS Preview Google69±2api $50.00/M chars2026-04

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

$ what it's good at

other tests1 not in a task · 97% of its score
testresultvs the others in its rundifficultycountswhy
Freya-TR-Eval Turkish TTS intelligibility (WER, faster-whisper large-v3, 8 kHz band) +11.3% ✎▄··▄··▄···▃█ beats 6/10avg 0.3%▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 97%several runs

$ where to run it

Through an API

api · price unknown · ai.google.dev ↗

$ how the score was worked out · Antalia-2 Mini model card (cl… 53%, EMA Lightning model card (can… 43%

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
Antalia-2 Mini model card (cloud0day3/antalia-mini), public Freya-TR-Eval re-run table1▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇▇ 53%Apache-2.0
EMA Lightning model card (canberkkkkkk/ema-lightning), Benchmarks: Freya-TR-Eval1▇▇▇▇▇▇▇▇▇▇▇▇▇ 43%Apache-2.0
prior · pull toward the middle▇ 3%
weighted average= 37.1

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Update model informationAdd a place to run itAdd a test resultPropose a benchmarkCorrect a benchmark scoreEdit data on GitHub

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