Instructions to use mlx-community/supertonic-3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use mlx-community/supertonic-3 with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir supertonic-3 mlx-community/supertonic-3
- Notebooks
- Google Colab
- Kaggle
- Local Apps
- LM Studio
- Supertonic 3 MLX
- Original Model Card
- license: openrail
language:
- en
- ko
- ja
- ar
- bg
- cs
- da
- de
- el
- es
- et
- fi
- fr
- hi
- hr
- hu
- id
- it
- lt
- lv
- nl
- pl
- pt
- ro
- ru
- sk
- sl
- sv
- tr
- uk
- vi
pipeline_tag: text-to-speech
tags:
- text-to-speech
- speech-synthesis
- tts
- onnx
- multilingual
- on-device
library_name: supertonic
- Original Model Card
- Supertonic 3 | Lightning Fast, On-Device, Accurate TTS
Supertonic 3 MLX
This repository contains a community MLX conversion of Supertone/supertonic-3.
The original ONNX graphs are converted into JSON topology plus NPZ initializers. Inference is executed with MLX arrays through the Supertonic-specific graph runtime in ailuntx/supertonic.
git clone https://github.com/ailuntx/supertonic
cd supertonic
python scripts/infer_mlx.py \
--model /path/to/supertonic-3 \
--text "Supertonic 3 is running with MLX." \
--lang en \
--voice M1 \
--total-step 8 \
--output output.wav
The MLX graph runtime has been checked against ONNX Runtime on the official assets; per-stage maximum absolute errors are around 1e-5.
Original Model Card
license: openrail language: - en - ko - ja - ar - bg - cs - da - de - el - es - et - fi - fr - hi - hr - hu - id - it - lt - lv - nl - pl - pt - ro - ru - sk - sl - sv - tr - uk - vi pipeline_tag: text-to-speech tags: - text-to-speech - speech-synthesis - tts - onnx - multilingual - on-device library_name: supertonic
Supertonic 3 | Lightning Fast, On-Device, Accurate TTS
Supertonic is a lightweight text-to-speech system for local inference. It runs with ONNX Runtime entirely on your device, with no cloud call required for synthesis.
Supertonic 3 expands the open-weight release from 5 to 31 languages, improves reading stability, and reduces repeat/skip failures.
Quick Start
Install the Python SDK and generate speech immediately. On first run, the SDK downloads the model assets from Hugging Face.
pip install supertonic
from supertonic import TTS
tts = TTS(auto_download=True)
style = tts.get_voice_style(voice_name="M1")
text = "A gentle breeze moved through the open window while everyone listened to the story."
wav, duration = tts.synthesize(text, voice_style=style, lang="en")
tts.save_audio(wav, "output.wav")
print(f"Generated {duration:.2f}s of audio")
What's New in Supertonic 3
- 31 languages: expanded from the 5-language Supertonic 2 release.
- More stable reading: fewer repeat and skip failures, especially on short and long utterances.
- Higher speaker similarity: improved similarity across the shared-language set compared with Supertonic 2.
- Expression tags: supports simple tags such as
<laugh>,<breath>, and<sigh>.
Custom Voices and Audio Samples
The open-weight package includes fixed preset voice styles for immediate local inference. If you want to hear how Supertonic 3 performs with zero-shot custom voice styles, visit the Audio Sample Demo to compare reference audio and generated speech across several use cases. To create your own Supertonic 3 voice-style JSON from reference audio, use Supertonic Voice Builder; purchased Voice Builder styles include downloadable embeddings for both Supertonic 2 and Supertonic 3.
Here are a few reference/generated pairs from the audio sample demo:
Call center, English
Text: Good morning, thank you for calling. How can I help you today?
| Reference voice | Supertonic 3 output |
|---|---|
Character voice, Japanese
Text: ใตใตใฃใ้ๅฑใใฆใใจใใใชใฎใใกใใใฉใใ้ใณ็ธๆใ่ฆใคใใใใโช
| Reference voice | Supertonic 3 output |
|---|---|
Elder character voice, Korean
Text: ํผ์ ๋ ๋๊ธฐ์ ๊ธธ์ด ํํ๊ตฌ๋. ์ด ๋ก์ ๊ฒ์ ๊ฐ์ ธ๊ฐ๊ฑฐ๋ผ. ์ธ์ ๊ฐ ์ด๋ ์ด ๋ค ์ด๋ฆ์ ๋ถ๋ฅด๋๋ผ๋, ๋ถ๋ ๋น์ ์์ง ๋ง๊ฑฐ๋ผ.
| Reference voice | Supertonic 3 output |
|---|---|
Audiobook, English
Text: I was not afraid of silence. I had lived with it long enough to know that, sometimes, it speaks more honestly than people do.
| Reference voice | Supertonic 3 output |
|---|---|
Audiobook, Japanese
Text: ใใฎๆใใญใณใใณใฎ้งใฏใใคใซใชใไฝใๅใใใใฆใใใ็งใฏใใ ใฎ่จชๅ่
ใ ใจๆใฃใฆใใใใใใผใ ใบใฎ็ฎใฏใใงใซๅฅใฎ็ต่ซใซใใฉใ็ใใฆใใใ
| Reference voice | Supertonic 3 output |
|---|---|
News, English
Text: Hereโs a story worth paying attention to. Supertone has released Supertonic 3, its on-device TTS model. This version expands support to thirty-one languages and improves reading stability.
| Reference voice | Supertonic 3 output |
|---|---|
Performance Highlights
Supertonic 3 is designed for practical on-device inference: compact enough to run locally, while staying competitive with much larger open TTS systems.
Reading Accuracy
Across measured languages, Supertonic 3 stays within a competitive WER/CER range against much larger open TTS models such as VoxCPM2, while preserving a lightweight on-device deployment path. Asterisked languages use CER; the others use WER.
Supertonic 2 to Supertonic 3
Compared with Supertonic 2, Supertonic 3 reduces repeat and skip failures, improves speaker similarity across the shared-language set, and expands language coverage from 5 to 31 languages.
Runtime Footprint
Supertonic 3 runs fast on CPU, even compared with larger baselines measured on A100 GPU, and uses substantially less memory. It does not require a GPU, which makes local, browser, and edge deployment much easier.
Model Size
At about 99M parameters across the public ONNX assets, Supertonic 3 is much smaller than 0.7B to 2B class open TTS systems. The smaller model size is a practical advantage for download size, startup time, and on-device inference.
Supported Languages
| Code | Language | Code | Language | Code | Language | Code | Language |
|---|---|---|---|---|---|---|---|
en |
English | ko |
Korean | ja |
Japanese | ar |
Arabic |
bg |
Bulgarian | cs |
Czech | da |
Danish | de |
German |
el |
Greek | es |
Spanish | et |
Estonian | fi |
Finnish |
fr |
French | hi |
Hindi | hr |
Croatian | hu |
Hungarian |
id |
Indonesian | it |
Italian | lt |
Lithuanian | lv |
Latvian |
nl |
Dutch | pl |
Polish | pt |
Portuguese | ro |
Romanian |
ru |
Russian | sk |
Slovak | sl |
Slovenian | sv |
Swedish |
tr |
Turkish | uk |
Ukrainian | vi |
Vietnamese |
License
This project's sample code is released under the MIT License. See the GitHub repository for details.
The accompanying model is released under the OpenRAIL-M License. See the LICENSE file in this repository for details.
This model was trained using PyTorch, which is licensed under the BSD 3-Clause License but is not redistributed with this project. See the PyTorch license for details.
Copyright (c) 2026 Supertone Inc.
Model tree for mlx-community/supertonic-3
Base model
Supertone/supertonic-3