README.md

---
license: openrail
language:
    - en
    - ko
    - es
    - pt
    - fr
pipeline_tag: text-to-speech
tags:
    - text-to-speech
    - speech-synthesis
    - tts
    - onnx
library_name: supertonic
---

# Supertonic 2 — Lightning Fast, On-Device TTS, Multilingual TTS

![Supertonic Preview](img/supertonic_preview_0.1.jpg)

<p align="center">
  <a href="https://huggingface.co/spaces/Supertone/supertonic-2"><img src="https://img.shields.io/badge/🤗_Demo-Hugging_Face-yellow?style=for-the-badge" alt="Demo"></a>
  <a href="https://github.com/supertone-inc/supertonic"><img src="https://img.shields.io/badge/💻_Code-GitHub-black?style=for-the-badge&logo=github" alt="Code"></a>
</p>

**Supertonic** is a lightning-fast, on-device text-to-speech system designed for **extreme performance** with minimal computational overhead. Powered by ONNX Runtime, it runs entirely on your device—no cloud, no API calls, no privacy concerns.

## What's New in Supertonic 2

**Supertonic 2** extends multilingual capabilities while maintaining the same inference speed and efficiency as the original.

### 🌍 Multilingual Support

| Language | Code |
|----------|------|
| English | `en` |
| Korean | `ko` |
| Spanish | `es` |
| Portuguese | `pt` |
| French | `fr` |

### ⚡ Same Speed, More Languages

- **No speed degradation**: Supertonic 2 delivers the same ultra-fast inference speed as the original—up to **167× faster than real-time**
- **Efficient architecture**: Only **66M parameters**, optimized for on-device deployment
- **Cross-language consistency**: All supported languages share the same model architecture and inference pipeline

## Performance

We evaluated Supertonic's performance (with 2 inference steps) using two key metrics across input texts of varying lengths: Short (59 chars), Mid (152 chars), and Long (266 chars).

**Metrics:**
- **Characters per Second**: Measures throughput by dividing the number of input characters by the time required to generate audio. Higher is better.
- **Real-time Factor (RTF)**: Measures the time taken to synthesize audio relative to its duration. Lower is better (e.g., RTF of 0.1 means it takes 0.1 seconds to generate one second of audio).

### Characters per Second
| System | Short (59 chars) | Mid (152 chars) | Long (266 chars) |
|--------|-----------------|----------------|-----------------|
| **Supertonic** (M4 pro - CPU) | 912 | 1048 | 1263 |
| **Supertonic** (M4 pro - WebGPU) | 996 | 1801 | 2509 |
| **Supertonic** (RTX4090) | 2615 | 6548 | 12164 |
| `API` [ElevenLabs Flash v2.5](https://elevenlabs.io/docs/api-reference/text-to-speech/convert) | 144 | 209 | 287 |
| `API` [OpenAI TTS-1](https://platform.openai.com/docs/guides/text-to-speech) | 37 | 55 | 82 |
| `API` [Gemini 2.5 Flash TTS](https://ai.google.dev/gemini-api/docs/speech-generation) | 12 | 18 | 24 |
| `API` [Supertone Sona speech 1](https://docs.supertoneapi.com/en/api-reference/endpoints/text-to-speech) | 38 | 64 | 92 |
| `Open` [Kokoro](https://github.com/hexgrad/kokoro/) | 104 | 107 | 117 |
| `Open` [NeuTTS Air](https://github.com/neuphonic/neutts-air) | 37 | 42 | 47 |

> **Notes:**  
> `API` = Cloud-based API services (measured from Seoul)  
> `Open` = Open-source models  
> Supertonic (M4 pro - CPU) and (M4 pro - WebGPU): Tested with ONNX  
> Supertonic (RTX4090): Tested with PyTorch model  
> Kokoro: Tested on M4 Pro CPU with ONNX  
> NeuTTS Air: Tested on M4 Pro CPU with Q8-GGUF

### Real-time Factor

| System | Short (59 chars) | Mid (152 chars) | Long (266 chars) |
|--------|-----------------|----------------|-----------------|
| **Supertonic** (M4 pro - CPU) | 0.015 | 0.013 | 0.012 |
| **Supertonic** (M4 pro - WebGPU) | 0.014 | 0.007 | 0.006 |
| **Supertonic** (RTX4090) | 0.005 | 0.002 | 0.001 |
| `API` [ElevenLabs Flash v2.5](https://elevenlabs.io/docs/api-reference/text-to-speech/convert) | 0.133 | 0.077 | 0.057 |
| `API` [OpenAI TTS-1](https://platform.openai.com/docs/guides/text-to-speech) | 0.471 | 0.302 | 0.201 |
| `API` [Gemini 2.5 Flash TTS](https://ai.google.dev/gemini-api/docs/speech-generation) | 1.060 | 0.673 | 0.541 |
| `API` [Supertone Sona speech 1](https://docs.supertoneapi.com/en/api-reference/endpoints/text-to-speech) | 0.372 | 0.206 | 0.163 |
| `Open` [Kokoro](https://github.com/hexgrad/kokoro/) | 0.144 | 0.124 | 0.126 |
| `Open` [NeuTTS Air](https://github.com/neuphonic/neutts-air) | 0.390 | 0.338 | 0.343 |

<details>
<summary><b>Additional Performance Data (5-step inference)</b></summary>

<br>

**Characters per Second (5-step)**

| System | Short (59 chars) | Mid (152 chars) | Long (266 chars) |
|--------|-----------------|----------------|-----------------|
| **Supertonic** (M4 pro - CPU) | 596 | 691 | 850 |
| **Supertonic** (M4 pro - WebGPU) | 570 | 1118 | 1546 |
| **Supertonic** (RTX4090) | 1286 | 3757 | 6242 |

**Real-time Factor (5-step)**

| System | Short (59 chars) | Mid (152 chars) | Long (266 chars) |
|--------|-----------------|----------------|-----------------|
| **Supertonic** (M4 pro - CPU) | 0.023 | 0.019 | 0.018 |
| **Supertonic** (M4 pro - WebGPU) | 0.024 | 0.012 | 0.010 |
| **Supertonic** (RTX4090) | 0.011 | 0.004 | 0.002 |

</details>

## License

This project’s sample code is released under the MIT License. - see the [LICENSE](https://github.com/supertone-inc/supertonic?tab=MIT-1-ov-file) for details.

The accompanying model is released under the OpenRAIL-M License. - see the [LICENSE](https://huggingface.co/Supertone/supertonic-2/blob/main/LICENSE) file 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 [LICENSE](https://docs.pytorch.org/FBGEMM/general/License.html) for details.

Copyright (c) 2026 Supertone Inc.