README.md

---
license: apache-2.0
pipeline_tag: text-to-speech
language:
  - en
  - zh
  - fr
  - de
  - es
tags:
  - text-to-speech
  - voice-cloning
---

[EN](README.md) | [中文](README_zh.md)

## CuteTTS: Efficient and High-Quality Speech Synthesis via Autoregressive Modeling of Continuous Latents

<a href="https://github.com/OPPO-Mente-Lab/CuteTTS"><img src="https://img.shields.io/badge/GitHub-CuteTTS-black?logo=github" alt="GitHub"></a>
<a href="https://arxiv.org/abs/2608.08638"><img src="https://img.shields.io/badge/Paper-CuteTTS-red" alt="paper"></a>

![CuteTTS logo](assets/logo.png)

- A lightweight (~230M-parameter) continuous autoregressive TTS model that runs efficiently on GPUs, CPUs, and Apple silicon.
- Ultra-low latency: ~40 ms to the first audio chunk and a throughput of ~9× real time on an NVIDIA RTX 4090.
- Excellent speech quality and voice cloning performance.
- Web demo, Python API, and CLI.
- Multilingual support: English, Chinese, French, German, and Spanish.

<br>

<img src="assets/cute_backbone.png" alt="CuteTTS architecture" width="100%">

<br>

<img src="assets/performance.svg" alt="CuteTTS performance" width="85%">


## Zero-shot voice-cloning performance

| <sub>Model</sub> | <sub>Params.</sub> | <sub>LibriSpeech test-clean WER (%) ↓</sub> | <sub>LibriSpeech test-clean SIM ↑</sub> | <sub>Seed-TTS EN WER (%) ↓</sub> | <sub>Seed-TTS EN SIM ↑</sub> | <sub>Seed-TTS ZH WER (%) ↓</sub> | <sub>Seed-TTS ZH SIM ↑</sub> |
|:--|--:|--:|--:|--:|--:|--:|--:|
| <sub>MOSS&#8209;TTS</sub> | <sub>8B</sub> | <sub>1.98</sub> | <sub>67.7</sub> | <sub>1.84</sub> | <sub>70.9</sub> | <sub>1.37</sub> | <sub>77.0</sub> |
| <sub>Qwen3&#8209;TTS</sub> | <sub>1.7B</sub> | <sub>2.35</sub> | <sub>70.3</sub> | <sub>1.66</sub> | <sub>71.4</sub> | <sub><strong>0.91</strong></sub> | <sub>77.0</sub> |
| <sub>FireRedTTS&#8209;2</sub> | <sub>1.5B</sub> | <sub>4.32</sub> | <sub>64.2</sub> | <sub>1.95</sub> | <sub>66.5</sub> | <sub>1.14</sub> | <sub>73.6</sub> |
| <sub>MOSS&#8209;TTS&#8209;Nano</sub> | <sub>0.1B</sub> | <sub>4.10</sub> | <sub>48.4</sub> | <sub>4.62</sub> | <sub>49.9</sub> | <sub>3.13</sub> | <sub>64.3</sub> |
| <sub>F5&#8209;TTS</sub> | <sub>0.3B</sub> | <sub>2.42</sub> | <sub>66.0</sub> | <sub>1.83</sub> | <sub>67.0</sub> | <sub>1.56</sub> | <sub>76.0</sub> |
| <sub>ZipVoice</sub> | <sub>0.1B</sub> | <sub>2.05</sub> | <sub>67.4</sub> | <sub>1.70</sub> | <sub>69.7</sub> | <sub>1.40</sub> | <sub>75.1</sub> |
| <sub>IndexTTS2</sub> | <sub>1.5B</sub> | <sub>2.47</sub> | <sub>70.0</sub> | <sub>2.22</sub> | <sub>70.6</sub> | <sub>1.02</sub> | <sub>76.5</sub> |
| <sub>CosyVoice&nbsp;3</sub> | <sub>0.5B</sub> | <sub>1.99</sub> | <sub>69.7</sub> | <sub>2.02</sub> | <sub>71.8</sub> | <sub>1.16</sub> | <sub>78.0</sub> |
| <sub>VoxCPM2</sub> | <sub>2B</sub> | <sub>3.01</sub> | <sub>74.0</sub> | <sub>1.84</sub> | <sub>75.3</sub> | <sub>0.97</sub> | <sub><strong>79.5</strong></sub> |
| <sub>VibeVoice</sub> | <sub>1.5B</sub> | <sub>–</sub> | <sub>–</sub> | <sub>3.04</sub> | <sub>68.9</sub> | <sub>1.16</sub> | <sub>74.4</sub> |
| <sub>DiTAR</sub> | <sub>0.6B</sub> | <sub>2.39</sub> | <sub>67.0</sub> | <sub>1.69</sub> | <sub>73.5</sub> | <sub>1.02</sub> | <sub>75.3</sub> |
| <sub>VibeVoice&#8209;Realtime</sub> | <sub>0.5B</sub> | <sub>2.00</sub> | <sub>69.5</sub> | <sub>2.05</sub> | <sub>63.3</sub> | <sub>–</sub> | <sub>–</sub> |
| <sub>Pocket&nbsp;TTS</sub> | <sub>0.1B</sub> | <sub><strong>1.59</strong></sub> | <sub>49.1</sub> | <sub><strong>1.63</strong></sub> | <sub>50.7</sub> | <sub>–</sub> | <sub>–</sub> |
|  |  |  |  |  |  |  |  |
| <sub><strong>CuteTTS</strong></sub> | <sub>0.2B</sub> | <sub>2.16</sub> | <sub><strong>78.9</strong></sub> | <sub>2.04</sub> | <sub><strong>76.5</strong></sub> | <sub>1.41</sub> | <sub>77.8</sub> |
| <sub><strong>CuteTTS&#8209;distill</strong></sub> | <sub>0.2B</sub> | <sub>2.41</sub> | <sub>76.8</sub> | <sub>2.03</sub> | <sub>74.2</sub> | <sub>1.47</sub> | <sub>75.6</sub> |