---
title: Ming-3.0-tts-tiny-4bit
canonical_url: "https://www.modelscope.cn/models/mlx-community/Ming-3.0-tts-tiny-4bit"
md_url: "https://www.modelscope.cn/models/mlx-community/Ming-3.0-tts-tiny-4bit.md"
repository: mlx-community/Ming-3.0-tts-tiny-4bit
last_updated: 2026-10-20
license: mit
model_type:
  - lingv3_tts
architectures:
  - LingV3TTSForConditionalGeneration
base_model:
  - inclusionAI/Ming-3.0-tts-tiny
base_model_relation: quantized
library_name:
  - mlx
  - safetensors
  - pytorch
frameworks:
  - pytorch
downloads: 94
stars: 0
tags:
  - mlx
  - audio
---

# Ming-3.0-tts-tiny-4bit

> Ming-3.0-tts-tiny-4bit - mlx-community 在 ModelScope 开源的模型。Ming-3.0 TTS Tiny for MLX

mlx-community/Ming-3.0-tts-tiny-4bit 是 ModelScope 魔搭社区上的机器学习模型，采用 mit 许可，基于 inclusionAI/Ming-3.0-tts-tiny 构建。

- **Repository**: mlx-community/Ming-3.0-tts-tiny-4bit
- **License**: mit
- **Base model**: inclusionAI/Ming-3.0-tts-tiny
- **Tags**: mlx, audio
- **Downloads**: 94
- **Stars**: 0
- **Last updated**: 2026-10-20

Source: https://www.modelscope.cn/models/mlx-community/Ming-3.0-tts-tiny-4bit

---

# Ming-3.0 TTS Tiny for MLX

Converted from [inclusionAI/Ming-3.0-tts-tiny](https://huggingface.co/inclusionAI/Ming-3.0-tts-tiny).

44.1 kHz speech with built-in voices, voice cloning and style controls. Only the language backbone is quantized; acoustic modules and MoE routers retain floating-point precision. CAMPPlus speaker extraction runs natively in MLX using the bundled `speaker_encoder/campplus.safetensors`. No ONNX packages are required. A 192-value `spk_emb` may also be supplied.

```python
from mlx_audio.tts import load
model = load('dev/ming3/converted/Ming-3.0-tts-tiny-4bit', strict=True)
result = next(model.generate("Hello from MLX Audio!", voice="US_James"))
from mlx_audio.audio_io import write
write("output.wav", result.audio, result.sample_rate)
```

Offline inference on Apple Silicon using native MLX code. The tokenizer is loaded without executing remote code.