---
title: MOSS-Audio-Tokenizer-MLX-8bit
canonical_url: "https://www.modelscope.cn/models/mlx-community/MOSS-Audio-Tokenizer-MLX-8bit"
md_url: "https://www.modelscope.cn/models/mlx-community/MOSS-Audio-Tokenizer-MLX-8bit.md"
repository: mlx-community/MOSS-Audio-Tokenizer-MLX-8bit
last_updated: 2026-04-16
license: apache-2.0
pipeline_tag: feature-extraction
tasks:
  - feature-extraction
base_model:
  - OpenMOSS-Team/MOSS-Audio-Tokenizer
base_model_relation: quantized
parameters: 500.8M
tensor_type:
  - F32
  - U32
library_name:
  - mlx
  - safetensors
  - pytorch
frameworks:
  - pytorch
language:
  - zh
  - en
downloads: 26
stars: 0
tags:
  - mlx
  - audio
  - speech
  - codec
  - tokenizer
  - apple-silicon
  - quantized
  - 8bit
---

# MOSS-Audio-Tokenizer-MLX-8bit

> MOSS-Audio-Tokenizer-MLX-8bit - mlx-community 在 ModelScope 开源的模型。MOSS Audio Tokenizer — MLX 8-bit

mlx-community/MOSS-Audio-Tokenizer-MLX-8bit 是 ModelScope 魔搭社区上的 500.8M 参数feature-extraction模型，采用 apache-2.0 许可，基于 OpenMOSS-Team/MOSS-Audio-Tokenizer 构建。

- **Repository**: mlx-community/MOSS-Audio-Tokenizer-MLX-8bit
- **License**: apache-2.0
- **Tasks**: feature-extraction
- **Parameters**: 500.8M
- **Base model**: OpenMOSS-Team/MOSS-Audio-Tokenizer
- **Tags**: mlx, audio, speech, codec, tokenizer, apple-silicon, quantized, 8bit
- **Downloads**: 26
- **Stars**: 0
- **Last updated**: 2026-04-16

Source: https://www.modelscope.cn/models/mlx-community/MOSS-Audio-Tokenizer-MLX-8bit

---

# MOSS Audio Tokenizer — MLX 8-bit

This repository contains an MLX-native int8 conversion of the MOSS Audio Tokenizer for Apple Silicon.

> Note
> This repo is a community mirror of the canonical MLX conversion maintained by
> [AppAutomaton](https://github.com/appautomaton) at
> [`appautomaton/openmoss-audio-tokenizer-mlx`](https://huggingface.co/appautomaton/openmoss-audio-tokenizer-mlx).

## Variants

| Path | Precision |
| --- | --- |
| `mlx-int8/` | int8 quantized weights |

## Model Details

- Developed by: AppAutomaton
- Shared by: `mlx-community`
- Original MLX repo: [`appautomaton/openmoss-audio-tokenizer-mlx`](https://huggingface.co/appautomaton/openmoss-audio-tokenizer-mlx)
- Upstream model: [`OpenMOSS-Team/MOSS-Audio-Tokenizer`](https://huggingface.co/OpenMOSS-Team/MOSS-Audio-Tokenizer)
- Task: audio tokenization and codec decoding
- Runtime: MLX on Apple Silicon

## How to Get Started

Load it directly with [`mlx-speech`](https://github.com/appautomaton/mlx-speech):

```python
from mlx_speech.models.moss_audio_tokenizer import MossAudioTokenizerModel

model = MossAudioTokenizerModel.from_path("mlx-int8")
```

The tokenizer is loaded automatically when you run OpenMOSS generation scripts. You usually do not need to instantiate it directly.

```bash
python scripts/generate/moss_local.py \
  --text "Hello from mlx-speech." \
  --output outputs/out.wav
```

## Notes

- This repo contains the quantized MLX runtime artifact only.
- The conversion remaps the original MOSS audio tokenizer weights explicitly for MLX inference.
- The artifact is shared by the OpenMOSS local TTS, TTSD, and SoundEffect runtime paths in this repo family.
- This mirror is a duplicated repo, not an automatically synchronized namespace mirror.

## Links

- Canonical MLX repo: [`appautomaton/openmoss-audio-tokenizer-mlx`](https://huggingface.co/appautomaton/openmoss-audio-tokenizer-mlx)
- Source code: [`mlx-speech`](https://github.com/appautomaton/mlx-speech)
- More examples: [AppAutomaton](https://github.com/appautomaton)

## License

Apache 2.0 — following the upstream license published with [`OpenMOSS-Team/MOSS-Audio-Tokenizer`](https://huggingface.co/OpenMOSS-Team/MOSS-Audio-Tokenizer).