Chatterbox Nano FP16 MLX
A native FP16 MLX conversion of
ResembleAI/chatterbox-nano,
prepared by Rybib for Apple Silicon and on-device experimentation.
Chatterbox Nano and its architecture were created by Resemble AI. This is an independent conversion, not an official Resemble AI release.
Package
- Native MLX tensor names and layouts
- FP16 floating-point weights; no 4-bit quantization
- Nano's distilled mean-flow speech decoder
- English tokenizer and default voice conditioning
- Approximately 697 MB for speech generation
- Bundled S3TokenizerV2 companion model for offline voice cloning
- Approximately 1.16 GB total with voice cloning
The converter strictly verifies that every required Nano decoder and vocoder parameter is mapped. It also merges PyTorch weight-normalization parameters into inference weights and converts convolution/GPT-2 layouts for MLX.
Quality
Listening tests on Apple Silicon found the output perceptually equivalent to the official FP32 Nano model. This is not a formal benchmark; applications should perform their own voice-cloning and long-form tests.
Usage
This package requires a Chatterbox Nano-capable MLX Audio runtime. At the time of conversion, upstream MLX Audio did not correctly map all Nano mean-flow decoder tensors without the accompanying runtime/converter fixes.
Voice cloning additionally requires the S3TokenizerV2 speech tokenizer. It is
included under S3TokenizerV2/ so applications can clone voices completely
offline after one installation.
Provenance and license
- Base model:
ResembleAI/chatterbox-nano - Upstream code:
resemble-ai/chatterbox - MLX ecosystem:
Blaizzy/mlx-audio - Speech tokenizer:
mlx-community/S3TokenizerV2 - Conversion precision: IEEE FP16
- Conversion owner: Rybib
The upstream Chatterbox model is distributed under the MIT License. Its
copyright notice is preserved in LICENSE.