VibeVoice — MLX

VibeVoice converted and quantized for native MLX inference on Apple Silicon.

A hybrid LLM + diffusion architecture built for long-form speech and voice-conditioned generation. Works in greedy or sampled mode, and produces natural-sounding output at scale.

Variants

Path	Precision
`mlx-int8/`	int8 quantized weights

How to Get Started

Via mlx-speech:

python scripts/generate_vibevoice.py \
  --text "Hello from VibeVoice." \
  --output outputs/vibevoice.wav

from mlx_speech.generation import VibeVoiceModel

model = VibeVoiceModel.from_path("mlx-int8")

Model Details

VibeVoice uses a 9B-parameter hybrid architecture combining a Qwen2 language model backbone with a continuous diffusion acoustic decoder. Converted to MLX with explicit weight remapping — no PyTorch at inference time.

See mlx-speech for the full runtime and conversion code.

License

Apache 2.0.

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MLX

Hardware compatibility

Quantized