MOSS-TTS¶

MOSS-TTS covers OpenMOSS's 8B MossTTSDelay v1.5 and v1.0 models plus the 1.7B local-transformer variant. The MLX port uses the upstream Qwen3 backbone weights, RVQ generation path for each variant, and the full OpenMOSS-Team/MOSS-Audio-Tokenizer.

Quick Start¶

from mlx_audio.audio_io import write as audio_write
from mlx_audio.tts import load

model = load("OpenMOSS-Team/MOSS-TTS-v1.5", lazy=True)

result = next(model.generate(
    text="Hello, this is MOSS-TTS running on MLX.",
    max_tokens=120,
))
audio_write("moss_tts.wav", result.audio, result.sample_rate)

For the local-transformer variant, load:

model = load("OpenMOSS-Team/MOSS-TTS-Local-Transformer", lazy=True)

For non-English v1.5 prompts, pass language when known:

result = next(model.generate(
    text="Bonjour, je voudrais essayer une voix francaise naturelle.",
    language="French",
    max_tokens=120,
))

The v1.5 delay-pattern checkpoint also accepts inline pause markers such as [pause 3.2s].

Voice Cloning¶

result = next(model.generate(
    text="This is a short cloned voice sample.",
    ref_audio="speaker.wav",
    max_tokens=120,
))
audio_write("moss_tts_clone.wav", result.audio, result.sample_rate)

Notes¶

The model uses 24 kHz audio.
The full audio tokenizer is required for reference encoding and waveform decoding.
Batch generation and streaming are not implemented in the first MLX port.