from mlx_audio.tts.utils import load

model = load("mlx-community/LongCat-AudioDiT-3.5B-6bit")

result = next(model.generate("Hello, this is a test of AudioDiT."))
audio = result.audio  # mlx array, 24kHz

Play audio directly:

python

from mlx_audio.tts.audio_player import AudioPlayer

player = AudioPlayer(sample_rate=24000)
result = next(model.generate("The quick brown fox jumps over the lazy dog."))
player.queue_audio(result.audio)
player.wait_for_drain()
player.stop()

Voice Cloning

Clone any voice using a reference audio sample and its transcript. Use guidance_method="apg" for best voice cloning quality:

python

result = next(model.generate(
    text="Today is warm turning to rain, with good air quality.",
    ref_audio="reference.wav",
    ref_text="Transcript of the reference audio.",
    guidance_method="apg",
    cfg_strength=4.0,
    steps=16,
))

Zero-Shot Generation (Chinese)

python

result = next(model.generate(
    text="今天晴暖转阴雨，空气质量优至良，空气相对湿度较低。",
    steps=16,
    cfg_strength=4.0,
))

Generation Parameters

Parameter	Default	Description
`steps`	16	Euler ODE solver steps. Higher = better quality, slower
`cfg_strength`	4.0	Classifier-free guidance strength
`guidance_method`	`"cfg"`	`"cfg"` for TTS, `"apg"` for voice cloning
`seed`	1024	Random seed for reproducibility
`ref_audio`	`None`	Reference audio for voice cloning (24kHz)
`ref_text`	`None`	Transcript of the reference audio

CLI

bash

# Zero-shot TTS
python -m mlx_audio.tts.generate \
  --model mlx-community/LongCat-AudioDiT-3.5B-6bit \
  --text "Hello, this is a test of AudioDiT." \
  --play

# Voice cloning
python -m mlx_audio.tts.generate \
  --model mlx-community/LongCat-AudioDiT-3.5B-6bit \
  --text "Today is warm turning to rain." \
  --ref_audio reference.wav \
  --ref_text "Transcript of the reference audio." \
  --play

License

LongCat-AudioDiT weights and code are released under the MIT License.