Instructions to use mlx-community/Audio8-TTS-Realistic-0.6b-bf16 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use mlx-community/Audio8-TTS-Realistic-0.6b-bf16 with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] hf download mlx-community/Audio8-TTS-Realistic-0.6b-bf16 --local-dir Audio8-TTS-Realistic-0.6b-bf16
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
Audio8-TTS-Realistic-0.6b-bf16 (MLX)
MLX conversion of Edge0/Audio8-TTS-Realistic-Air
(revision 925bbd4) for Apple Silicon. Upstream published this model as Audio8-TTS-Realistic-0.6b and
renamed it Realistic-Air on 2026-11-02; the weights are unchanged, so this conversion is the same model
under its new name. It is a 0.6B-parameter multilingual text-to-speech
model with zero-shot voice cloning and a bundled 44.1 kHz neural codec.
Realistic is an RL-tuned successor to Audio8-TTS-Preview-0.6b. The architecture, codec, tokenizer and tensor layout are the same; only the language-model weights differ. Anything that loads the Preview bundle loads this one.
- Language model: bf16 (as published upstream)
- Codec: fp32, converted from
codec.pthto safetensors with weight-norm folded and conv weights in MLX (channels-last) layout. Byte-identical to the Preview bundle'scodec.safetensors. - Architecture:
arktts, a DualAR transformer. A 24-layer slow AR predicts one semantic token per frame, and a 4-layer fast AR predicts 10 codec codebooks per frame.
Conversion parity vs the PyTorch reference (fp32, CPU, transformers 4.57.3):
- unit and block outputs within 1e-3
- reference-audio codec encoding is 100% code-exact
- greedy generation is token-exact over all 129 frames of the validation utterance
- decoded waveform max-abs 7.1e-6
Usage (mlx-audio)
Requires mlx-audio β₯ 0.4.7, the first release with the
arktts model family.
pip install -U "mlx-audio>=0.4.7"
import soundfile as sf
from mlx_audio.tts.utils import load
model = load("mlx-community/Audio8-TTS-Realistic-0.6b-bf16")
# zero-shot voice cloning: the reference transcript must match the reference audio
for result in model.generate(
text="Welcome to Audio8 TTS, running on Apple Silicon.",
ref_audio="reference.wav",
ref_text="Transcript of the reference clip.",
temperature=0.7, top_p=0.9, top_k=50,
):
sf.write("output.wav", result.audio, result.sample_rate)
Without ref_audio, the model synthesizes with a default voice.
For Swift, the mlx-audio8-tts-swift package
loads this bundle as Audio8RealisticPackage.
Against the Preview checkpoint
These numbers come from our own A/B of this conversion against the Preview conversion. Both cloned two English reference voices, with paired seeds, 2 draws per line, scored by Whisper-large-v3-turbo and CAM++.
| Preview-0.6b | Realistic-0.6b | |
|---|---|---|
| error rate, en / zh / de / es / fr / ja (macro) | 0.0122 | 0.0126 |
| speaker similarity (CAM++) | 0.7212 | 0.7211 |
| pause time per line | 0.62 s | 1.52 s |
On those six languages the two models score the same on accuracy and voice similarity. Realistic pauses more: its takes run about 13% longer, and all of the extra time is silence.
Supported languages
- Upstream's original 11: Cantonese, Chinese, Dutch, English, French, German, Italian, Japanese, Korean, Polish, Spanish.
- New in Realistic, measured at 1β7% error: Finnish, Indonesian, Malay, Portuguese, Russian, Turkish.
- Experimental: Hindi, Norwegian and Swedish work but are uneven, at 10β25% error.
- Not usable: Arabic, Thai and Vietnamese. Thai falls into repetition loops.
These figures come from three lines per language, two voices and two seeds. Most of the new-language lines were not checked by native speakers.
License
Apache-2.0, following the upstream model. The upstream fine-tunes the Apache-2.0 Audio8-TTS-Preview-0.6b, whose slow AR derives from Qwen2.5-0.5B (Apache-2.0). The bundled codec weights are the Preview's and carry the same license.
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Base model
Edge0/Audio8-TTS-Preview-0.6b