Instructions to use mlx-community/IndexTTS-2-MLX with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use mlx-community/IndexTTS-2-MLX with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir IndexTTS-2-MLX mlx-community/IndexTTS-2-MLX
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
IndexTTS-2-MLX
IndexTeam/IndexTTS-2 converted to MLX safetensors (fp32) for native Apple Silicon inference, with mlx-indextts.
IndexTTS-2 is a zero-shot voice-cloning TTS system with emotion control. It clones a voice from a single short reference clip (5–15 s) and synthesizes Chinese and English speech with optional explicit emotion vectors.
Model files
| File | Description |
|---|---|
gpt.safetensors |
GPT semantic-code generator (autoregressive) |
s2mel.safetensors |
S2Mel flow-matching mel decoder |
bigvgan.safetensors |
BigVGAN v2 vocoder (22.05 kHz, 80-band) |
vq2emb.safetensors |
Semantic-code → embedding table |
feat1.pt / feat2.pt |
Speaker-style / emotion matrices for explicit emotion control |
wav2vec2bert_stats.pt |
w2v-BERT feature normalization statistics |
tokenizer.model / config.yaml / config.json |
Text front end and runtime configs |
LICENSE.txt / LICENSE_ZH.txt |
Upstream IndexTTS-2 license |
Auxiliary encoders (w2v-BERT 2.0, MaskGCT semantic codec, CAMPPlus) are loaded from their original upstream checkpoints at runtime; see the inference repo for details.
Use with mlx-indextts
git clone https://github.com/Jup33Q/mlx-indextts
cd mlx-indextts && uv sync
hf download Jup33QE/IndexTTS-2-MLX --local-dir models/IndexTTS-2-MLX
HF_HUB_OFFLINE=1 uv run python -m mlx_indextts.generate_v2 \
--model-dir models/IndexTTS-2-MLX \
--reference path/to/reference.wav \
--text "你好,这是一段 MLX 原生推理的中文语音。" \
--output out.wav
Conversion notes
- Converted from the official PyTorch checkpoints with
mlx_indextts/convert_v2.py, fully offline from local weights. - Layer-wise alignment vs PyTorch (MPS): end modules match within fp32 tolerance (BigVGAN full-model MAE 6.8e-3, emotion pipeline ~5e-4); a few intermediate layers show device-level numerical outliers that do not affect end-to-end output.
- Verified end-to-end on Apple M5 Max: Mandarin synthesis RTF ≈ 1.9 (fp32, batch).
License
IndexTTS-2 weights are released under the upstream IndexTTS license — see
LICENSE.txt (English) and LICENSE_ZH.txt (Chinese), which are included in this
repo and apply to the converted weights as well. The MLX conversion code lives in
mlx-indextts under its own license.
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Base model
IndexTeam/IndexTTS-2