mlx-indextts2-2.5-8bit

IndexTTS 2.5 converted to native MLX weights for Apple Silicon. Use it with vanch007/mlx-indextts2.

Variant

  • Precision / quantization: 8bit
  • Approximate local size: 1.6GB
  • Source model: IndexTeam/IndexTTS-2.5
  • Source revision: d0aa86e75bb6f3437f3831e95056fa72842d89ef
  • Conversion status: strict manifest pass
  • Details: GPT uses persistent 8-bit group quantization; the remaining components use float16. This is the recommended default variant.

The model supports Chinese, English, Japanese, Spanish, and Arabic, including cross-lingual voice transfer, separate speaker/emotion references, manual and text-derived emotion control, and Pinyin/CMU/Kana pronunciation annotations.

Download and Run

git clone https://github.com/vanch007/mlx-indextts2.git
cd mlx-indextts2
uv sync --extra v25

hf download vanch007/mlx-indextts2-2.5-8bit \
  --local-dir models/mlx-indextts2-2.5-8bit

uv run mlx-indextts generate \
  --profile v25 \
  -m models/mlx-indextts2-2.5-8bit \
  --language zh \
  -r /path/to/reference.wav \
  -t "你好,这是 IndexTTS 2.5 的 MLX 推理测试。" \
  -o output.wav

See the project README and IndexTTS 2.5 guide for batch, API, WebUI, streaming, duration, pronunciation, and emotion-control examples.

Included Files

  • gpt.safetensors
  • codec.safetensors
  • s2mel.safetensors
  • bigvgan.safetensors
  • multilingual_zh_ja_yue_char_del.tiktoken
  • config.yaml and config.json
  • model_manifest.json and conversion_report.json
  • reference preprocessing statistics/features
  • LICENSE

The runtime additionally resolves the manifest-declared facebook/w2v-bert-2.0 and funasr/campplus preprocessing dependencies.

Validation Boundary

The converted component coverage and strict load checks passed. The project validation matrix also covers five-language synthesis, ASR sanity checks, speaker similarity, emotion modes, cross-lingual generation, batch/API/WebUI, and completed-segment streaming. Results are hardware- and sample-specific; human listening remains recommended before production use.

License and Derivative Notice

The repository code is MIT-licensed, but these converted model weights are a Derivative Work governed by the included bilibili Model Use License Agreement. Review its commercial thresholds, downstream obligations, use restrictions, and prohibited high-risk scenarios before downloading or using the model.

Any modifications made to the original model in this Derivative Work are not endorsed, warranted, or guaranteed by the original right-holder of the original model, and the original right-holder disclaims all liability related to this Derivative Work.

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