Instructions to use whitelabel/mlx-q6-higgs-tts-3-4b with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use whitelabel/mlx-q6-higgs-tts-3-4b with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir mlx-q6-higgs-tts-3-4b whitelabel/mlx-q6-higgs-tts-3-4b
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
mlx-q6-higgs-tts-3-4b
Derived from Higgs TTS 3, licensed from Boson AI USA, Inc.
This model was converted to MLX format from bosonai/higgs-tts-3-4b using mlx-audio 0.4.5 (6-bit, group_size 64, 6.550 bpw). Refer to the original model card for more details.
License
Research and non-commercial use only, per the included LICENSE (Boson Higgs TTS 3 Research and Non-Commercial License). Commercial use requires a separate license from Boson AI (contact@boson.ai). The Boson Acceptable Use Policy applies. See the NOTICE file for attribution and the list of modifications.
Requirements
- mlx-audio ≥ 0.4.5
- Apple Silicon with 8 GB unified memory is enough (~3.7 GB of weights) — works even on the entry-level MacBook Neo (A18 Pro, 8 GB)
model_typeinconfig.jsonis already patched tohiggs_audio_v3— without this patch, model detection in mlx-audio 0.4.5 is non-deterministic (see Blaizzy/mlx-audio#854)
What was changed
- Quantized to 6-bit (group_size 64, affine, 6.550 bpw) with the official
mlx_audio.convertfrom mlx-audio 0.4.5. - Audio codec weights extracted from the LM checkpoint into
codec.safetensors. model.safetensors.index.jsonremoved (required for mlx-audio codec discovery).config.jsonmodel_typeset tohiggs_audio_v3(washiggs_multimodal_qwen3).
See NOTICE for the full modification list.
Performance
Probe benchmark on a MacBook Neo (A18 Pro, 8 GB unified memory), mlx-audio 0.4.5:
| Type | Chars | RTF avg |
|---|---|---|
| short | 22 | 7.28 |
| medium | 195 | 2.06 |
| long | 450 | 2.12 |
| voice clone | 55 | 6.58 |
Model load: 4.5 s. The benchmark ran with memory pressure from other apps
(3 GB used, swap active), so these RTF numbers may be slightly pessimistic.
Listening evaluation: quality is good — the first usable MLX quant of Higgs v3. A 4-bit quant (4.56 bpw) of the same model was rejected in listening tests.
Samples
Generated with the default voice from this repository's weights (downloaded back from the Hub, so they also serve as an end-to-end integrity check). The English sample is the exact command from Usage below.
English — “Hello from the 6-bit Higgs TTS.”
Russian — «Привет! Это шестибитный квант Higgs TTS, запущенный на MacBook Neo.»
Usage
python -m mlx_audio.tts.generate --model whitelabel/mlx-q6-higgs-tts-3-4b \
--text "Hello from the 6-bit Higgs TTS." --file_prefix hello
The output is written as hello_000.wav to the current directory (use
--output_path DIR to change it). For voice cloning, pass --ref_audio ref.wav
and --ref_text "transcript of the reference".
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Base model
bosonai/higgs-tts-3-4b