Instructions to use mlx-community/MiniMax-Music3-nvfp4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use mlx-community/MiniMax-Music3-nvfp4 with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir MiniMax-Music3-nvfp4 mlx-community/MiniMax-Music3-nvfp4
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
MiniMax Music 3 · MLX NVFP4
Native MLX NVFP4 weights for
MiniMaxAI/MiniMax-Music3,
converted for lyric-conditioned song generation on Apple Silicon with
mlx-audio. This variant is experimental
until it receives broader listening evaluation.
Community conversion, not an official MiniMax release. All model credit goes to MiniMax. Review the original model card and license before use.
Other MLX variants:
BF16
· 8-bit
· 6-bit
· 4-bit
· MXFP8
· MXFP4 (experimental)
Install
MiniMax Music 3 support is proposed in
Blaizzy/mlx-audio#888.
Until that PR is released, install the tested commit directly:
python -m pip install "mlx-audio @ git+https://github.com/pinglin/mlx-audio.git@c2fa486ddf98ea8268c227b6d624b2f9ba00dbab"
Generate
python -m mlx_audio.music.generate \
--model mlx-community/MiniMax-Music3-nvfp4 \
--caption "Warm acoustic pop, 96 BPM, intimate female vocal" \
--lyrics $'[verse]\nMorning light across the room\n[chorus]\nSing with me' \
--duration 30 \
--steps 30 \
--seed 7 \
--output song.wav
from mlx_audio.music import load
model = load("mlx-community/MiniMax-Music3-nvfp4")
result = next(
model.generate(
text="Warm acoustic pop, 96 BPM, intimate female vocal",
lyrics="[verse]\nMorning light across the room\n[chorus]\nSing with me",
duration=30,
steps=30,
seed=7,
)
)
print(result.audio.shape, result.sample_rate) # stereo, 44100 Hz
Lyrics are required by the checkpoint contract. Use [instrumental] explicitly
for instrumental generation. Duration is a requested upper bound: the
autoregressive stage may emit its end token early. Style, tempo, instrument, and
vocal controls are probabilistic rather than strict.
Quantization and verification
- NVFP4 weight quantization with group size 16.
- Large linears in the global language model, RVQ depth decoder, and flow transformer are quantized. Embeddings, output heads, convolutions, condition encoder, and vocoder remain dense for fidelity.
- The two weight shards total 9,199,077,544 bytes.
- Strict loading and real generation produced finite 44.1 kHz stereo audio.
- The mlx-audio regression suite passed 1,742 tests with 34 expected skips; the focused music, converter, and registry suite passed 43 tests and 3 subtests.
Converted with mlx-audio 0.4.8 development commit c2fa486 and MLX 0.31.2.
License
The weights remain subject to the
MiniMax-Music3 Community License,
including its acceptable-use and commercial terms. The full license text is
included in this repository.
- Downloads last month
- -
4-bit
Model tree for mlx-community/MiniMax-Music3-nvfp4
Base model
MiniMaxAI/MiniMax-Music3