Instructions to use FenomAI/MiniMax-Music3 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

Notebooks
Google Colab
Kaggle
Local Apps Settings

How to use FenomAI/MiniMax-Music3 with llama.cpp:

Install (macOS, Linux)

curl -LsSf https://llama.app/install.sh | sh
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf FenomAI/MiniMax-Music3:F16
# Run inference directly in the terminal:
llama cli -hf FenomAI/MiniMax-Music3:F16

Install from WinGet (Windows)

winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf FenomAI/MiniMax-Music3:F16
# Run inference directly in the terminal:
llama cli -hf FenomAI/MiniMax-Music3:F16

Use pre-built binary

# Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases
# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf FenomAI/MiniMax-Music3:F16
# Run inference directly in the terminal:
./llama-cli -hf FenomAI/MiniMax-Music3:F16

Build from source code

git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf FenomAI/MiniMax-Music3:F16
# Run inference directly in the terminal:
./build/bin/llama-cli -hf FenomAI/MiniMax-Music3:F16

Use Docker

docker model run hf.co/FenomAI/MiniMax-Music3:F16

LM Studio
Jan
Ollama
How to use FenomAI/MiniMax-Music3 with Ollama:
```
ollama run hf.co/FenomAI/MiniMax-Music3:F16
```

Unsloth Studio

How to use FenomAI/MiniMax-Music3 with Unsloth Studio:

Install Unsloth Studio (macOS, Linux, WSL)

curl -fsSL https://unsloth.ai/install.sh | sh
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for FenomAI/MiniMax-Music3 to start chatting

Install Unsloth Studio (Windows)

irm https://unsloth.ai/install.ps1 | iex
# Run unsloth studio
unsloth studio -H 0.0.0.0 -p 8888
# Then open http://localhost:8888 in your browser
# Search for FenomAI/MiniMax-Music3 to start chatting

Using HuggingFace Spaces for Unsloth

# No setup required
# Open https://huggingface.co/spaces/unsloth/studio in your browser
# Search for FenomAI/MiniMax-Music3 to start chatting

Docker Model Runner
How to use FenomAI/MiniMax-Music3 with Docker Model Runner:
```
docker model run hf.co/FenomAI/MiniMax-Music3:F16
```

Lemonade

How to use FenomAI/MiniMax-Music3 with Lemonade:

Pull the model

# Download Lemonade from https://lemonade-server.ai/
lemonade pull FenomAI/MiniMax-Music3:F16

Run and chat with the model

lemonade run user.MiniMax-Music3-F16

List all available models

lemonade list

Atomic Chat

MiniMax-Music3 / README.md

FenomAI

Duplicate from scragnog/MiniMax-Music3-GGUF

b107b26 4 days ago

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metadata

license: other
license_name: minimax-music3-community-license
license_link: https://huggingface.co/MiniMaxAI/MiniMax-Music3/blob/main/LICENSE
base_model: MiniMaxAI/MiniMax-Music3
tags:
  - gguf
  - music-generation
  - text-to-music
  - hot-step-cpp

MiniMax-Music3 — GGUF (f16)

GGUF conversion of MiniMaxAI/MiniMax-Music3 for HOT-Step CPP, a fully local desktop app for AI music generation with a native C++/GGML engine. As far as we know this is the first GGUF conversion of this model.

These files are downloaded automatically by HOT-Step's Model Manager when the MiniMax-Music3 backend is selected. They are not usable with llama.cpp alone: mm3-lm-f16.gguf is structurally a Qwen3 GGUF, but music generation requires the full five-module pipeline (LM → RVQ depth decoder → condition encoder → flow-matching DiT → vocoder) implemented in HOT-Step's engine.

Files

File	Size	Contents
`mm3-lm-f16.gguf`	17.2 GB	Global LM (8.59B, Qwen3 arch, 200k vocab incl. 16,384 semantic audio codes) + full tokenizer
`mm3-synth-f16.gguf`	6.4 GB	RVQ depth decoder (0.6B) + condition encoder (25M) + flow DiT (2.4B) + vocoder (54M), namespaced `depth.` / `cond.` / `dit.` / `voc.`
`LICENSE`	—	MiniMax-Music3 Community License (governs the weights)

Output: 44.1 kHz 16-bit stereo, up to 5 minutes. VRAM: ~24 GB at f16 (quantized variants may follow).

Conversion provenance

Converted 2026-08-13 with HOT-Step's engine/tools/convert-mm3.py from the bf16/fp16 safetensors published by MiniMax (via the Comfy-Org repackage). Vocoder weight-norm folded at conversion; vocoder and DiT Fourier/RoPE bases pinned F32; all 911 tensors shape-validated. The HOT-Step implementation is parity-validated against the official diffusers reference (per-module correlation ≥ 0.9999 vs fp32; full-pipeline replay 0.9988).

License

The model weights are subject to the MiniMax-Music3 Community License (included here as LICENSE, per its notice-preservation requirement). Notable terms: prominent display of "MiniMax-Music3" in commercial products, separate authorization above US$20M annual revenue, acceptable-use policy, and clear disclosure of AI generation for publicly distributed outputs. The conversion adds no additional restrictions.