MiniMax Music 3 nodes for ComfyUI with verified model downloads, full audio VAE loading, MOSS-Music dataset preprocessing, and resumable LoRA training through a pinned SimpleTuner backend.

Features

Music 3 Loader - Downloads, verifies, and loads the MODEL, CLIP, and decoder VAE with live per-file progress
Full Audio VAE - Loads the SimpleTuner DAV encoder/decoder for waveform encoding and decoding
Intelligent Dataset Preprocessing - Uses MOSS-Music to caption, transcribe, analyze, and segment local music libraries
Large Library Support - Reads an absolute source directory at execution time without uploading or copying the source collection
LoRA Training - Runs the pinned Music 3 SimpleTuner integration in an isolated environment
Live Training Dashboard - On-node step, loss, learning-rate, progress, loss-chart, and validation-audio monitoring
Durable Runs - Preserves logs, metrics, checkpoints, validation samples, interruption state, and resume metadata
ComfyUI LoRA Export - Copies completed adapters into the standard ComfyUI LoRA folder

Nodes

| Node | Description | |------|-------------| | FL MiniMax Music 3 Loader | Downloads and loads the Music 3 diffusion model, text encoder, and decoder VAE | | FL MiniMax Music 3 Audio VAE Loader | Loads the full waveform encoder/decoder DAV | | FL MiniMax Music 3 Dataset Preprocessor | Creates captioned, transcribed, segmented Music 3 datasets with MOSS-Music | | FL MiniMax Music 3 Dataset | Validates audio, captions, lyrics, durations, and dataset identity | | FL MiniMax Music 3 Train Config | Defines LoRA rank, precision, optimizer, steps, and checkpoint behavior | | FL MiniMax Music 3 Validation Config | Defines deterministic validation caption, lyrics, duration, seed, CFG, and sampling settings | | FL MiniMax Music 3 Training Run | Loads a persisted run for inspection or resume | | FL MiniMax Music 3 LoRA Trainer | Trains, monitors, checkpoints, resumes, and exports a Music 3 LoRA |

Installation

ComfyUI Manager

Search for FL MiniMax Music 3 and install it, or open the Comfy Registry listing.

Manual

cd ComfyUI/custom_nodes
git clone https://github.com/filliptm/ComfyUI-FL-MiniMaxMusic3.git
cd ComfyUI-FL-MiniMaxMusic3
pip install -r requirements.txt

Restart ComfyUI after installation.

Quick Start

Music 3 Inference

Add FL MiniMax Music 3 Loader
Choose the model precision, text-encoder precision, CLIP device, and download policy
Connect its MODEL, CLIP, and VAE outputs to the standard MiniMax Music 3 workflow
Queue the workflow; missing artifacts download only when the node executes
Monitor verification, download, and loading progress directly on the node

Dataset Preprocessing

Put .wav, .flac, .mp3, .ogg, .m4a, or .aac files in a local directory
Add FL MiniMax Music 3 Dataset Preprocessor
Paste the directory's absolute path into source_folder
Set backend_policy and model_policy to their install/download options for the first run
Queue the node and monitor MOSS installation, model download, analysis, and segmentation in its dashboard
Connect the resulting dataset directly to the training nodes or review the generated sidecars first

The source directory is scanned recursively at execution time. Files are read in place and are not uploaded through the browser.

LoRA Training

Prepare a dataset manually or with FL MiniMax Music 3 Dataset Preprocessor
Connect Dataset -> Train Config -> LoRA Trainer
Optionally connect Validation Config for checkpoint audio samples
Set backend_policy to install_pinned_if_missing for the first run
Queue the workflow and monitor the on-node training dashboard
Use FL MiniMax Music 3 Training Run to resume an interrupted run from its latest full checkpoint

Completed adapters are saved to:

ComfyUI/models/loras/MiniMaxMusic3/<output-name>/<output-name>.safetensors

Load them with ComfyUI's standard Load LoRA (Model Only) node between the Music 3 loader and sampler.

Dataset Format

Trainer-ready datasets contain one audio file and two text sidecars per segment:

dataset/
  track_001.wav
  track_001.txt
  track_001.lyrics
  track_001.music3.json

.txt contains the musical caption
.lyrics contains lyrics and structure tags such as [verse] and [chorus]
.music3.json contains provenance, source hashes, analysis, and review state for generated segments

The preprocessor writes lossless PCM WAV segments so Windows training does not depend on TorchCodec audio decoding.

Models and Backends

| Component | Source | Purpose | |-----------|--------|---------| | MiniMax Music 3 | MiniMaxAI/MiniMax-Music3 | Diffusion model, text encoder, and decoder VAE | | Music 3 Encoder | SimpleTuner/MiniMax-Music-3-Encoder | Full waveform encoder/decoder DAV | | MOSS-Music 8B Instruct | OpenMOSS-Team/MOSS-Music-8B-Instruct | Audio captioning, transcription, structure analysis, and segmentation | | SimpleTuner | Pinned commit in training/backend_manifest.json | Music 3 LoRA training |

Inference models are stored in the normal ComfyUI model directories. MOSS-Music is checksum-verified under:

ComfyUI/models/moss_music/MOSS-Music-8B-Instruct/

Preprocessing and training dependencies are installed into separate managed environments under:

ComfyUI/user/fl_minimax_music3/backends/

They are not installed into ComfyUI's Python environment. Model and backend downloads begin only after an explicit queued node execution or dashboard action.

Runs and Recovery

Preprocessing and training runs are persisted under:

ComfyUI/user/fl_minimax_music3/

Interrupting ComfyUI requests a graceful worker exit and preserves the latest usable checkpoint. Resume validation prevents accidental changes to dataset identity, LoRA shape, precision, or output name.

Requirements

A current ComfyUI build with MiniMax Music 3 support
Python 3.10+ for the node pack; the pinned training backend currently requires Python 3.12 or 3.13
FFmpeg and FFprobe available on PATH
NVIDIA CUDA GPU with BF16 support for the initial training backend
At least 20 GiB free for training-backend installation, plus model and checkpoint storage
Approximately 16.9 GiB for the optional MOSS-Music model

The first training release targets one NVIDIA GPU. Multi-GPU, LyCORIS, full-rank training, AnyFlow, TwinFlow, CREPA, and LayerSync are not currently exposed.

Example Workflow

Start with example_workflows/MiniMax Music 3 LoRA Training.json. Its deliberately short training and validation settings are intended for installation checks; increase them for real training.

Development Tests

From the ComfyUI directory:

D:\ComfyUI\venv\Scripts\python.exe -m unittest discover -s custom_nodes\ComfyUI-FL-MiniMaxMusic3\tests -q
node --test custom_nodes\ComfyUI-FL-MiniMaxMusic3\tests\*.mjs

License

Apache-2.0. The optional training backend installs and invokes unmodified SimpleTuner as a separate AGPL-3.0-or-later program. MiniMax Music 3, the encoder, and MOSS-Music artifacts retain their respective model licenses. See NOTICE for details.