FL YuE2 · Load Models

YuE was the January 2025 "Suno at home" moment - a 787-point r/StableDiffusion thread, and then a year of people discovering that a 4090 needed about six minutes to produce thirty seconds of music, that a single 2:30 track could eat nineteen gigs of VRAM and an hour of your evening, and that the install itself was a fight. The model was good. Running it was a chore.

This node is the modern answer to that chore: one loader that puts YuE2-3B and its decoder where ComfyUI expects them, using ComfyUI's own memory management, without installing the upstream YuE2 package or touching your Torch. It's the first node in every workflow in this pack, and it's where the pack's two hard requirements live.

What it actually does

It has exactly one widget, download_missing (on by default), and it hands back two things: music_model and audio_decoder. The first is the 3B language-model-ish backbone that writes scores and music tokens; the second is the separate stereo VAE that turns latents into waveform. They're loaded as two independent ComfyUI model patchers, which is why you can, if you want, mix and match - one loader per branch, or one loader feeding several Compose/Render chains. In the shipped example workflow, a single loader feeds the editable-score branch and the generation branch at once.

On the first queued run it downloads about 7.8 GB from Hugging Face into:

ComfyUI/models/yue2/YuE2-3B/
ComfyUI/models/yue2/YuE2-Vae/

The downloader is more careful than most node packs. Transfers go to .partial files and resume with a Range request, it verifies the weight manifest (size and SHA-256 of model.safetensors), and it rewrites weights into the parameterisation ComfyUI's Stable-Audio-derived decoder expects at load time. So the second run is instant and fully offline. Flip download_missing off for a strictly offline load - it will then fail loudly with the path it expected rather than reaching for the network. If you keep models on another drive, register that root as yue2 in extra_model_paths.yaml; existing installs are searched before anything downloads.

Install

Manager: search ComfyUI-FL-YuE2 and install. Manually:

cd ComfyUI/custom_nodes
git clone https://github.com/filliptm/ComfyUI-FL-YuE2.git
cd ComfyUI-FL-YuE2
python -m pip install -r requirements.txt

That requirements file is tiktoken, safetensors and filelock - nothing exotic, no Torch downgrade, no upstream YuE repo. Restart ComfyUI afterwards. What you do need is a current ComfyUI: the attention path calls comfy_kitchen.rms_rope_split_half, the fused RMS-norm/RoPE op. On an older build you'll get an import error at startup and no nodes, which is the "node missing" case in the README. Update ComfyUI first, then restart and read the startup console if anything named FL YuE2 is absent.

Also install the models on a case-sensitive filesystem - the file list includes licenses/ and LICENSE/MODEL_LICENSE, and the resolver checks for them.

Traps worth knowing before you queue

It's NVIDIA BF16 or nothing. The loader checks device.type == "cuda" and torch.cuda.is_bf16_supported() and raises otherwise. No MPS, no CPU, no AMD. That's not gatekeeping for its own sake - the whole runtime is BF16 kernels.

24 GB is unvalidated. The author validated on an RTX PRO 6000 Blackwell with roughly 96 GB, and post-generation retained Torch allocation was about 7 GiB. That's not a peak-VRAM number, and it's the one place I'd expect to see reports of trouble: this pack leans on ComfyUI's model management and doesn't change CUDA memory limits, so if you're on a 3090 you'll want a short max_duration on the Render node and a small tile_frames on Decode before you conclude anything is broken.

The weights are CC BY-NC 4.0. The source code is Apache 2.0, the model is non-commercial. If this is heading into anything you sell, stop here and read MODEL_LICENSE.

And if a load dies mid-download, don't nuke the folder - the partial transfers are kept, so just queue again. Only the specific file named in the error needs deleting.

Where this sits against the competition: ACE-Step is still the local music model I'd hand a beginner, because it runs in under 4 GB and is fast. YuE2's pitch is different - it writes an actual symbolic score you can edit, and its decoder output is clean 48 kHz stereo. This loader is the toll booth on that road.