yue2-mothersuperior-realaudio-tokenizer-v4: 12GB+ VRAM, File List

- 1. At a Glance
- 2. Overview
- 3. Specifications
- 4. Performance and Quality
- 5. Strengths and Use Cases
- 6. Differences from Similar Models
- 7. Hardware Requirements
- 8. Can You Run It Locally?
- 9. Our Own Measurements
- 10. Distributed Files
- 11. How to Get It
- 12. Related Articles
- 13. What to Read Next
- 14. Sources
- 15. Update History
At a Glance
| Item | Value |
|---|---|
| Repository | Mothersuperior/yue2-mothersuperior-realaudio-tokenizer-v4 |
| Family guide | YuE2 guide (3 articles) |
| Publisher guide | M-A-P: models and licenses |
| Published | 2026-09-14 |
| License | cc-by-nc-4.0 |
| Formats | safetensors |
| Source type | Primary source (the publisher itself) |
Values determined by this site’s code when the information was collected. Dates are JST.
Overview
Mothersuperior has released a real audio toolkit for the open music generation model “YuE2-3B", titled Mothersuperior/yue2-mothersuperior-realaudio-tokenizer-v4. It is a real audio tokenizer that accepts audio or music as input, encodes them into semantic tokens, and renders actual production-level latent representations through NAR branch LoRAs. This enables tokenizing one’s own recordings, fine-tuning artist LoRAs, and generating new songs or covers.
Specifications
- Base model: m-a-p/YuE2-3B
- License: cc-by-nc-4.0 (Non-commercial use only)
- Included files:
tokenizer_head_joint_v4.pt: An 8-layer transformer (d=512, 512-frame window) that converts features from MERT-v2-FullSong layer 20 into 32,768 YuE2 semantic codes. Achieves 16.1% top-1 accuracy on YuE2’s own held data for songs –nar_lora_joint_v4.pt: Rank-32 LoRAs for 28 layers ofnar_self_attn.{q,k,v,o}_projandnar_mlp.{gate,up,down}_proj, as well asvae2llm/llm2vae
Performance and Quality
The model card of the original model publishes evaluation results on WildSongBench and SHS100K. Below are the evaluation results for full song generation on WildSongBench.
→ Scroll horizontally to see all columns
| Model | Musicality ↑ | SongBench Avg ↑ | MuLan ↑ | AllMusicCaps ↑ | Q3O ↑ | PER ↓ |
|---|---|---|---|---|---|---|
| YuE 1 | 4.0847 | 4.9165 | 0.2623 | 0.2882 | 3.7301 | 36.38% |
| SongBloom | 3.4493 | 4.2350 | 0.2697 | 0.1926 | 3.0287 | 19.19% |
| LeVo 2 | 5.4590 | 6.3247 | 0.3542 | 0.2680 | 3.9458 | 26.12% |
| ACE-Step 1.5 | 5.1588 | 6.0118 | 0.4372 | 0.3869 | 4.5809 | 7.46% |
| HeartMuLa | 5.4963 | 6.2483 | 0.3823 | 0.2786 | 3.4907 | 10.71% |
| DiffRhythm 2 | 4.4775 | 5.2428 | 0.3782 | 0.3255 | 4.0870 | 18.41% |
| Muse | 5.1692 | 6.0349 | 0.3937 | 0.3466 | 4.4038 | 33.42% |
| MiniMax Music 3 | 5.3482 | 6.2830 | 0.3928 | 0.3609 | 4.4362 | 6.27% |
| YuE2 | 5.9075 | 6.7316 | 0.5068 | 0.4054 | 4.6819 | 8.44% |
| YuE2 (best-of-8) | 6.2666 | 6.9632 | 0.5051 | 0.3980 | 4.7009 | 9.79% |
While the original YuE2 model records excellent scores in many metrics such as Musicality, SongBench Avg, MuLan, and AllMusicCaps, it falls short of other models in certain items like PER (Phoneme Error Rate). These are figures published directly by the authors.
Strengths and Use Cases
It is suited for tokenizing one’s own recorded audio, fine-tuning AR via LoRA using tracks from specific artists, and generating new songs or cover tracks. After being trained on 4,765 YuE2 self-generated songs, it has been adapted to real audio, and combining it with an additional regularization pack (Mothersuperior/yue2-minted-corpus) can prevent token grammar collapse with small artist sets. It is also possible to transcribe existing recordings with tools like SheetSage2 to obtain melodies and generate cover songs.
Differences from Similar Models
Unlike the original base models Music Generation Model “YuE2-3B" Released, Create Songs from Lyrics and Style and Repackaged Version of Music Generation Model “YuE2-3B" for ComfyUI Released, this model adds a real audio tokenizer and NAR branch LoRAs that are not officially bundled, making a specific difference by enabling direct tokenization using one’s own audio and artist-specific LoRA training.
Hardware Requirements
Estimated requirements (calculated by Local Model Watch) — 3.6B parameters (taken from the base model m-a-p/YuE2-3B)
| Your VRAM | Quantization | File size | Est. memory needed |
|---|---|---|---|
| 12GB (RTX 4070 / 3060 12GB, etc.) | BF16 | 6.8GB | 8.1GB |
Memory estimates add a 20% runtime overhead (KV cache, etc.) to the actual size of the distributed files. Actual usage varies with context length, batch size and inference engine. These figures are computed by this site from file sizes, not published by the model’s authors. This release is an adapter (LoRA etc.); the table shows what the base model m-a-p/YuE2-3B needs. Compare with other models in our VRAM quick reference. What the quantization names mean: glossary.
Can You Run It Locally?
The publisher distributes this model as safetensors.
License — cc-by-nc-4.0 (Commercial use prohibited):
Commercial use is prohibited (NC = NonCommercial). Internal business use can also count as commercial, so avoid this license for work use.
Compiled by this site’s code from the published formats and the license field. License summaries are not legal advice — check the publisher’s original terms before relying on them.
Our Own Measurements
Measurements We Did Not Take
This model’s license (cc-by-nc-4.0) does not permit commercial use. Because this site carries advertising, we did not run the model (no CPU run, answers, quantization comparison, conversion or generation).
Distributed Files
Weight files published in Mothersuperior/yue2-mothersuperior-realaudio-tokenizer-v4, listed by this site from the Hugging Face API. Sizes are the actual file sizes.
| File | Size |
|---|---|
nar_lora_joint_v4.bf16.safetensors |
70MB |
nar_lora_joint_v4.pt |
141MB |
nar_lora_joint_v4.safetensors |
141MB |
nar_lora_joint_v4_comfyui.safetensors |
108MB |
nar_lora_joint_v5.bf16.safetensors |
70MB |
nar_lora_joint_v5.safetensors |
141MB |
nar_lora_joint_v5_comfyui.safetensors |
108MB |
nar_lora_joint_v8.bf16.safetensors |
70MB |
nar_lora_joint_v8.safetensors |
141MB |
nar_lora_joint_v8_comfyui.safetensors |
108MB |
nar_lora_joint_v9.bf16.safetensors |
70MB |
nar_lora_joint_v9.safetensors |
141MB |
nar_lora_joint_v9_comfyui.safetensors |
108MB |
tokenizer_head_joint_v4.bf16.safetensors |
86MB |
tokenizer_head_joint_v4.pt |
171MB |
tokenizer_head_joint_v4.safetensors |
171MB |
tokenizer_head_joint_v5.bf16.safetensors |
86MB |
tokenizer_head_joint_v5.safetensors |
171MB |
tokenizer_head_joint_v8.bf16.safetensors |
86MB |
tokenizer_head_joint_v8.safetensors |
171MB |
4 more file(s) are listed on Hugging Face.
How to Get It
- Repository:
Mothersuperior/yue2-mothersuperior-realaudio-tokenizer-v4(Hugging Face) - Required additional data: Needs the regularization pack (
regularizer/minted_regularizer_pack.pt) fromMothersuperior/yue2-minted-corpus - Dependencies: Python 3.12 venv,
yue2-infer(commit 92a73cc7), torch 2.10 + cu128, torchaudio 2.10, transformers, soundfile, scipy, safetensors, demucs
Related Articles
What to Read Next
- Explore the same model family → YuE2 family overview (3 articles)
- Formats this model is available in → Safetensors format guide and models
- Learn about the publisher → M-A-P: models, licenses and articles
Sources
- https://huggingface.co/Mothersuperior/yue2-mothersuperior-realaudio-tokenizer-v4
- https://huggingface.co/m-a-p/YuE2-3B
Update History
- 2026-09-24: Rebuilt the article: Added a “can you run it locally?" verdict from the distribution formats, converted builds, engine registries, license terms and measured compression
- 2026-09-25: Changed the title to show what the article covers (VRAM requirements, file list, etc.).

