m-a-p/YuE2-3B — new model trending #30 on Hugging Face
M-A-P released YuE2-3B, an open music generation model that outperforms Suno v5 on WildSongBench and runs locally on a 24GB GPU.
The M-A-P (multimodal-art-projection) team released YuE2-3B, an open-weights music generation model that turns lyrics and a style prompt into full songs with vocals and accompaniment. It uses an AR-NAR Mixture-of-Transformers backbone with symbolic planning and flow matching through a VAE, and supports editable scores (melody and chords, including ABC notation) plus agentic editing workflows. On 192 WildSongBench prompts it reports a SongBench average of 6.9632 (best-of-8) versus 6.8721 for Suno v5, claimed as state of the art among evaluated open and proprietary models. It runs 48 kHz stereo inference locally on a single 24GB NVIDIA GPU without quantization, with companion releases including YuE2-Vae, MERT-v2 encoders, the WildSongBench dataset, and SheetSage2.
- Open-weights model generates complete songs with vocals from lyrics and style prompts.
- Editable score workflow supports melody/chord planning in ABC notation and agentic revisions.
- Reports SongBench average 6.9632 on WildSongBench, ahead of Suno v5's 6.8721.
- Runs 48 kHz stereo inference locally on a single 24GB GPU without quantization.
- Companion releases include YuE2-Vae, MERT-v2 encoders, WildSongBench, and SheetSage2.
- Vendors
- Hugging FaceM-A-P
- Organizations
- Multimodal Art Projection (M-A-P)
- AI models
- YuE2-3B
From the original article
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By m-a-p · huggingface.co
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