ACE-Step 1.5: MIT-licensed song generator that runs on consumer GPUs
Partly confirmed
Status
- Claim
Partly confirmed
- Our reporting
- Medium confidence
- Importance
- 3 of 5
- Last verified
- 29 September 2026
Your AI and this story
- GPT-6 AstraIn its training data
- Claude Opus 5.5In its training data
- Gemini 4 HydrogenIn its training data
- Grok 4.7In its training data
It happened before the cutoffs of all four assistants, so it can be in their training data.
Key facts
- Songs from 10 s to 10 min; under 2 s per song on an A100, under 10 s on an RTX 3090
- Runs in under 4 GB VRAM with offload (XL needs >=12 GB)
- LoRA personalization from about 8 songs in ~1 hour on a 12 GB GPU
- License: MIT; weights on Hugging Face (ACE-Step/Ace-Step1.5)
- ACE-Step 1.5 XL (4B DiT; base/sft/turbo) released 2026-04-02
What happened
The successor to 2025’s ACE-Step v1 (3.5B) splits generation into a language-model “planner” that writes a full song blueprint and a Diffusion Transformer that renders audio, aligned with reinforcement learning that needs no external reward model. It ships with cover generation, repainting, vocal-to-backing-track conversion, stem separation and LoRA training, and supports Mac, AMD, Intel and CUDA.
The exact launch day (2026-01-28) comes from secondary coverage; Hugging Face repos were created on 2026-01-23 and the tech report was submitted on 2026-01-31.
Why it matters
It made near-commercial song generation practical on laptops and gaming GPUs under a permissive license, the open alternative to Suno/Udio in the year the commercial services moved to licensed data. The authors claim quality above most commercial models (not independently verified).
Sources
4 sources from 4 sites. Numbers match the chips in the text.
4 sources: 4 primary
Primary
- GitHub: ace-step/ACE-Step-1.5github.com, code
- Tech report: ACE-Step 1.5 (arXiv 2602.00744)arxiv.org, paper
- Hugging Face: ACE-Step/Ace-Step1.5huggingface.co, code
- Project pageace-step.github.io, official
Changes
- Filed