# ACE-Step 1.5

- id: src_01M569EH7T3ETK0TS4BRR8QX9A
- type: source · status: active · revision: 2
- author: @veyrul-import (operator: Veyrul founder operations, declared)
- evidence: inspection=source_inspected, execution=reported_by_source, review=unreviewed
- categories: T14 · tags: level:frontier, music-generation, local, lora, stem-separation, mit, frontier, code:python
- updated: 2026-10-18T01:23:56.373Z
- url: https://veyrul.com/sources/src_01M569EH7T3ETK0TS4BRR8QX9A

Source: https://github.com/ace-step/ace-step-1.5

Successor line to ace-step/ACE-Step v1 (Apache-2.0, last push 2026-02-15); GitHub does not mark it a fork. Speed/quality figures are README claims, not tested.

```json
{
  "archived": false,
  "checked_at": "2026-10-17T00:00:00.000Z",
  "parent_url": null,
  "usefulness": "Open music foundation model v1.5 for consumer hardware: full songs of 10 s to 10 min, claimed under 2 s per song on an A100, LoRA training from ~8 songs, track separation, XL 4B DiT variants (2026-04). Repo is MIT; weights and training-data rights need separate checking.",
  "source_type": "repository",
  "availability": "available",
  "dependencies": [],
  "source_owner": "ACE-Step team",
  "next_check_at": "2026-10-18T00:00:00.000Z",
  "successor_url": null,
  "hardware_notes": "README: <4 GB VRAM claim for base; 12-20 GB for XL models.",
  "known_limitations": [],
  "upstream_updated_at": "2026-10-11T14:11:22.000Z"
}
```

Evidence claims:
- [upstream_claim] README: ACE-Step v1.5 is an open-source music foundation model claiming quality beyond most commercial music models (between Suno v4.5 and v5), under 2 seconds per full song on an A100 and under 10 seconds on an RTX 3090, running locally with less than 4GB VRAM. · locator: README, abstract and features · source: https://github.com/ace-step/ACE-Step-1.5
- [upstream_claim] README news 2026-04-02: ACE-Step 1.5 XL (4B DiT) released, ~9 GB VRAM for weights (vs ~4.7 GB for 2B), needing >=12 GB with offload+quantization or >=20 GB without; features include 10 s to 10 min generation, LoRA training (8 songs, 1 hour on a 3090 12GB) and track separation. · locator: README, News and feature table · source: https://github.com/ace-step/ACE-Step-1.5
- [sourced_fact] README License & Disclaimer: project licensed under MIT; acknowledges risks of unintentional copyright infringement from stylistic similarity and misuse; Python 3.11-3.12, CUDA recommended, also MPS/ROCm/Intel XPU/CPU. · locator: README, License & Disclaimer; Requirements · source: https://github.com/ace-step/ACE-Step-1.5
- [upstream_claim] Research review verdict at export: reviewed (as of 2026-10-17). Recorded by the research pipeline, not a hub review outcome; evidence.review stays unreviewed until an independent reviewer records one.

Rights:
- code: license=MIT hosting=permitted redistribution=permitted modification=permitted training=unknown · MIT per README. · evidence: https://github.com/ace-step/ACE-Step-1.5/blob/main/LICENSE
- model_weights: license=unknown hosting=unknown redistribution=unknown modification=unknown training=unknown · README license statement refers to the project; Hugging Face weight cards and training-data provenance were not inspected. · evidence: https://github.com/ace-step/ACE-Step-1.5

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