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A5

ace-step/ACE-Step-1.5

The most powerful local music generation model that outperforms almost all commercial alternatives, supporting Mac, AMD, Intel, and CUDA devices.

12k Stars1.5k Forks153 Open Issues12k WatchersPythonMIT
Automation
Review Readiness

This repository page is useful for visitors, but Git-Stars keeps it out of search indexing until more original evidence and comparison context are available.

70

review score

Needs original analysis
Decision Snapshot

Problem solved

It addresses the need for high-quality, fast, and locally runnable music generation, overcoming the limitations of commercial models that are slow, resource-intensive, or not open-source. It also enables personalized style capture via LoRA training from a few songs.

Deployment reality

The available setup signal starts with: curl -LsSf https://astral.sh/uv/install.sh | sh. Treat this as a starting point, then ask Codex or Claude to inspect the README, environment variables, runtime version, and deployment target before production use.

Commercial use

The recorded license is MIT. This is a useful commercial-use signal, but teams should still verify license text, dependencies, model/API terms, and trademark constraints.

Capability ceiling

ace-step/ACE-Step-1.5 still needs a clearer capability analysis. Use the metadata as a discovery signal, not as a production recommendation.

Source and compliance noteLast synced: Aug 15, 2026

Git-Stars is independent and not affiliated with GitHub or this project. Analysis may be AI-assisted and based on public repository metadata plus short README-derived summaries. We do not mirror full README files, docs, issues, or social comments.

Original GitHub sourceMethodologyEditorial Policy
Editorial Evaluation

ace-step/ACE-Step-1.5 is tracked as a Python project in the Automation area. This evaluation combines public GitHub metadata, category signals, short source summaries, and Git-Stars editorial rules rather than copying project documentation.

Momentum check: the repository has 12k total stars, with +0 today, +160 this week, and +0 this month. These growth windows help distinguish durable adoption from short-lived visibility spikes.

Maintenance check: current activity is Active; the latest push was 28 days ago, and the open issue queue is 153, about 1.25% of total stars. Treat this as an adoption signal, not a substitute for engineering due diligence.

Adoption check: 1.5k forks and 12k watchers suggest how often the project is reused or followed. License signal: MIT. Always verify license compatibility before commercial or internal use.

Practical fit: this project is most relevant when you need Python teams evaluating ecosystem-native tooling. Be cautious when you need a legal review, security audit, or production SLA.

Source check: Git-Stars currently has 2 explicit source reference(s) for this report and a recent growth signal of 160. Follow the original GitHub repository for final install, security, and release information.

Evidence Checklist

Analysis

Limited

Needs stronger original analysis before indexing.

Sources

Ready

Repository metadata and README/source references are attached.

License

Ready

MIT is recorded for review.

Maintenance

Ready

Recent activity is visible in repository metadata.

Alternatives

Ready

Enough nearby projects exist for comparison.

Best For
  • Python teams evaluating ecosystem-native tooling
  • teams that prefer mature projects with broad adoption signals
  • use cases where recent maintenance matters
Avoid When
  • you need a legal review, security audit, or production SLA
Adoption Signals

Momentum

12k Stars

Reuse

1.5k Forks

Attention

12k Watchers

Maintenance

active

License

MIT

Open issues

153

Overview

ACE-Step 1.5 is an open-source music generation foundation model that produces commercial-grade audio on consumer hardware. It uses a hybrid architecture combining a language model planner with a diffusion transformer for fast, high-quality generation, supporting tasks like cover generation, repainting, and vocal-to-BGM conversion.

Key Features

- Ultra-fast generation: under 2 seconds per full song on A100, under 10 seconds on RTX 3090 - Flexible duration: supports 10 seconds to 10 minutes of audio - Versatile editing: cover generation, repainting, track separation, multi-track generation, and vocal-to-BGM conversion

Tool Positioning

Automation

Workflow automation, integration glue, and orchestration

Quick Start
curl -LsSf https://astral.sh/uv/install.sh | sh
View on GitHub Project Homepage
Project Activity

80

Health Score

Active

Commit Activity

Sep 4, 2025

Created

Jul 25, 2026

Last push

Source Trail

GitHub repository metadata

metadata

GitHub README

readme_summary

Star History

+20

Today's growth

+20

7-day growth

+20

30-day growth

Aug 14, 2026Aug 15, 2026
Community Health
1.5k

Forks

153

Open

12k

Watchers

Owner
A5

ace-step

GitHub profile
Topics & Language
Pythontext2music
Ecosystem & Usage
GitHub Repository Project Website
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License
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Last pushJul 25, 2026
Last syncedAug 15, 2026
Repository Standards

✓

License

✓

Forked

✓ Active

Maintained