LIVE
Anthropic files IPO prospectus, with risk disclosures taking center stage26/10/26 · Anthropic|Robot policy trained only in simulation matches top real-world systems26/10/26|OpenAI unveils GPT-6.1 Terra, a model built for computer use26/10/26 · OpenAI|OpenAI models are coming to Google Cloud21/10/26 · OpenAI|OpenAI details ChatGPT's new advertising infrastructure21/10/26 · OpenAI|Liquid AI unveils LFM3, a base for specialized multimodal models27/10/26 · Liquid AI|US Police Departments Use AI to Flag 'Suspicious' Driving Behavior27/10/26|AllenAI questions whether LLMs can judge research novelty27/10/26 · AllenAI|Open-Source AI Tools Aim to Speed Up Dementia Research27/10/26 · NVIDIA|Solid-state transformers eyed as a fix for AI's power grid bottleneck27/10/26|OpenAI expands Oracle partnership to bring business apps into ChatGPT27/10/26 · OpenAI|OpenAI publishes a page announcing 'GPT-6.1 Terra', with no technical details available26/10/26 · OpenAI|Anthropic files IPO prospectus, with risk disclosures taking center stage26/10/26 · Anthropic|Robot policy trained only in simulation matches top real-world systems26/10/26|OpenAI unveils GPT-6.1 Terra, a model built for computer use26/10/26 · OpenAI|OpenAI models are coming to Google Cloud21/10/26 · OpenAI|OpenAI details ChatGPT's new advertising infrastructure21/10/26 · OpenAI|Liquid AI unveils LFM3, a base for specialized multimodal models27/10/26 · Liquid AI|US Police Departments Use AI to Flag 'Suspicious' Driving Behavior27/10/26|AllenAI questions whether LLMs can judge research novelty27/10/26 · AllenAI|Open-Source AI Tools Aim to Speed Up Dementia Research27/10/26 · NVIDIA|Solid-state transformers eyed as a fix for AI's power grid bottleneck27/10/26|OpenAI expands Oracle partnership to bring business apps into ChatGPT27/10/26 · OpenAI|OpenAI publishes a page announcing 'GPT-6.1 Terra', with no technical details available26/10/26 · OpenAI|
AppRisingofficial publisher

ACE-Step 1.5

App : A product you use directly

Full music generation (vocals, structure, style) running locally, open source.

The best local music generator in 2026: a full song in a few seconds on a consumer GPU.

Overall score
8.3 /10
Security: nothing to flag
Utility
9.0
Reliability
10.0
Security
No caveat on record
Ease
Technical · Technical

Security reflects where data goes, requested permissions and incidents on record at the verification date. It is not a guarantee of zero risk: check the deployment mode and the connections you enable.

What it does, concretely

Creating complete music with vocals, instruments and coherent structure usually requires expensive professional software or online services that retain your data. ACE-Step 1.5 addresses this by offering an open-source music generator that runs entirely on your own machine.

The model combines a diffusion transformer with a language model that acts as a planner: it turns a simple text description into a complete song with lyrics, metadata and musical structure. Generation takes under 10 seconds on an RTX 3090 GPU and under 2 seconds on a professional A100. The model runs with as little as 4 GB of VRAM.

ACE-Step 1.5 is aimed at musicians, producers and content creators who want to generate original tracks, create accompaniments for an existing vocal recording, edit a specific section of a song, or train a personalised style from their own songs using LoRA.

However, the tool is not suited to users without a dedicated graphics card (a CPU mode exists but is significantly slower), nor to those looking for a ready-to-use interface without any installation. Quality can vary by genre, with some styles such as Chinese rap being less well handled, and results remain sensitive to the choice of random seed.

What it offers

  • ·Full song generation from a text description, with lyrics, structure and style, in under 10 seconds on a consumer GPU.
  • ·Support for over 50 languages for lyrics, with fine-grained control over BPM, key, time signature and duration (from 10 seconds to 10 minutes).
  • ·Vocal-to-accompaniment conversion (Vocal2BGM): the model automatically generates an instrumental track suited to an existing vocal recording.
  • ·Local repaint editing: only a specific section of a track can be regenerated without altering the rest.
  • ·One-click personalised LoRA training from around 8 songs, taking about one hour on an RTX 3090 with 12 GB of VRAM, to capture a particular musical style.
  • ·Audio stem separation and multi-track generation to add instrumental layers.
  • ·XL variant (4 billion parameters) available for higher audio quality, requiring at least 12 GB of VRAM.

In practice

Price
Free
Commercial use
Commercial use: unclear
Available on
windows, linux, macos
Licence
voir dépôt
Runs locally
Yes, 4 GB VRAM recommended
FR interface
No

Security and data

Rating
Security: nothing to flag
Your data
Data stays local
Known incidents
Licence des poids à vérifier pour un usage commercial.
Maintenance
Active
Last release
18 May 2026

Links and repository checked on 25 October 2026 · added on 1 May 2025

How to install ACE-Step 1.5

1. Install Python 3.11 or 3.12 and make sure you have a compatible GPU (CUDA, MPS on Apple Silicon, or ROCm on AMD). 2. Install the uv package manager: on macOS/Linux, run curl -LsSf https://astral.sh/uv/install.sh | sh; on Windows, use the PowerShell command shown in the documentation. 3. Clone the repository: git clone https://github.com/ACE-Step/ACE-Step-1.5.git then enter the folder with cd ACE-Step-1.5. 4. Install dependencies: uv sync. 5. Launch the Gradio interface: uv run acestep then open http://localhost:7860 in your browser. Models download automatically on first run. 6. On Windows or macOS, you can use the portable package available on the official site to avoid any manual installation. All processing stays local: no data is sent externally.
git clone https://github.com/ACE-Step/ACE-Step-1.5.git && cd ACE-Step-1.5 && uv sync && uv run acestep

In the same category

Whole category Audio, voice & music →