Generate Music with AI Locally Using ACE-Step: One-Click Text-to-Music Model

Author(s): Md Monsur ali

Originally published on Towards AI.

Create full-length AI-generated songs from text prompts, tags, and lyrics using the ACE-Step v1–3.5B open-source model — no cloud, no API, just your GPU.

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Imagine describing a song with words like “a mellow jazz tune with saxophone and piano,” clicking a button, and having a complete, studio-quality track generated on your computer without sending a single byte to the cloud. That’s the promise of ACE-Step v1–3.5B, an open-source music generation model that ACE Studio and StepFun developed.

ACE-Step brings powerful text-to-music generation completely offline in an era of growing concerns over data privacy and dependency on cloud services, making it one of the most creator-friendly tools in the AI music space.

ACE-Step v1–3.5B is a deep learning model designed to generate full-length music tracks from natural language prompts. Built on a diffusion-based framework, the model combines a Deep Compression AutoEncoder (DCAE) with a lightweight linear transformer. This combination allows it to produce rich, multi-instrument compositions that are musically coherent and stylistically diverse.

Where other models may struggle to maintain structure across several minutes of audio, ACE-Step is optimized for long-form music generation. It doesn’t just create loops or short motifs — it can generate 4-minute tracks with a sense of progression, genre fidelity, and emotional flow.

Most AI music generators either create random compositions or… Read the full blog for free on Medium.

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Published via Towards AI