Explore text- and melody-conditioned music generation with Meta’s AudioCraft research toolkit and MusicGen models.
music generationMusicGenmelodyresearchnoncommercial weights
Source-reviewedNot hands-on testedSources checked
Start with an idea
What you can make
01
Sketch instrumental musical ideas for noncommercial experimentation
02
Study how prompts and a permitted reference melody influence generated music
Creator demonstration
See the documented workflow
Official project sample page linked by the repository, including text-conditioned and stereo examples; curated examples are not an independent quality test.
Repository installation instructions specify Python 3.9 and PyTorch 2.1.0
FFmpeg is recommended; check the pinned dependency stack before choosing an environment
Download model checkpoints; allow GPU memory and runtime for the chosen model and clip duration
Runs through / on
Python / PyTorch · GPU workstation · Local Gradio interface · Official browser demo
The real tradeoffs
Cost & licensing
Running costs
No software fee for local use within license terms; GPU compute is your cost.
The official MusicGen guide calls for a GPU and at least 16 GB of memory for medium models. Smaller models or shorter clips may fit smaller GPUs; rented hardware and hosted demo availability are separate.
Code and supplied model weights have different licenses. The noncommercial weights restriction means this is not an unrestricted commercial-generation option.
Know the limitations
MusicGen does not generate realistic vocals
English prompts are best supported; styles and cultures are represented unevenly
Outputs can collapse to silence, and prompt experimentation may be necessary
A research toolkit with noncommercial model weights needs additional review before downstream deployment
Follow the evidence
Sources & verification
Official sources were reviewed on October 14, 2026. We did not install, run or benchmark this project. This is a source-check date, not a release date.