AudioGen
Open-source text-to-sound generation for local research workflows
At a glance
- Editor scoreNot yet scored
- PricingFree plan
- Best forResearchers building custom local audio workflows
- Free planYes
- Paid fromNone
- Text-to-soundYes
- Facts checked20 Sep 2026
Where it wins
- Generates environmental audio from natural-language descriptions
- Includes Python inference, continuation, and configurable sampling
- Provides training and evaluation pipelines for custom research workflows
Where it doesn't
- Requires self-hosting through a local research library
- Commercial use is restricted by the CC-BY-NC 4.0 license
- Research-oriented tooling may be less convenient for typical creators
Our verdict on AudioGen
AudioGen is an open-source text-to-sound generation model from Meta AI’s FAIR team. It is designed for audio, machine-learning and AI researchers, along with amateurs exploring generative audio. The model generates general environmental audio from natural-language descriptions using an autoregressive Transformer and 16 kHz EnCodec-based audio tokenization. Its released medium model has 1.5 billion parameters and runs locally through the AudioCraft Python library, making it a fit for custom workflows rather than a hosted commercial sound-effects application.
For research and development, AudioGen provides more than prompt-based generation. The feature set includes audio continuation from an audio prompt, configurable generation duration and sampling parameters, and a Python inference API through AudioCraft. Training and evaluation pipelines support custom research workflows, while the model’s open-source distribution allows local work with the released system. These capabilities make AudioGen particularly relevant when researchers need to inspect, adapt or integrate generation into their own Python-based processes.
The main trade-off is the product’s local, research-focused delivery model. AudioGen is distributed as a model and local research library rather than a hosted commercial application, so it is less convenient for creators seeking a ready-to-use browser workflow. The model weights use the CC-BY-NC 4.0 license, restricting commercial use. Researchers building custom local audio systems should consider AudioGen; creators needing straightforward commercial production workflows or a hosted experience should choose a tool aligned with those requirements instead.
AudioGen pricing
AudioGen fact sheet
| Free plan | Yes |
|---|---|
| Paid from | None |
| Text-to-sound | Yes |
| Reference input | Yes |
| Maximum clip length | Not verified |
| Download formats | Wav |
| Commercial use | Restricted |
| API access | Yes |
| Deployment | Self-hosted |
| Support | Community, Docs |
| Built for | Solo, Small business (editorial estimate) |
| Pricing | Free plan |
| Website | github.com |
| Facts checked | 20 Sep 2026 |
Alternatives to AudioGen
- SoniloA flexible SFX generator with video timing, API access, and a useful free tier.7.7
- MireloA deep AI sound-effects toolkit for professional editors and production teams.7.7
- Noiz AIA controllable AI sound-effects generator for reactive game audio and production workflows.—
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Reviewed by iTechGuides Editors · Editorial team · Updated Sep 2026
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