AudioCraft
Open Source
Open-source audio generation
For AI researchers
High-quality audio
Text-to-music
Generate high-quality audio and music from text with Meta's open-source AI.
Last updated: Apr 15, 2026
OPEN_SOURCE
ai.meta.com
Quick Answer
AudioCraft is an open-source library by Meta for generating high-quality audio and music using deep learning. It features the EnCodec audio compressor and MusicGen for music generation with text and melodic conditioning. Best for researchers and developers building AI audio solutions. It is open-source and free to use.
About AudioCraft
AudioCraft is an open-source library by Meta for audio processing and generation using deep learning. It includes the EnCodec audio compressor/tokenizer and MusicGen, a language model for music generation with textual and melodic conditioning. This tool allows researchers and developers to create high-quality audio and music from text prompts, facilitating advancements in AI audio solutions.
What Makes It Unique
AudioCraft features the state-of-the-art EnCodec audio compressor/tokenizer and MusicGen, a controllable music generation language model with both textual and melodic conditioning capabilities.
Use Cases & Target Users
Best For
Generating music from text descriptions
Creating audio for creative projects
Researching audio generation models
Developing AI-powered audio applications
Company Size
SOLO
SMALL
MEDIUM
ENTERPRISE
Fit Score
Complexity
ADVANCED
Target Team Size
INDIVIDUAL
SMALL_TEAM
LARGE_TEAM
Target Skill Level
EXPERT
Key Features
EnCodec audio compressor
EnCodec audio tokenizer
MusicGen music generation
Textual conditioning for music generation
Melodic conditioning for music generation
Deep learning-based audio processing
Technical Specifications
API Available
SDK Available
MCP Compatible
Open Source
MIT
Team Features
SSO/Enterprise
Webhook Support
Has Demo
Deployment:
SELF_HOSTED
Pros
- +Open-source and freely available for research and development
- +Includes state-of-the-art audio compression with EnCodec
- +Offers controllable music generation with text and melody inputs
- +Backed by Meta AI's extensive research capabilities
Limitations
- -Requires technical expertise in deep learning and programming to use
- -Not a user-friendly graphical interface for non-developers
- -Primarily designed for research and development, not end-user content creation
- -May require significant computational resources for model training and inference
Powered By
Base Models
MusicGenEnCodec
Uses Models
MusicGenEnCodec
Decision Intelligence
Best For
Generating music from text descriptions
Creating audio for creative projects
Researching audio generation models
Developing AI-powered audio applications
Not Ideal For
Non-technical users seeking a simple, plug-and-play audio generation application
Users needing a cloud-hosted, managed service for audio generation
Creating complex multi-track audio productions without coding knowledge
Users without access to computational resources for deep learning models
Frequently Asked Questions
Your Actions
Dimension Scores
Ease of Use2/10
Output Quality8/10
Value for Money9/10
Customization7/10
Support6/10
Integration1/10
Task Scores
Format Support
6
Voice Naturalness
1
Language Coverage
1
Speaker Cloning
1
Transcription Accuracy
1
Real Time Processing
1
Emotion Control
1
Noise Handling
1
Trust Score
35/100
Limited Data
Based on 4 verified signals
Trust Signals
Verified CompanyMeta
FundingPublic (NASDAQ: META)
Team Size5000+
Data Residency
Switching & Migration
Migration Difficulty
Easy to Switch
Data portable as:
WAV
Community Forum + Docs
Quick Stats