Bark
Text-prompted generative audio model that produces speech, music, and sound effects from natural language
★ 39,182 GitHub
MIT text-to-speechaudio-generationmusic-generationsound-effectsmultilingualsuno Image & Video
Overview
Bark is a transformer-based text-prompted generative audio model developed by Suno AI. With nearly 40,000 GitHub stars, it can generate highly realistic and multilingual speech, music, background noises, and sound effects from simple text prompts. Unlike traditional TTS systems, Bark understands context and can produce non-verbal sounds like laughs, sighs, and throat clears. It supports 13+ languages and can generate music with vocals, making it one of the most versatile open-source audio generation models available. Bark runs on consumer GPUs with as little as 4GB VRAM and offers both Python API and Docker deployment options.
Requirements
Min vCPU
2
Min RAM
4096 MB
Min Disk
10 GB
Rec vCPU
4
Rec RAM
8192 MB
Rec Disk
20 GB
Recommended VPS
Hostinger · KVM 4
4 vCPU · 16384 MB · 200 GB
Hostinger · KVM 4
4 vCPU · 16384 MB · 200 GB
Hostinger · KVM 8
8 vCPU · 32256 MB · 400 GB
Affiliate disclosure
Docker Compose
# Generated by Run This Ai — docker-compose.yml
services:
bark:
image: barksim/bark:latest
restart: unless-stopped
ports:
- 8080:8080
volumes:
- ./data/bark:/data
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