Get Sulla Desktop
Available for Windows, macOS, and Linux. Free, open source, and ready to supercharge your productivity.
Windows
Windows 10 or later (64-bit)
Installation Instructions
1. Download the installer above
2. Run SullaDesktop-Setup.exe
3. Follow the installation wizard
4. Launch Sulla from Start Menu
macOS
macOS 11 Big Sur or later
Installation Instructions
1. Download the .dmg file above
2. Open SullaDesktop.dmg
3. Drag Sulla to Applications folder
4. Launch from Applications or Launchpad
First launch: Right-click and select "Open" to bypass Gatekeeper
Linux
Ubuntu 20.04+ / Fedora 34+ / Debian 11+
Installation Instructions
AppImage (Recommended):
./Sulla-Desktop.AppImage
Debian/Ubuntu (.deb):
sudo apt-get install -f
Fedora/RHEL (.rpm):
Alternative Installation Methods
Choose your preferred package manager or build from source
Homebrew
Snap Store
Docker
From Source
npm install && npm run build
System Requirements
Minimum and recommended specifications for optimal performance
Minimum Requirements
Processor
Dual-core 2.0 GHz or equivalent
Memory
4 GB RAM
Storage
2 GB available space
Network
Broadband internet connection
Recommended Specs
Processor
Quad-core 3.0 GHz or Apple M1/M2
Memory
8 GB RAM or more
Storage
5 GB available SSD space
Network
High-speed internet for AI features
Frequently Asked Questions
Is Sulla Desktop really free?
Yes! Sulla Desktop is 100% free and open source. No hidden costs, no premium tiers, no subscriptions. You can even modify and redistribute it under the MIT license.
How do I update Sulla Desktop?
Sulla Desktop includes an auto-updater that checks for new versions on startup. You can also manually check for updates in Settings → About → Check for Updates.
Can I use my own AI API keys?
Absolutely! Sulla Desktop supports custom API keys for OpenAI, Anthropic, Google, and many other providers. You can also run local models with Ollama or LM Studio integration.
Does it work offline?
Yes! While cloud AI features require internet, Sulla Desktop supports local LLMs, offline n8n workflows, and local Docker management. Your data stays on your machine.