Desktop App
The LlamaFarm Desktop App provides a complete local AI environment with visual project management, dataset uploads, chat interface, and built-in model management — no command line required.
Downloads
Hardware Requirements
Minimum Requirements
To run the desktop app with small models (1-3B parameters like Qwen 1.7B):
| Component | Mac (M1+) | Windows | Linux |
|---|---|---|---|
| CPU | Apple M1 or newer | Intel i5 / AMD Ryzen 5 (8th gen+) | Intel i5 / AMD Ryzen 5 (8th gen+) |
| RAM | 8 GB | 8 GB | 8 GB |
| Storage | 10 GB free | 10 GB free | 10 GB free |
| OS | macOS 12+ (Monterey) | Windows 10/11 (64-bit) | Ubuntu 22.04+ (tested) |
| GPU | Integrated (Metal) | Optional | Optional |
Recommended Requirements
For larger models (7-8B parameters) and better performance:
| Component | Mac (M1+) | Windows | Linux |
|---|---|---|---|
| CPU | Apple M1 Pro/Max or M2+ | Intel i7 / AMD Ryzen 7 | Intel i7 / AMD Ryzen 7 |
| RAM | 16 GB+ | 16 GB+ | 16 GB+ |
| Storage | 50 GB+ SSD | 50 GB+ SSD | 50 GB+ SSD |
| OS | macOS 13+ (Ventura) | Windows 11 | Ubuntu 22.04+ |
| GPU | Unified Memory (Metal) | NVIDIA RTX 3060+ (8GB+ VRAM) | NVIDIA RTX 3060+ (8GB+ VRAM) |
Model Memory Requirements
The default model is Qwen 1.7B GGUF (Q4_K_M quantization), which works well on modest hardware.
| Model | Parameters | RAM Required | VRAM (GPU) | Notes |
|---|---|---|---|---|
| Qwen 1.7B (default) | 1.7B | 4 GB | 2 GB | Great for testing, fast responses |
| Qwen 3B | 3B | 6 GB | 4 GB | Better quality, still fast |
| Llama 3.1 8B | 8B | 10 GB | 6 GB | High quality, needs more resources |
| Qwen 8B | 8B | 10 GB | 6 GB | High quality reasoning |
GGUF models use quantization (Q4_K_M, Q5_K_M, Q8_0) to reduce memory usage. Q4_K_M offers the best balance of quality and speed for most users.
Platform-Specific Notes
Mac (Apple Silicon)
- Tested on: M1, M1 Pro, M1 Max, M2, M3
- Acceleration: Uses Metal for GPU acceleration automatically
- Memory: Unified memory is shared between CPU and GPU — 16GB+ recommended for 8B models
- Installation: Unzip and drag to Applications folder
Windows
- Tested on: Windows 10 (21H2+), Windows 11
- Acceleration: NVIDIA CUDA (if available), otherwise CPU
- GPU Support: NVIDIA GPUs with CUDA 11.8+ drivers
- Installation: Run the
.exeinstaller
Windows Defender may scan the app on first launch. This is normal and should complete within a minute.
Linux
- Tested on: Ubuntu 22.04 LTS, Ubuntu 24.04 LTS
- Format: AppImage (portable, no installation needed)
- Acceleration: NVIDIA CUDA or Vulkan (if available)
- Dependencies: FUSE required for AppImage
# Make executable and run
chmod +x LlamaFarm-0.0.19.AppImage
./LlamaFarm-0.0.19.AppImage
# If FUSE is not installed:
sudo apt install fuse libfuse2
While Ubuntu is our primary test platform, the AppImage should work on most modern Linux distributions with glibc 2.31+. Community reports for Fedora, Arch, and Debian are welcome!
Features
The desktop app includes:
- Visual Project Management — Create, configure, and switch between projects
- Dataset Uploads — Drag-and-drop file uploads with real-time processing status
- Chat Interface — Test your AI with full RAG context
- Model Management — Download, switch, and configure models
- Built-in Services — No need to run Docker or manage background processes
Troubleshooting
App won't start
- Windows: Allow through Windows Defender/Firewall
- Linux: Ensure FUSE is installed, check AppImage is executable
Out of memory
- Close other applications
- Use a smaller model (Qwen 1.7B instead of 8B)
- Use higher quantization (Q4_K_M instead of Q8_0)
Model download fails
- Check internet connection
- Ensure sufficient disk space
- Try downloading again — downloads resume automatically
Need help?
Next Steps
- Quickstart Guide — Get started with your first project
- Configuration Guide — Customize your setup
- CLI Reference — For power users who want command-line access