Welcome to Local AI
Running a Large Language Model on your own hardware is easier than ever. This guide will walk you through the essentials.
Hardware Requirements
Minimum Requirements
| Component | Minimum | Recommended |
|---|---|---|
| RAM | 8GB | 16GB+ |
| GPU | Integrated | NVIDIA RTX 3060+ |
| VRAM | 4GB | 8GB+ |
| Storage | 10GB free | 50GB+ SSD |
GPU Considerations
- NVIDIA: Best support with CUDA. RTX 3060 (12GB) is the sweet spot for beginners.
- AMD: Growing support via ROCm. RX 6800+ recommended.
- Apple Silicon: M1/M2/M3 chips work well with optimized builds.
- CPU-only: Possible but slower. Requires 16GB+ RAM for decent models.
Popular Tools
Ollama
The easiest way to get started. One command installs and runs models.
# Install (Linux/macOS)
curl -fsSL https://ollama.com/install.sh | sh
# Run a model
ollama run llama3.2
LM Studio
GUI-based tool for Windows, macOS, and Linux. Great for beginners who prefer visual interfaces.
- Download models from integrated Hugging Face browser
- Chat interface built-in
- Local server mode for API access
Text Generation WebUI
Advanced option with maximum flexibility. Supports:
- Multiple backend engines
- Model training/fine-tuning
- Extensive plugin ecosystem
Your First Model
Step 1: Choose a Model
For beginners, we recommend:
| Model | Size | Use Case |
|---|---|---|
| Llama 3.2 3B | 3GB | Quick responses, low resources |
| Mistral 7B | 4GB | General purpose, balanced |
| Phi-3 Mini | 2GB | Very lightweight, surprisingly capable |
Step 2: Download and Run
Using Ollama:
ollama pull mistral
ollama run mistral
Step 3: Start Chatting
That’s it! You’re now running a local LLM. Try asking questions, generating text, or coding assistance.
Next Steps
- Explore Resources for model recommendations and community links
- Check our blog for hardware guides and model reviews
- Join community discussions to share experiences
Need Help?
Common issues and solutions will be covered in upcoming posts. For now, check the documentation of your chosen tool (Ollama, LM Studio, etc.) for troubleshooting.