A comprehensive guide to running AI models entirely locally on your own hardware, covering model selection based on VRAM and parameters, quantization levels, and mixture-of-experts (MoE) models. Shows how to set up LM Studio as a local inference server, then connect it to VS Code via the Continue extension for autocomplete and agentic coding, GitHub Copilot's local model support, and the Pi CLI tool for terminal-based agent workflows. Includes practical benchmarks comparing GPU-only vs. RAM-overflow performance, and a real-world vibe-coding demo generating a Sudoku app locally.
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