AI Coding at Home Without Going Broke

Stephen Bochinski's blog describes how to use AI coding assistants locally on home hardware without incurring high cloud costs. He recommends using quantized models (e.g., CodeLlama 7B Q4) that run on 8GB+ GPUs, or on CPU via llama.cpp. He also covers using tools like Continue.dev as a plugin for VS Code, which interfaces with local models. Performance comparisons show that smaller models are adequate for many tasks like autocomplete and refactoring. The post suggests using cloud APIs only for complex reasoning tasks. Total hardware investment can be under $1,000 for a used GPU setup. The guide aims to democratize AI coding.