Optimizing Local LLM Inference for 8GB VRAM GPUs

Developers can run powerful Large Language Models on consumer GPUs with just 8GB of VRAM, despite the belief that expensive 24GB+ hardware is required. Using optimization techniques like 4-bit quantization, layer offloading, and tools such as llama.cpp and Ollama, models like Mistral 7B run smoothly on RTX 3060 or similar cards. These local setups provide complete data privacy, zero ongoing API costs, and full customization control for AI coding assistants and chatbots.