DeepSeek V3 Complete Guide: Deploy and Optimize Local AI

DeepSeek V3, a 671-billion parameter AI model using Mixture-of-Experts architecture that activates only 37 billion parameters per inference, can be deployed locally to avoid cloud costs and meet data residency requirements. Deployment involves installing Ollama, pulling the quantized model (requiring 32GB RAM, 12GB+ VRAM, and 400GB storage), then building a Node.js API backend and React frontend for real-time chat. Performance optimization focuses on selecting appropriate quantization levels like Q4_K_M, tuning GPU layer offloading to maximize VRAM usage, and implementing context-aware conversation trimming.