https://infotechwithben.com/tags/local-ai/Recent content in Local-Ai on Ben's Info Tech BlogHugoenSat, 28 Mar 2026 00:00:00 +0000https://infotechwithben.com/posts/shadow-stack-local-vs-api-cost-analysis/Sat, 28 Mar 2026 00:00:00 +0000https://infotechwithben.com/posts/shadow-stack-local-vs-api-cost-analysis/Hardware TCO Sample Build: RTX 3090 24GB (used market, ~$700–800) Component Cost RTX 3090 (used) $750 Host server (Proxmox, used workstation) $400 32 GB RAM $80 1 TB NVMe $80 Power (600W system × 8h/day × $0.12/kWh) ~$21/month One-time hardware ~$1,310 Monthly power ~$21 Break-even calculation — you need to compare against API costs you’d otherwise pay. RTX 4060 Ti 16GB Build (~Budget) Component Cost RTX 4060 Ti 16GB $450 Mini PC / used workstation $200 16 GB RAM $40 512 GB NVMe $50 Power (250W × 8h × $0.https://infotechwithben.com/posts/shadow-stack-complete-guide/Sat, 28 Mar 2026 00:00:00 +0000https://infotechwithben.com/posts/shadow-stack-complete-guide/What Is the Shadow Stack? The “shadow stack” is a local inference layer that runs alongside your cloud API usage. Instead of every prompt hitting OpenAI or Anthropic, lightweight or private workloads run on GPUs you already own. You choose the right tier per task. Three deployment tiers: Cloud APIs — Claude, GPT-4o, Gemini. Highest quality, per-token cost, zero ops. Local inference — Llama 3, Mistral, Phi-3 on your hardware. Fixed cost after setup, full data sovereignty.