How I Built a Game Bot That Uses LLM Vision for $0.01/Hour (Not $1/Hour)

Most tutorials about using LLMs for game automation show you how to send screenshots to GPT-4 or Claude every few seconds. It works — but at $1+/hour, you'll burn through hundreds of dollars a month. I built a framework that gets the same results for $0.01/hour . Here's how. The Expensive Way Every 3 seconds: 1. Take screenshot 2. Send to Claude: "What should I do?" 3. Parse response 4. Execute action 5. Repeat Cost: ~1,200 API calls/hour × $0.001 = $1.20/hour This is how most LLM game agents work. It's simple, but the cost adds up fast — especially if you want to run 24/7. The Cheap Way: 5-Layer Hybrid Architecture The insight is that 98% of game decisions don't need AI . You can handle them locally, for free: Layer 5: STRATEGIC AI ──── LLM reviews strategy every 30 min ($0.004) Layer 4: WORKFLOWS ─────── Scripted tap sequences (FREE) Layer 3: WORLD MODEL ───── Tracks timers and predicts events (FREE) Layer 2: STATE MACHINE ─── Detects screens and handles popups (FREE) Layer 1: PERCEP