How I Built a "Retry Tax" Simulator to Solve My AI Unit Economics Debt

Hello DEV! 👋 Like many of you, I’ve been migrating my agents from OpenAI to models like DeepSeek-V3.2 to save on costs. On paper, it’s a 10x saving. In production, it’s a different story. I kept hitting what I now call the 'Retry Tax'. If a model is cheaper but requires 3 retries to get the logic right, are you actually saving money? To solve my own headache, I built a simple AI Cost & Retry Simulator. What it does: Compares GPT-5.2 vs DeepSeek V3.2 (using March 5th live rates). Factors in Context Caching (the 90% discount). Includes a Standard vs Batch Mode toggle. I built this with vanilla JS to keep it fast. It’s been a life-saver for my margin planning this month. Check it out here: https://bytecalculators.com/deepseek-ai-token-cost-calculator I'd love to hear how you guys are calculating your "break-even" point. Is a 3x retry multiplier too optimistic for complex reasoning? Let's discuss!