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Taz / ByteCalculators
Taz / ByteCalculators

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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!

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Taz / ByteCalculators

I'm currently working on adding Claude 4.6 Sonnet to the comparison logic. Do you feel the 'Retry Tax' is higher or lower on Anthropic's models compared to GPT-5.2?"