Identifying the 'Pivot Point': When does DeepSeek-V3.2 actually become cheaper than GPT-5.2?

I’ve been obsessed with AI Unit Economics lately. Most founders look at the raw token cost ($0.28 vs $1.75) and think it’s a no-brainer.

But after stress-testing agents in production, I realized we're ignoring the 'Retry Tax'. If a cheaper model needs 3 retries to match the reasoning quality of a flagship model, your margins might actually shrink.

I built a simple simulator to find the exact 'Pivot Point' where scaling becomes cost-effective without sacrificing quality. It factors in:

March 5th Live Pricing (GPT-5.2 vs DeepSeek V3.2)

Context Cache Discounts (90% off for regenerations)

Quality Multipliers (The "Retry Tax")

I’d love some brutal feedback on the math. Are you guys seeing a similar 2x-3x retry rate for complex reasoning, or is my 'Quality Multiplier' too harsh?

Simulator logic here: https://bytecalculators.com/deepseek-ai-token-cost-calculator