Quick Answer: For most SaaS apps, route cheap high-volume tasks (classification, extraction, chat) to DeepSeek V4 Flash or Gemini 3.1 Flash-Lite, route agentic coding and customer-facing reasoning to Claude Sonnet 5, and reserve Grok only for features that need live web or X data. Never run every request through one flagship model.
The cheapest way to fix a runaway AI bill is model routing, not model loyalty. Picking one flagship and sending every request to it is the single most common mistake I see in early-stage SaaS stacks.
I rebuilt our support-and-onboarding AI layer three times last year chasing this exact problem, so this comparison is built from actual invoices, not vendor marketing pages.
What Each Model Is Actually Built For
Every one of these five labs is optimizing for a different job, and that's the part most "best AI model" posts skip.
