Developer Switches from Gemini Pro to Flash High Mode After Costly Bugs and Token Overruns

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A developer building a Point of Sale SaaS project initially relied on Gemini 3.1 Pro for agentic coding but encountered severe regressions, including broken dashboard analytics caused by the model rewriting SQL queries without respecting cross-module dependencies. Switching to GPT-based models resolved some issues but quickly became unsustainable due to rapid token quota exhaustion and high API costs. Community benchmarks on Agent Arena suggested Flash models outperformed 3.1 Pro on agentic tasks, prompting a trial of Gemini 3.6 Flash, which proved faster and more cost-efficient. The developer later upgraded to Gemini 3.7 Flash in High Mode, which handled complex multi-table queries cleanly, avoided unintended file changes, and kept token usage low. The project was ultimately delivered on time, with the developer crediting the model switch as the key turning point.

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