Do You Need a Smart Model for Routine Tasks? Comparing LLM Performance

An author on Habr investigated whether using top-tier language models is justified for routine programming tasks. The experiment involved four models from the same family completing five identical tasks. The results showed that the most expensive and powerful model was more efficient, completing tasks faster (341 seconds versus 395 for the entry-level model) due to fewer iterations and more concise responses. While most tasks were solved successfully by all participants, the smallest model made a critical error in the fifth test, providing contradictory information. The study highlights that choosing a 'smart' model for daily tasks can be not only higher in quality but also more cost-effective due to speed and code generation accuracy, which reduces the need for manual corrections.