The article evaluates two advanced AI language models, OpenAI o3-mini and o4-mini, on their ability to detect hard-to-find bugs in code. The evaluation dataset consists of 210 programs with small, realistic bugs introduced by the author. The results show that o3-mini significantly outperformed o4-mini overall, detecting 37 out of 210 bugs compared to o4-mini's 15. A detailed breakdown by programming language reveals that o3-mini excelled in Python, Go, TypeScript, and Rust, while o4-mini showed promise in Ruby. The study highlights the potential advantages of enhanced reasoning capabilities in certain languages and suggests that future AI-driven software verification tools could benefit from balancing pattern recognition with logical reasoning.