The article evaluates the bug detection capabilities of two OpenAI models, o1 and 4o-mini, on a dataset of real-world bugs across five programming languages. The results show that 4o-mini outperformed o1 in four out of five languages, with especially strong results in Ruby and Python, where logical reasoning is required. This suggests that 4o-mini's added reasoning phase helps it detect bugs that don't follow obvious patterns, making it more robust in complex codebases. In contrast, o1 excels when there are clear patterns and performed slightly better in TypeScript, a highly structured language. The study highlights the importance of choosing the right model based on the specific use case, with 4o-mini being better suited for real-world reviews and o1 being more suitable for high-volume, pattern-rich environments.