The article compares two compact Language Model-based (LLM) models, o1-mini and 4o-mini, developed by OpenAI, in their ability to detect real bugs in real code. The evaluation dataset consists of 210 programs across five languages, each with a small, difficult-to-catch, and realistic bug. The results show that 4o-mini outperforms o1-mini in detecting bugs, particularly in high-context situations where identifying a bug requires understanding the logic and intent behind the code. This suggests that 4o-mini has a deeper logical reasoning capability, which allows it to generalize better and detect more complex bugs. The article highlights the importance of reasoning capabilities in AI-powered code review and concludes that 4o-mini is clearly stronger for this task.