OpenAI's new model, referred to as o1, is designed to enhance reasoning capabilities across various tasks, including mathematical, coding, and commonsense reasoning. A recent comparative study indicates that o1 outperforms other models in these domains. Notably, the model achieved a success rate of 34.3% in coding tasks, nearly doubling the performance of its predecessors, and further improved to 42.2% when utilizing a self-debug framework. At the TED AI Conference in San Francisco, OpenAI scientist Noam Brown highlighted that o1's approach, termed 'system two thinking,' can yield performance enhancements comparable to increasing computational resources and data by a factor of 100,000. The model's capabilities were also evaluated against other leading models, including Claude 3.5 Sonnet and Gemini 1.5 pro, with o1 demonstrating superior performance in text-based tasks. Additionally, the PolyMATH benchmark was introduced to assess multimodal reasoning, showing that while Claude 3.5 Sonnet performed best among multimodal models, o1 excelled in text-only assessments, closely matching human performance. The research reflects significant advancements in AI reasoning and problem-solving skills, positioning o1 as a leading model in the field.