Core Viewpoint - The article discusses the confusion surrounding the naming and selection of OpenAI models, providing a guide for users to choose the appropriate model based on their tasks and needs [1][4][30]. Model Selection Guide - OpenAI's model naming has been inconsistent, leading to confusion among users about which model to use for specific tasks [5][6]. - A guide by Karpathy categorizes models based on their strengths: - o3 is recommended for complex tasks, while 4o is suitable for everyday questions [10][12]. - Karpathy emphasizes that using o3 is crucial for important tasks, as it outperforms 4o in reasoning capabilities [11][16]. - For coding assistance, GPT-4.1 is suggested for improving existing code rather than writing from scratch [17][18]. User Experience and Recommendations - Karpathy shares personal usage statistics, indicating that he uses 40% of the time for 4o in simple queries and 40% for o3 in complex inquiries [15][16]. - A tip is provided for deep research, which is based on o3 but is not directly equivalent to it [20][21]. - Users are encouraged to keep a reference image for quick model selection [22]. Community Feedback - The article notes that users have varying experiences with the models, with some finding o4-mini to be nearly as effective as o3 but faster [32]. - Karpathy suggests a simple decision-making process for model selection based on task importance and urgency [33]. Conclusion - The guide aims to alleviate user confusion and improve the selection process for OpenAI models, highlighting the importance of reasoning in model choice [30][37].

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