The New Era of ChatGPT: What Makes o1-preview Different from GPT-4o?

1. Is GPT-4o Being Replaced by o1-preview?

The introduction of the ChatGPT o1-preview series marks a fundamental shift in how AI models process information and solve problems. Unlike GPT-4o, the o1-preview model is designed to spend more time thinking before providing an answer. It mimics the human approach to tackling difficult tasks—analyzing, trying different strategies, identifying mistakes, and correcting them.

In tests conducted by OpenAI, o1 models demonstrated significantly better performance in solving complex problems in physics, chemistry, and biology. While GPT-4o correctly solved only 13% of tasks in the International Mathematical Olympiad (IMO) qualifying exam, the o1-preview model successfully solved 83%. This demonstrates the o1 models’ superior reasoning capabilities in complex contexts.

And here is an interesting fact: ChatGPT o1-preview couldn’t generate content about itself. The reason for this might stem from the limitations in its knowledge base and the stage of its development. While o1-preview models excel at reasoning and complex analysis, their knowledge base may not be as broad as GPT-4o’s. As a pre-release model, o1-preview may lack detailed access to its own architecture or the context in which it was developed. Additionally, since o1-preview is designed for tasks requiring deep thought and complex problem-solving, it may not be as effective in generating content about its own evolution—something GPT-4o, with its broader general knowledge, can handle more efficiently. As an early-stage model, the o1-preview’s knowledge base and functionality may still be partially limited compared to more mature models like GPT-4o.

2. Advanced Coding and Debugging Capabilities

The o1 series, particularly o1-mini, also stands out in generating and debugging complex code. This is a key feature for developers who need a tool to solve technical problems and write code at an advanced level. In programming competitions, the o1 model reached the 89th percentile in Codeforces contests, representing a significant improvement compared to GPT-4o.

However, GPT-4o’s speed may be crucial in scenarios where response time is a priority. Since GPT-4o doesn’t spend as much time on deep reasoning, its responses can be provided faster, which is important for simpler tasks that don’t require intensive analysis. For example, GPT-4o generates responses at 103 tokens per second, while o1-mini generates at 73.9 tokens per second. This speed difference makes GPT-4o particularly well-suited for tasks like customer service or real-time data analysis, where quick replies are essential. While o1-mini excels at coding and technical tasks, GPT-4o remains the better choice for scenarios where speed and multitasking are more important than deep problem-solving.

ChatGPT o1-mini was specifically designed with speed and efficiency in mind. It is a smaller model that retains the reasoning capabilities of the o1 series but is 80% cheaper than the o1-preview version. This makes o1-mini an ideal choice for developers and companies who need a cost-effective model for solving programming problems but don’t require broad world knowledge.

3. Safety and Responsibility

A significant aspect of the new model series is also safety. OpenAI has introduced a new training approach that allows these models to reason in the context of safety principles and follow them more effectively. As a result, the o1 models handle situations where users attempt to bypass safety rules (so-called “jailbreaking“) more adeptly. While GPT-4o scored 22 out of 100 in one of the most difficult jailbreak tests, the o1-preview model achieved an impressive score of 84.

Additionally, OpenAI has implemented new internal procedures, including advanced testing and collaboration with governmental institutions, to ensure the safety and compliance of its models with current regulations.