So let\u2019s start.<\/p>\n\n\n\n
What Is GPT-o1?<\/h2>\n\n\n\n
In September 2024, OpenAI launched GPT-o1-preview, alongside a lighter, more cost-efficient variant called o1-mini. <\/p>\n\n\n\n
By December 2024, the preview version was officially replaced by the full GPT-o1 model. <\/p>\n\n\n\n
According to OpenAI, GPT-o1 is made to tackle highly complex problems by dedicating more computational “thinking” time before generating responses. <\/p>\n\n\n\n
This includes advanced tasks like competitive programming, abstract mathematics, and scientific reasoning, which the model can handle with near-expert finesse.<\/p>\n\n\n\n
And the tests are evidence of this expertise. <\/p>\n\n\n\n
In benchmark testing, o1-preview ranked in the 89th percentile on Codeforces<\/a> competitions.<\/p>\n\n\n\n On the American Invitational Mathematics Examination<\/a>, o1 solved 83% of problems (12.5\/15). By comparison, GPT-4o barely cracked 13% (1.8\/15).<\/p>\n\n\n\n This model also showed PhD-level proficiency across multiple scientific domains (physics, chemistry, and biology).<\/p>\n\n\n\n So it\u2019s clear that the model was made for research and technical applications, primarily.<\/p>\n\n\n From GPT-o1\u2019s perspective, the differences to GPT-3.5, GPT-4 and GPT-4o are both subtle and stark, depending on the task at hand.<\/p>\n\n\n\n GPT-3.5 operates on an older dataset with a limited 16,385 context window (4,096 output tokens) and offers basic reasoning and decent coding skills. <\/p>\n\n\n\n It does okay with general prompts, but hand it a problem with nested logic or a tricky algorithm, and you’ll quickly see its edges. <\/p>\n\n\n\n Compared to it GPT o1 operates in a different cognitive class. So, the comparison isn\u2019t right.<\/p>\n\n\n\n GPT-4 remains solid, more refined than 3.5 and capable across a broader range of tasks, especially those needing nuance. But even it doesn\u2019t dig into technical complexity with the same rigor as o1. <\/p>\n\n\n\n GPT-4o further refined speed and multimodal capabilities but still lagged in deep analytical tasks.<\/p>\n\n\n\n It’s faster, more interactive, and better equipped for general-purpose use. It handles creative writing, chatting, and multimedia tasks better than o1 for now. <\/p>\n\n\n\n But, when it comes to logic-heavy use cases, o1 holds a measurable lead. <\/p>\n\n\n\n That said, GPT-o1 lacks some user-friendly features like web browsing or file uploads, which GPT-4o supports.<\/p>\n\n\n\n The mode can also be a little terse. Its refusal responses are shorter, which sometimes skip over references or deeper explanations that 4o tends to include. <\/p>\n\n\n\n Another major caveat of o1 is that it can amplify risks when addressing dangerous queries. <\/p>\n\n\n\n For example, when asked about rock-climbing techniques, GPT-o1\u2019s in-depth engagement could encourage over-reliance<\/a>, whereas GPT-4o defaults to generic advice.<\/p>\n\n\n [source<\/a>]<\/p>\n\n\n\n![\"\"](\"https:\/\/undetectable.ai/blog\/wp-content\/uploads\/2025\/04\/PhD-level-1024x464.jpg\")
<\/picture><\/figure><\/div>\n\n\nHow It Differs from GPT-3.5, GPT-4 & GPT-4o<\/h3>\n\n\n\n
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