The video discusses the release of OpenAI’s new models, O3 and O4 Mini, highlighting their advanced reasoning capabilities and performance benchmarks against Google’s Gemini 2.5 Pro, where OpenAI’s models excel in tasks like coding and multimodal reasoning. Despite their superior performance, the host notes that Gemini offers better cost efficiency, making it an attractive option for users.
In the recent video, the host discusses the release of OpenAI’s new models, O3 and O4 Mini, and compares their performance against Google’s Gemini 2.5 Pro. The video begins with an overview of the O3 model, which was previously used for deep research in ChatGPT. The new models are designed to enhance reasoning capabilities and can utilize various tools within ChatGPT, such as search and data analysis, to provide detailed and thoughtful answers quickly. The host explains the naming conventions of the models, indicating that models with a number are non-thinking, while those with an “O” followed by a number are thinking models.
The video then delves into the specifics of the O3 and O4 Mini models, highlighting their capabilities. O3 is noted for its advanced reasoning, while O4 Mini is the fastest among the advanced reasoning models. The O4 Mini High variant is tailored for coding and visual reasoning tasks. The host emphasizes that these models can think with images rather than just converting them into words, marking a significant advancement in their functionality.
Next, the host presents benchmark comparisons between the OpenAI models and Gemini 2.5 Pro. The benchmarks reveal that OpenAI’s models, particularly O3 and O4 Mini, perform well in various tasks, often outperforming Gemini in areas such as coding and multimodal tasks. The video includes a tally of scores from different benchmarks, showcasing the strengths of OpenAI’s models in comparison to Gemini, particularly in math and coding tasks.
The discussion then shifts to pricing, where the host highlights the cost differences between OpenAI’s models and Gemini. OpenAI’s O3 model is priced at $10 per million tokens, while O4 Mini is significantly cheaper at $1.10 per million tokens. In contrast, Gemini offers a free version and lower pricing for its models, making it a more cost-effective option for users. The host notes that while OpenAI’s models may be superior in performance, the cost efficiency of Gemini makes it an attractive choice for many users.
Finally, the host conducts practical tests using prompts to evaluate the outputs of the different models. The results indicate that while O3 struggles with certain tasks, O4 Mini and O4 Mini High perform better, particularly in speed and output quality. However, the host concludes that despite the promising advancements in OpenAI’s reasoning models, Gemini remains the best value for money. The video wraps up with an invitation for viewers to engage with the host’s community for further resources and learning opportunities related to AI.