April 16, 2025 Openai released Updated versions of advanced reasoning models. These new models, called O3 and O4-Mini, offer improvements to their predecessors, O1 and O3-Mini respectively. The latest models provide increased performance, new functions and greater availability. In this article, he examines the main benefits of O3 and O4-Mini, presents their main possibilities and discusses how they can affect the future of the AI application. But before we immerse ourselves in what distinguishes O3 and O4-Mini, it is important to understand how OpenAI models have evolved over time. Let's start with a short review of OPENENAI in developing increasingly powerful language and reasoning systems.
Evolution of large OPENAI language models
The development of large OPENAI language models began with GPT-2 AND GPT-3which brought chatgpt to the mainstream due to their ability to produce a liquid and accurate contextual text. These models have been widely admitted to tasks such as summary, translation and answer to questions. However, when users applied them to more complex scenarios, their flaws became clear. These models often fought with tasks that required deep reasoning, logical consistency and multi -stage problem solving. To meet these challenges, Opeli introduced GPT-4 and focused on increasing the ability to reason its models. This change led to the development of O1 i O3-mini. Both models were used a method called chain hints, which allowed them to generate more logical and accurate answers by reasoning step by step. While O1 is intended for advanced problem solving, O3-Mini is built to ensure similar possibilities in a more efficient and profitable way. Based on this foundation, Opeli has now introduced O3 and O4-Mini, which further increases the ability to reason their LLM. These models are designed to obtain more accurate and well-understood answers, especially in technical fields, such as programming, mathematics and scientific analysis, in which logical precision is crucial. In the following section we will examine how O3 and O4-Mini improve their predecessors.
Key progress in O3 and O4-Mini
Improved reasoning opportunities
One of the key improvements of O3 and O4-Mini is their increased ability to reason complex tasks. Unlike previous models that provided quick answers, the O3 and O4-Mini models spend more time to process each monitors. This additional processing allows them to reason and create more accurate answers, which leads to improving results on comparative tests. For example, O3 exceeds O1 by 9% ON Livebench.aiThe reference point, which assesses the performance in many complex tasks, such as logic, mathematics and code. On his bench, who tests reasoning in software engineering tasks, O3 achieved the result 69.1%Even out exceeding competitive models, such as Gemini 2.5 Pro, which achieved the rating 63.8%. Meanwhile, O4-Mini obtained 68.1% at the same reference point, offering almost the same reasoning depth at much lower costs.
Multimodal integration: Thinking with images
One of the most innovative features of O3 and O4-Mini is their ability to “think with images”. This means that they can not only process text information, but also integrate visual data directly with the process of reasoning. They can understand and analyze images, even if they are of low quality – such as handwritten notes, sketches or diagrams. For example, the user can send a scheme of a complex system, and the model can analyze it, identify potential problems, and even suggest improvements. This ability combines the gap between text and visual data, enabling more intuitive and comprehensive interactions with AI. Both models can perform actions such as enlargement of details or rotating images to better understand them. This multimodal reasoning is a significant progress in relation to its predecessors, such as O1, which were primarily textual. It opens new applications in areas such as education in which visual aids are crucial, and studies in which diagrams and charts are often crucial for understanding.
Advanced use of tools
O3 and O4-Mini are the first Openai models that simultaneously use all tools available in ChatGPT. These tools include:
- Viewing websites: enabling models to download the latest information about sensitive queries.
- Python code: enabling them to perform complex calculations or data analysis.
- Image processing and generation: Increasing their ability to work with visual data.
By using these tools, O3 and O4-Mini can more effectively solve complex, multi-stage problems. For example, if the user asks a question requiring current data, the model can conduct internet search to download the latest information. Similarly, in the case of tasks covering data analysis, it can be performed by Python code for data processing. This integration is a significant step towards more autonomous AI agents that can support a wider range of tasks without human intervention. Introduction Codex cli, Light, Open Source, which works with O3 and O4-Mini, additionally increases their usability for programmers.
Implications and new possibilities
The O3 and O4-Mini editions have widespread implications in the industries:
- Education: These models can help students and teachers, providing detailed explanations and visual aids, thanks to which more interactive and effective learning. For example, a student can send a sketch of a mathematical problem, and the model can provide a step -by -step solution.
- Tests: They can accelerate the discovery by analyzing complex data sets, generating hypotheses and interpretation of visual data, such as charts and diagrams that are invaluable for fields such as physics or biology.
- Industry: Can optimize processes, improve decision making and improve interactions with clients by handling text and visual questions, such as product design analysis or solving technical problems.
- Creativity and media: The authors can use these models to transform the contours of chapters into simple scenery. Musicians match the graphics to the melody. Film editors receive pace suggestions. Architects transform hand -drawn floor plans into detailed 3 -d plans containing structural and balanced notes.
- Availability and inclusion: For the blind, models describe images in detail. In the case of deaf people, they convert diagrams to visual sequences or signed text. Their translation of both words and visualization helps to fill the gaps in language and culture.
- Towards autonomous agents: Because models can view the network, run the code and process images in one work flow, they form the basis of autonomous agents. Developers describe the function; The model writes, tests and implements the code. Knowledge employees can delegate data collection, analysis, visualization and report writing to one AI assistant.
Restrictions and what next
Despite these progress, O3 and O4-Mini still have a limit of knowledge in August 2023, which limits their ability to respond to the latest events or technologies, unless it has been supplemented by browsing websites. Future iterations probably solve this gap, improving real -time data consumption.
We can also expect further progress in autonomous AI agents – systems that can plan, reason, act and learn constantly with minimal supervision. Integration of OpenAI tools, reasoning models and real -time access signals that are approaching such systems.
Lower line
The new models Openai, O3 and O4-Mini offer improvements of reasoning, multimodal understanding and integration of tools. They are more accurate, versatile and useful in a wide range of tasks – from the analysis of complex data and code generation to interpretation of images. These progress can potentially significantly increase efficiency and accelerate innovations in various industries.
