OpenAI’s Most Advanced Reasoning Models

Just days after the launch of the GPT 4.1 family, OpenAI has released its o3 and o4-mini reasoning models, taking a leap towards AGI (Artificial General Intelligence). The o3 and o4-mini aren’t just AI models; they are AI systems that come with advanced intelligence, autonomy, tool calling function, and real-world software engineering skills. These new models don’t wait for you to do the work; they go ahead, use their tools, and autocomplete tasks themselves! So let’s dive in and explore the features, benchmark performances, and applications of the new o-series models – o3 and o4-mini.

What are o3 and o4-mini?

o3 and o4-mini are OpenAI’s newest reasoning models, succeeding and replacing previous models in the o-series like o1 and o3-mini. Unlike standard LLMs that primarily focus on pattern recognition and text generation, these reasoning models employ a longer internal “chain of thought” process.

This allows them to break down complex problems, evaluate different steps, and arrive at more accurate and thoughtful solutions. Hence, they especially excel in domains like STEM, coding, and logical deduction. Furthermore, these models are the first in the o-series capable of agentically using and combining the full suite of tools available within ChatGPT.

o3 is OpenAI’s most advanced reasoning model to date, excelling in tasks that require deep analytical thinking across various domains. Built with 10 times the compute put into o1, this model introduces the ability to “think with images.” This allows it to process and reason about visual inputs directly within its cognitive processes, which is phenomenal​

o4-mini serves as a compact, efficient, and cost-effective counterpart to o3. While smaller in size, it delivers impressive performance, particularly in areas like math, coding, and visual tasks. Its optimized design ensures faster responses and higher throughput, making it suitable for applications where speed and efficiency are paramount.​

Other Models: OpenAI has also released an o4-mini-high variant, which takes more time for potentially more reliable answers.

Future Releases: An even more powerful version, o3-pro, utilizing more compute resources, is planned for release to Pro subscribers in the near future.

Also Read: Llama 4 Models: Meta AI is Open Sourcing the Best

Key Features of o3 and o4-mini

Here are some of the key features of these advanced and powerful reasoning models:

• Agentic Behavior: They exhibit proactive problem-solving abilities, autonomously determining the best approach to complex tasks and executing multi-step solutions efficiently.​
• Advanced Tool Integration: The models seamlessly utilize tools such as web browsing, code execution, and image generation to enhance their responses and tackle complex queries effectively.​
• Multimodal Reasoning: They can process and integrate visual information directly into their reasoning chain, which enables them to interpret and analyze images alongside textual data.​
• Advanced Visual Reasoning (“Thinking with Images”): The models can interpret complex visual inputs like diagrams, whiteboard sketches, or even blurry/low-quality photos. They can even manipulate these images (zoom, crop, rotate, enhance) as part of their reasoning process to extract relevant information.

Do o3 and o4-mini Reflect AGI?

Both these ‘o-series’ models are specifically designed to think more deeply and perform complex, multi-step reasoning before generating a response.

When given a problem to solve, o3 first uses brute force to come up with a solution. The model then finds a smarter way to do the calculation and presents it in a neater format. It  further goes on to recheck the answer and simplifies it to provide the user with a very simple and easily understandable response.

Now, although part of this thinking process is based on the compute and training, these models weren’t explicitly taught to simplify the answer or recheck it. This makes them self evolving and self learning models, which inch us closer towards AGI.

Moreover, o3 can autonomously decide when and how to use the various tools available within ChatGPT (web search, Python data analysis, DALL·E image generation, and vision) to solve complex, multi-faceted queries. It can chain multiple tool calls, search the web iteratively, analyze results, and synthesize information across modalities.

Also Read: Towards AGI: Technologies, Challenges, and the Path Ahead

Availability of o3 and o4-mini

Both models are accessible through OpenAI’s ChatGPT platform and API services:​

ChatGPT Access: Users subscribed to ChatGPT Plus, Pro, and Team plans can utilize o3, o4-mini, and o4-mini-high models directly on the chat interface. Enterprise and Education users will gain access within a week. Free-tier users can experience o4-mini by selecting the ‘Think’ option before submitting their queries.​

API Access: Developers can integrate o3 and o4-mini into their applications via OpenAI’s Chat Completions API and Responses API, enabling customized AI solutions across various platforms.​

o3 and o4-mini: Benchmark Performance

Both o3 and o4-mini models have demonstrated exceptional capabilities across a range of standard benchmark tests.

• SWE-Lancer: The high variants of both these models perform exceptionally well in this coding benchmark, putting their ancestors to shame.
• SWE-Bench Verified (Software Engineering): o3 achieved a score of 69.1%, while o4-mini closely followed with 68.1%. Both models significantly outperformed previous models like o3-mini (49.3%) and competitors such as Claude 3.7 Sonnet (63.7%).​
• Aider Polyglot (Code Editing): Both these models prove to be the best from OpenAI when it comes to this code editing benchmark, setting new records.

• AIME 2025 (Mathematics): o4-mini set a new benchmark here by scoring 99.5% when equipped with a Python interpreter, while o3 is right behind, scoring 98.4%.
• Codeforces (Competitive Programming): o4-mini achieved an Elo rating of 2719, reflecting its advanced problem-solving skills in competitive programming scenarios. Meanwhile, o3 scores 2706, still performing exponentially better than the other models.
• GPQA Diamond (PhD-Level Science): o3, without any tools, demonstrated advanced scientific reasoning by achieving an accuracy of 87.7% on this benchmark. o4-mini follows right behind with 81.4%.

• MMMU (Massive Multimodal Multitask Understanding): o3 excelled in this benchmark, showcasing its ability to handle diverse and complex tasks involving both textual and visual data.

• Humanity’s Last Exam: On this benchmark assessing expert-level reasoning across various domains, o3 achieved an accuracy of 26.6% outperforming all other OpenAI models. Meanwhile o4-mini significantly outperforms its predecessor, o3-mini.

Applications of o3 and o4-mini

The enhanced reasoning, tool use, and visual capabilities of o3 and o4-mini unlock a wide range of potential applications, including:

• Complex Data Analysis & Reporting: Analyzing datasets by writing and executing Python code, fetching supplementary information from the web, and generating summaries or visualizations.
• Advanced Scientific Research: Assisting researchers by interpreting complex diagrams, analyzing experimental data, searching literature, and potentially suggesting new avenues of inquiry.
• Sophisticated Coding & Software Engineering: Debugging complex code, generating code based on visual mockups or diagrams, understanding repository structures, and performing multi-step software development tasks.
• Education & Tutoring: Explaining complex STEM concepts using step-by-step reasoning, interpreting textbook diagrams or handwritten notes, and providing interactive problem-solving assistance.
• Multimodal Content Creation & Understanding: Generating detailed descriptions or analyses of images, creating content that requires integrating text and visual elements, and answering questions based on visual evidence.
• Business Intelligence & Strategy: Analyzing market trends using real-time web data, developing forecasts, and creating strategic plans based on integrated information sources.
• Creative Problem Solving: Tackling open-ended challenges that require combining different types of information and reasoning steps.

Conclusion

OpenAI’s o3 and o4-mini models represent a significant advancement in AI capabilities, particularly in reasoning and multimodal understanding. By integrating deep reasoning with versatile, agentic tool use and the novel ability to “think with images,” these models set a new standard for AI intelligence and utility. Their impressive performance across a variety of benchmarks underscores their potential to tackle complex, real-world tasks in fields ranging from software engineering to scientific research.

While o3 offers peak performance for the most demanding tasks, o4-mini provides a compelling blend of capability, speed, and cost-efficiency. Both models, however, share the same agentic and autonomous capabilities that showcase how advanced AI has become. As AI continues to evolve, such innovative models will pave the way for more sophisticated and versatile applications, bringing us closer to achieving AGI.​

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