o1 and o1-mini from OpenAI : The latest AI models with unrivalled reasoning capabilities

OpenAI o1: The Birth of AI Reasoning Models

In September 2024, OpenAI introduced o1, a fundamentally different kind of AI model. Unlike GPT-4o which generates responses quickly, o1 was designed to “think” before answering—spending time on internal chain-of-thought reasoning before producing a response. This approach delivered breakthrough performance on mathematics, coding, and scientific reasoning tasks.

o1-mini offered a lighter, faster alternative focused specifically on STEM tasks, providing near-o1 performance on math and coding at significantly lower cost. Together, they established a new category in OpenAI’s model lineup: reasoning models that trade speed for accuracy on complex problems.

From o1 to o3: Rapid Evolution

The reasoning model family evolved rapidly through 2025. o1 Pro (December 2024) added more compute for the hardest problems, available exclusively to ChatGPT Pro subscribers. Then in early 2025, OpenAI released o3 and o3-mini, which represented a generational leap: better reasoning, lower costs, and configurable thinking time (low, medium, high compute options).

o3-mini became particularly popular among developers, offering near-o1-Pro quality on reasoning tasks at a fraction of the price. Its configurable compute approach let developers balance between speed and accuracy depending on the task—a practical solution for production applications.

How Reasoning Models Work

Reasoning models use chain-of-thought processing: before generating a visible response, the model works through the problem step by step internally. This “thinking” phase can last from a few seconds to over a minute for complex problems. The visible output is just the final answer, but behind it lies an extensive reasoning trace.

This approach excels on tasks that benefit from deliberate analysis: multi-step mathematical proofs, debugging complex code with subtle logic errors, scientific reasoning requiring the integration of multiple concepts, and strategic planning problems. On competitive math benchmarks, o3 scored dramatically higher than GPT-4o, demonstrating that reasoning capability is a distinct dimension from general language fluency.

The Current State: GPT-5.4 Thinking (March 2026)

As of March 2026, the reasoning model lineage has been integrated into GPT-5’s hybrid architecture. GPT-5.4 Thinking is the successor to o3, offering advanced reasoning within the unified GPT-5 experience. The intelligent router in GPT-5 automatically engages the thinking sub-model when it detects a query requiring deeper reasoning, making the experience seamless for users.

For developers, the o3-mini API endpoint remains available for applications specifically requiring reasoning at controlled costs. It’s widely used in automated code review pipelines, mathematical computation services, and scientific research tools where reasoning accuracy is critical.

Choosing Between Standard and Reasoning Models

The choice depends on your task. For general conversation, creative writing, translation, and most everyday tasks, standard GPT-4o mini or GPT-5.3 Instant is faster and more cost-effective. For complex coding, mathematics, scientific analysis, legal reasoning, and tasks requiring step-by-step logical deduction, reasoning models provide significantly more reliable results.

For a detailed comparison of the standard models, see our GPT-4o vs GPT-4o mini comparison. The key insight is that AI capabilities are no longer one-dimensional—the best results come from matching the right model type to the specific task at hand.