Is ChatGPT o3 Really Better at Math

OpenAI’s new o3 model isn’t just an incremental upgrade—it shows a meaningful leap in symbolic reasoning and applied math. In a recent test, OpenAI compared o3 to the earlier o1 model using a complex math problem involving polynomial construction and factorization. The task required understanding abstract algebra, polynomial identities, and recurrence relations—well beyond what most general-purpose AI models could handle.

The result?ChatGPT o3 successfully constructed the required polynomial, verified its mathematical properties, and computed the final result using Python—all within seconds. ChatGPT o1, by contrast, struggled to complete the task.

Why this matters to engineers

This isn’t just academic. Here’s why o3’s math improvements could impact real-world engineering tasks:

• Process engineers can use it to verify equations for heat exchangers, flow balancing, or control loop stability.

• Project managers can ask it to check spreadsheet logic behind cost rollups, volume estimates, or tank sizing.

• Junior engineers can use it as a learning partner to walk through formulas step-by-step—especially on topics like valve sizing or pressure drop.

More importantly, ChatGPT o3 now reasons through why it’s taking each step, not just what the answer is—making it far more usable in a professional setting.

Final thoughts

This level of math reasoning isn’t a replacement for human review—but it’s now useful enough to catch errors, double-check assumptions, or guide you through a solution path. If you’re in engineering or technical management, it’s worth understanding what this model can (and can’t) do.

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