GPT-5.2OpenAI

Is GPT-5.2 Good for Math?

GPT-5.2 is a competent math model that handles calculus, statistics, and applied mathematics reliably. Here's an honest assessment of where it stands against the math-specialized competition.

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Our verdict
7/10

GPT-5.2 is a solid choice for applied mathematics, statistics, and computational math, particularly when combined with code execution. It handles calculus, probability, linear algebra, and data-oriented math problems well. However, it is not the top model for pure mathematical reasoning: DeepSeek V3 dominates on competition-level problems and formal proofs, while Claude Sonnet 4.5 provides clearer step-by-step explanations for educational use. GPT-5.2 earns its place through reliability and its ability to seamlessly combine mathematical reasoning with code.

Where GPT-5.2 excels at math

1Strong Applied Mathematics

GPT-5.2 excels at the kind of math that shows up in real-world applications: statistics, probability, optimization problems, and financial modeling. It handles these tasks more reliably than it handles abstract theoretical math.

2Seamless Math-to-Code Integration

GPT-5.2 can derive a formula and immediately produce working Python, R, or MATLAB code to compute it. This tight coupling between mathematical reasoning and code generation is a significant productivity advantage for engineers and data scientists.

3Reliable Structured Output for Math

When you need math results in a specific format, such as LaTeX, JSON with computed values, or structured tables, GPT-5.2 follows formatting instructions more consistently than other models, reducing manual cleanup.

4Broad Curriculum Coverage

From basic algebra through graduate-level statistics, GPT-5.2 covers the full breadth of standard mathematics curricula. It handles standard textbook problems across all common topics with consistent accuracy.

Limitations to consider

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Weaker on Competition-Level Problems

On olympiad-style and competition math, GPT-5.2 trails DeepSeek V3 significantly. If your use case involves advanced combinatorics, number theory proofs, or mathematical competition prep, DeepSeek is the better model.

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Less Rigorous Step-by-Step Reasoning

GPT-5.2 sometimes skips intermediate steps or makes logical leaps in proofs. Claude Sonnet 4.5 provides more thorough, pedagogically clear derivations that are better suited for educational contexts.

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Occasional Calculation Errors

Like all LLMs, GPT-5.2 can make arithmetic errors in multi-step calculations. For critical computations, always verify results with code execution or use GPT-5.2's own code interpreter to double-check numerical answers.

Pro tips

Get more from GPT-5.2 for math

01

Ask GPT-5.2 to write and execute code for any computation that involves more than a few arithmetic steps to avoid calculation errors.

02

For proofs and derivations, explicitly request 'show every intermediate step' to reduce the chance of logical gaps.

03

Use LLMWise Compare mode to send hard math problems to both GPT-5.2 and DeepSeek V3 simultaneously and cross-check their solutions.

04

Specify the output format (LaTeX, plain text, or code) in your prompt to get results you can directly paste into your workflow.

Evidence snapshot

GPT-5.2 for math

How GPT-5.2 stacks up for math workloads based on practical evaluation.

Overall rating
7/10
for math tasks
Strengths
4
key advantages identified
Limitations
3
trade-offs to consider
Alternative
DeepSeek V3
top competing model
Consider instead

DeepSeek V3

Compare both models for math on LLMWise

View DeepSeek V3

Common questions

Is GPT-5.2 or DeepSeek V3 better at math?
DeepSeek V3 is better for pure mathematical reasoning, competition-level problems, and formal proofs. GPT-5.2 is stronger at applied math, statistics, and tasks that combine math with code generation. DeepSeek is also significantly cheaper.
Can GPT-5.2 solve calculus problems?
Yes. GPT-5.2 handles standard calculus reliably, including derivatives, integrals, series, and differential equations. For multi-step problems, ask it to generate verification code to catch any arithmetic errors.
How accurate is GPT-5.2 at math?
GPT-5.2 is reliable for standard curriculum math through graduate-level statistics and applied math. Accuracy drops on olympiad-level problems and complex proofs. Always verify critical calculations with code execution.
Should I use GPT-5.2 for math tutoring?
GPT-5.2 is a good math tutor for applied topics, but Claude Sonnet 4.5 provides clearer pedagogical explanations with more detailed step-by-step reasoning. Use LLMWise to compare both on sample problems before choosing.
How much does GPT-5.2 API cost for math problems?
GPT-5.2 charges premium per-token rates, and math problems with detailed step-by-step solutions use more output tokens. LLMWise credits keep costs predictable, and you can route routine math to DeepSeek V3 at a fraction of the price.
What are the limitations of GPT-5.2 for math?
GPT-5.2 struggles with olympiad-level competition math and can make arithmetic errors in long calculations. It also provides less rigorous step-by-step reasoning than Claude Sonnet 4.5. Use LLMWise Compare mode to cross-verify critical solutions.

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