Best AI for Math
Rankings of the best AI models for mathematical reasoning. Compare models by math problem solving and mathematical capabilities.
About this ranking
As of April 2026, Gemini 3 Pro leads math benchmarks with a score of 100.0, followed by GPT-5.2 (100.0) and GPT-5.2 Pro (100.0). All three use extended reasoning, adding 2-5x latency — for latency-sensitive workloads, the fastest model above 90% accuracy is often the better choice.
Ranked by 69 benchmarks including MATH, GSM8K, and AIME competition-level evaluations, sourced from official model cards and independent reproductions.
It depends on difficulty. For word problems and arithmetic, the top 5 models all score above 95% on GSM8K — differences are negligible. For competition math (AMC/AIME), only the top 2-3 score above 70% on MATH-5 problems requiring creative insight. Check the leaderboard above for current rankings.
Yes. Top models handle single-variable calculus, standard differential equations, and integration techniques reliably. Performance drops on multi-variable calculus, partial differential equations, and problems requiring geometric intuition. For symbolic computation, dedicated tools like Wolfram Alpha remain more reliable.
They serve different purposes. AI models explain reasoning step-by-step and handle word problems naturally. Wolfram Alpha excels at precise symbolic computation and doesn't make arithmetic errors. For learning and tutoring, AI models are better. For guaranteed-correct symbolic answers, Wolfram Alpha is better.
Reasoning models (like o-series) spend more compute per problem, generating internal chains of thought before answering. They outperform standard models by 10-30% on hard math but cost 3-5x more and respond slower. For simple arithmetic, a standard model is sufficient and much faster.
On grade-school word problems (GSM8K), top models exceed 95% accuracy. On competition math (MATH benchmark), scores range from 50-85% depending on difficulty level. On Olympiad problems (IMO level), even the best models score below 50%. Accuracy drops sharply as problems require more creative reasoning.