Claude vs Kimi for Math
Kimi narrowly outperforms Claude on pure mathematics (AIME 2025: 96.1% vs 95.6%), making it marginally better for competition-style math and rigorous problem-solving. However, Claude's extended thinking capability provides clearer advantages for complex mathematical reasoning and proofs, with better overall performance on advanced science benchmarks. For price-conscious mathematicians, Kimi is compelling; for comprehensive problem-solving across domains with established support, Claude is the stronger choice.
Head-to-Head for Math
| Criteria | Claude | Kimi | Winner |
|---|---|---|---|
| Competition Math (AIME-style problems) | Excellent arithmetic and proofs | Slightly stronger edge overall | Kimi |
| Quantitative Reasoning Depth (GPQA) | Superior analytical rigor | Competitive but narrower margin | Claude |
| Extended Thinking for Complex Proofs | Adjustable depth thinking capability | Parallel component reasoning approach | Tie |
| Applied Math Problem Solving | Strong decomposition and clarity | Effective multi-step coordination | Tie |
| Cost Efficiency for Math Tasks | Premium pricing, higher cost | Significantly cheaper API access | Kimi |
Competition Math (AIME-style problems)
Claude
Excellent arithmetic and proofs
Kimi
Slightly stronger edge overall
Quantitative Reasoning Depth (GPQA)
Claude
Superior analytical rigor
Kimi
Competitive but narrower margin
Extended Thinking for Complex Proofs
Claude
Adjustable depth thinking capability
Kimi
Parallel component reasoning approach
Applied Math Problem Solving
Claude
Strong decomposition and clarity
Kimi
Effective multi-step coordination
Cost Efficiency for Math Tasks
Claude
Premium pricing, higher cost
Kimi
Significantly cheaper API access
See Them Answer a Math Question
We asked both models the same math-focused prompt.
“Solve the integral ∫(x²·eˣ)dx step by step, explaining each application of integration by parts and verifying your answer by differentiation.”
Solve the integral ∫(x²·eˣ)dx step by step, explaining each application of integration by parts and verifying your answer by differentiation.
Integration by Parts: ∫x²eˣ dx
Setup and Method
Integration by Parts Formula: ∫u dv = uv − ∫v du
This integral requires repeated application because differentiating x² takes two steps to reach a constant.
First Application of Integration by Parts
Choose:
| Variable | Assignment | Reason |
|---|---|---|
| u = x² | du = 2x dx | Differentiates toward 0 |
| dv = eˣ dx | v = eˣ | eˣ is its own integral |
Applying the formula:
The remaining integral ∫xeˣ dx still needs integration by parts.
Second Application of Integration by Parts
Working on ∫xeˣ dx — Choose:
| Variable | Assignment |
|---|---|
| u = x | du = dx |
| dv = eˣ dx | v = eˣ |
Applying the formula:
Combining the Results
Substituting back into the first result:
Verification by Differentiation
Differentiate F(x) = eˣ(x² − 2x + 2) using the product rule:
This matches our original integrand, confirming the answer is correct.
Key Pattern (LIATE Rule)
When choosing u, pick the function that simplifies when differentiated: Logarithms → Inverse trig → Algebraic (polynomials) → Trig → Exponentials
For xⁿeˣ, always let u = xⁿ and dv = eˣ dx, applying integration by parts n times until the polynomial disappears.
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Detailed Breakdown
Both Claude and Kimi are strong math performers, and the benchmark numbers tell a surprisingly close story. On AIME 2025 — one of the most demanding math competition benchmarks — Kimi edges ahead with 96.1% versus Claude's 95.6%. On GPQA Diamond, which tests graduate-level scientific reasoning including quantitative problems, Claude leads at 89.9% versus Kimi's 87.6%. For most math use cases, these differences are marginal, but the context around each model matters more than the raw numbers.
Claude's extended thinking feature is a genuine advantage for complex mathematical work. When tackling multi-step proofs, calculus problems, or combinatorics, Claude can be prompted to reason through intermediate steps methodically before arriving at a final answer. This reduces the chance of confident-sounding errors that skip critical reasoning steps — a common failure mode in AI math assistance. Claude also handles symbolic math notation well in prose explanations, making it useful for writing up solutions in a clear, teachable format. For students and educators who need not just the answer but a well-explained derivation, Claude's writing quality gives it a natural edge.
Kimi's competitive AIME score suggests it has been specifically trained or fine-tuned with a focus on mathematical reasoning, and its parallel sub-task coordination makes it capable of breaking down complex problems into structured components. For API users building math-heavy applications on a budget, Kimi's pricing (~$0.60/1M input tokens versus Claude's ~$3.00) is a compelling reason to consider it. Kimi also supports image understanding, which means it can parse handwritten equations or math diagrams from an uploaded photo — a practical feature for students working from textbooks or handwritten notes.
Claude, however, has the advantage of file uploads, which allows users to submit entire problem sets, exam PDFs, or research papers for analysis. For professionals or academics dealing with applied mathematics — engineering calculations, statistical modeling, financial math — this workflow flexibility is significant.
In real-world terms: a high school student prepping for math competitions might find Kimi's raw solving speed appealing, while a university student writing proofs or a professional needing step-by-step explanations will likely get more value from Claude's structured, articulate reasoning.
Recommendation: For pure problem-solving throughput and cost efficiency, Kimi is a strong choice. For math learning, tutoring, and detailed explanations where the quality of reasoning matters as much as the answer, Claude is the better pick. If budget isn't a constraint and you need reliable, explainable math work, go with Claude.
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