Perplexity vs Kimi for Math

Kimi is the clear winner for math, with exceptional performance on the AIME 2025 benchmark (96.1%) and strong reasoning capabilities that directly translate to mathematical problem-solving. Perplexity's search-focused architecture and citation-heavy approach don't provide advantages for pure math work, where raw reasoning ability matters far more than web access. For serious mathematics, Kimi delivers superior results at a fraction of Perplexity's cost.

Head-to-Head for Math

Mathematical Reasoning

Kimi

Perplexity

General-purpose, reliable reasoning

Kimi

Exceptional: 96.1% on AIME 2025

Multi-step Problem Solving

Kimi

Perplexity

Linear approach, search-focused

Kimi

Excels at coordinating parallel subtasks

Source Verification

Perplexity

Perplexity

Cites sources for reference checking

Kimi

No citations provided

Advanced Math Benchmarks

Kimi

Perplexity

Not specialized for math

Kimi

87.6% GPQA Diamond, 87.1% MMLU Pro

Cost-Effectiveness

Kimi

Perplexity

$20/mo or expensive per query

Kimi

Affordable API at ~$0.60 per M

See Them Answer a Math Question

We asked both models the same math-focused prompt.

Solve the integral ∫(x²·ln(x))dx step by step, then verify your answer by differentiating the result.

Perplexity Sonar Pro

Solve the integral ∫(x²·ln(x))dx step by step, then verify your answer by differentiating the result.

To solve x2lnxdx\int x^2 \ln x \, dx, use integration by parts, with the formula udv=uvvdu\int u \, dv = uv - \int v \, du. Set u=lnxu = \ln x (so du=1xdxdu = \frac{1}{x} dx) and dv=x2dxdv = x^2 dx (so v=x33v = \frac{x^3}{3})[1][2][3].

This gives: x2lnxdx=lnxx33x331xdx=x3lnx313x2dx.\int x^2 \ln x \, dx = \ln x \cdot \frac{x^3}{3} - \int \frac{x^3}{3} \cdot \frac{1}{x} \, dx = \frac{x^3 \ln x}{3} - \frac{1}{3} \int x^2 \, dx.

Integrate the remaining term using the power rule: x2dx=x33,\int x^2 \, dx = \frac{x^3}{3}, so x3lnx313x33+C=x3lnx3x39+C.\frac{x^3 \ln x}{3} - \frac{1}{3} \cdot \frac{x^3}{3} + C = \frac{x^3 \ln x}{3} - \frac{x^3}{9} + C.

The final antiderivative is x33lnxx39+C\frac{x^3}{3} \ln x - \frac{x^3}{9} + C[1][2][3].

Verification by differentiation: Differentiate x33lnxx39\frac{x^3}{3} \ln x - \frac{x^3}{9} using the product rule on the first term and power rule on the second.

  • Product rule: ddx(x33lnx)=x331x+lnx3x23=x23+x2lnx\frac{d}{dx} \left( \frac{x^3}{3} \ln x \right) = \frac{x^3}{3} \cdot \frac{1}{x} + \ln x \cdot \frac{3x^2}{3} = \frac{x^2}{3} + x^2 \ln x.
  • Power rule: ddx(x39)=3x29=x23\frac{d}{dx} \left( -\frac{x^3}{9} \right) = -\frac{3x^2}{9} = -\frac{x^2}{3}.

Adding these: x2lnx+x23x23=x2lnxx^2 \ln x + \frac{x^2}{3} - \frac{x^2}{3} = x^2 \ln x, matching the integrand[1][3].

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Detailed Breakdown

When it comes to math, these two tools are in completely different leagues — and Kimi wins by a wide margin.

Kimi's flagship model scores 96.1% on AIME 2025, one of the most demanding math competition benchmarks available. It also scores 87.6% on GPQA Diamond, which tests graduate-level scientific and quantitative reasoning. These aren't incremental improvements over average models — they place Kimi among the strongest math reasoners available to consumers today. Its extended thinking mode allows it to work through multi-step proofs, algebraic manipulations, and complex word problems in a structured, verifiable way. If you're a student working through calculus problem sets, an engineer doing numerical analysis, or a researcher verifying statistical models, Kimi can handle the heavy lifting with genuine depth.

Perplexity, by contrast, was never designed as a math engine. Its core value proposition is real-time web search with cited sources — useful for looking up formulas, finding worked examples on Khan Academy, or pulling in recent academic papers on a mathematical topic. But when it comes to actually solving problems step by step, Perplexity is limited. It doesn't execute code, it doesn't natively run a symbolic math engine, and its reasoning on complex multi-step problems can be unreliable. It may confidently present a wrong answer with a citation attached, which is arguably worse than admitting uncertainty.

In practice, this distinction matters a lot. If you ask Kimi to solve a system of differential equations or walk through a proof by induction, it will typically produce correct, well-structured work that you can follow and verify. If you ask Perplexity the same thing, you might get a reasonable-looking answer sourced from a math forum — but you'll want to double-check it, which defeats the purpose of using AI assistance.

Where Perplexity does add value for math is as a research companion rather than a solver. Asking "what are the main approaches to solving Laplace's equation?" or "find me recent papers on Fourier transform applications in signal processing" plays to its strengths. For that kind of reference-gathering, its citation model is genuinely useful.

Recommendation: For math, choose Kimi. Its benchmark performance on competition math and graduate-level reasoning is exceptional, and its extended thinking gives you reliable step-by-step problem solving. Use Perplexity only if you need to quickly look up mathematical references or source academic material — not for doing the math itself.

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