Best LLMs for Math (2026)

Large language models best suited for mathematical reasoning, equation solving, proof writing, and quantitative analysis — ranked on MATH, AMC, and AIME benchmarks.

Quick Answer

The best LLM for math in 2026 is o3 — it achieves a gold-medal level score on IMO 2024 problems and leads AIME 2024 at 96.7%, making it the first LLM to genuinely surpass competition math. DeepSeek R1 is the best open-weight alternative: it matches o3-mini on MATH-500 (97.3%) at a fraction of the cost, and is MIT-licensed for self-hosting.

Why o3 is Best for Math

o3 leads our math rankings with gold-medal level performance on competition math benchmarks including AIME and IMO-level problems. Its reasoning chain approach — thinking through problems step by step before committing to an answer — dramatically reduces arithmetic errors and logical mistakes compared to standard auto-regressive generation. This makes it the strongest choice for any quantitative task requiring multi-step reasoning.

Cost Estimate

For a typical math reasoning workload (~20M tokens/month, 70% input / 30% output), the cheapest qualifying model (DeepSeek R1) costs approximately $24.80/month. The most capable model may cost more but delivers higher quality results.

Price vs Quality for Math

Top 5 Models Compared

RankModelProviderInput $/MOutput $/MArena ELOSpeed (tok/s)
#1o3OpenAI$10.00$40.00134015
#2o4-miniOpenAI$1.10$4.401260105
#3DeepSeek R1DeepSeek$0.700$2.50131045
#4Gemini 2.5 ProGoogle$1.25$10.00143070
#5Claude Opus 4Anthropic$5.00$25.00150450

Last updated April 13, 2026

Best LLM for Math — Side-by-Side (2026)

Six models compared on MATH-500 pass rate, AIME 2024, GPQA science reasoning, native code execution for numerical work, and API price.

ModelMATH-500AIME 2024GPQACode ExecInput / Output $/M
o3~96%96.7%94%Via tools$10 / $40
o4-mini~93%~93%60%Via tools$1.10 / $4.40
DeepSeek R197.3%~79.8%72%No$0.55 / $2.19
Gemini 2.5 Pro~90.5%~85%74%Native$1.25 / $10
Claude Opus 4~83%~70%83.1%Via tools$15 / $75
GPT-4o76.6%~40%53.6%Native$2.50 / $10

Benchmark scores current as of April 13, 2026. MATH-500 is a 500-problem subset of the Hendrycks MATH benchmark.

The Right Math LLM for Your Use Case

Best for Competition Math (AIME/Olympiad)

o3

Gold-medal level performance on IMO 2024 problems and 96.7% on AIME 2024 — the first LLM to solve competition math at the level of elite human competitors.

Best Budget Math LLM

DeepSeek R1

97.3% on MATH-500 at $0.55/$2.19 per million tokens — the most math performance per dollar of any model. MIT-licensed for self-hosting on a single H100.

Best for Applied Math + Code

Gemini 2.5 Pro

Strong MATH benchmark scores combined with native code execution — the best combination for numerical analysis, optimization problems, and applied statistics where you need to run the computation.

Best Cost-Efficient Reasoning

o4-mini

~93% on MATH-500 at $1.10/$4.40 per million tokens — significantly cheaper than o3 with only slightly lower math performance. The sweet spot for high-volume math applications.

Best for Graduate-Level STEM

Claude Opus 4

Leads GPQA at 83.1% — the graduate-level science reasoning benchmark covering physics, chemistry, and biology. Better at multi-disciplinary STEM reasoning than pure math-focused models.

Frequently Asked — Best LLM for Math

Which LLM is best for math in 2026?
o3 is the best LLM for math in 2026 — it achieves a gold-medal level performance on IMO 2024 problems and leads AIME 2024 at 96.7%, marking the first time an LLM has genuinely surpassed competition math. DeepSeek R1 is the best open-weight alternative: it matches o3-mini on MATH-500 (97.3%) at a fraction of the cost and is MIT-licensed for self-hosting.
Can ChatGPT solve math problems?
GPT-4o solves most undergraduate-level math problems reliably, scoring 76.6% on the MATH benchmark (competition-level problems). For basic calculus, algebra, statistics, and probability, GPT-4o is more than sufficient. For competition math (AMC, AIME, Olympiad level), you need a reasoning model: o3, o4-mini, or DeepSeek R1. For applied math and numerical computation, GPT-4o with Code Interpreter is the strongest because it can run Python/numpy and verify results.
What is the MATH benchmark and which LLM leads?
The MATH benchmark (Hendrycks et al.) contains 12,500 competition mathematics problems across 7 difficulty levels — from basic algebra to Olympiad-level proofs. MATH-500 is a 500-problem subset used for faster evaluation. As of 2026: o3 leads at ~96%, DeepSeek R1 at 97.3% on MATH-500, o4-mini at ~93%, and Gemini 2.5 Pro at ~90.5%. GPT-4o scores 76.6% — strong for its class but below reasoning-specialist models.
What is the best LLM for calculus?
For symbolic calculus (derivatives, integrals, series), o3 and o4-mini are the strongest — they reason through multi-step problems reliably. For applied calculus with numerical computation, GPT-4o with Code Interpreter is the best choice because it can run SymPy, SciPy, and verify answers computationally. DeepSeek R1 is the best budget option for calculus at $0.55/$2.19/M tokens.
What is AIME and which LLM scores best?
AIME (American Invitational Mathematics Examination) is a 15-problem competition for top US high school students. It's widely used as a difficult LLM math benchmark because problems require chained multi-step reasoning without multiple-choice guessing. AIME 2024 scores: o3 at 96.7%, DeepSeek R1 at ~79.8%, o4-mini at ~93%, Gemini 2.5 Pro at ~85%. GPT-4o scores around 40%, which is why reasoning models (o-series, R1) matter for hard math.
Is DeepSeek R1 better than GPT-4 at math?
Yes — DeepSeek R1 significantly outperforms GPT-4o on math benchmarks. DeepSeek R1 scores 97.3% on MATH-500 vs GPT-4o's ~78%. It matches or beats o3-mini on most math tasks at a fraction of the cost ($0.55/$2.19 vs $1.10/$4.40 for o4-mini). The key advantage of o3 and o4-mini over DeepSeek R1 is reliability and consistency — DeepSeek R1 can fail on problems it should solve, while o3 is more stable.
Which LLM is best for statistics and probability?
For applied statistics and probability theory, GPT-4o with Code Interpreter is the most complete option — it runs Python, fits distributions, performs hypothesis tests, and interprets results in plain language. For pure theoretical statistics (proofs, derivations), o3 or o4-mini is stronger. Claude Sonnet 4 writes the clearest statistical explanations and is best for turning analysis results into interpretable reports.

See Also

#1o3
OpenAI
ELO 1340
Input

$10.00/M

Output

$40.00/M

JSON ModeFunctionsCode Exec
#2o4-mini
OpenAI
ELO 1260
Input

$1.10/M

Output

$4.40/M

JSON ModeFunctions
#3DeepSeek R1
DeepSeek
ELO 1310
Input

$0.700/M

Output

$2.50/M

JSON Mode
#4Gemini 2.5 Pro
Google
ELO 1430
Input

$1.25/M

Output

$10.00/M

VisionJSON ModeFunctionsMultimodalCode Exec
#5Claude Opus 4
Anthropic
ELO 1504
Input

$5.00/M

Output

$25.00/M

VisionJSON ModeFunctionsMultimodal
#6GPT-4o
OpenAI
ELO 1260
Input

$2.50/M

Output

$10.00/M

VisionJSON ModeFunctionsMultimodalCode Exec

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