math benchmark
AIME Leaderboard
AIME is a math benchmark containing 30 challenging mathematical problems from the AIME 2024 competition, each with an integer answer between 000-999.
Updated Sep 5, 2026
Models2
Model coverage2
MetricScore
EvidenceB
AIME Ranking
Higher score ranks better on this benchmark.
Sort by
Rank | Model | Score | Percentile | Participants | Evidence | Evaluated |
|---|
| Rank01 | ModelMI | Score57.50% | Percentile100.00% | Participants2 | EvidenceC | Evaluated |
| Rank02 | ModelXI | Score37.30% | Percentile0.00% | Participants2 | EvidenceC | Evaluated |
AIME Highlights
The leading models and scores on this benchmark.
AIME Score Distribution
A closer view of the leading scores on this benchmark.
The Top AI Models for AIME
The first five results on this benchmark, with official price and output speed added where the model identity can be matched.
What is AIME?
What AIME measures and how its scores work.
AIME is the American Invitational Mathematics Examination benchmark for evaluating large language models on mathematical reasoning.
It measures mathematical reasoning capabilities using the Score metric, reported as a ratio.
Scores are shown in ratio. This benchmark is not independently verified and has an evidence level of B.
- Family
- AIME
- Modality
- text
- Primary category
- math
- Score direction
- higher
- LLMBoard eligible
- No
- Evaluation key
- overall
LLM Stats. Benchmark scores retain their original unit. Overall score eligibility is shown separately.
FAQ
Common questions about AIME.
Which model scores highest on AIME?
Phi 4 Mini Reasoning is currently ranked first with 57.50%.
What are the top three models on AIME?
The current leaders are Phi 4 Mini Reasoning (57.50%) and MiMo-V2.5-Pro (37.30%).
Which AIME model has the lowest official input price?
Phi 4 Mini Reasoning has the lowest matched official input price at $0.08 input / $0.30 output per 1M tokens.
Which models are fastest among AIME results?
The fastest matched records are MiMo-V2.5-Pro (5.27 tok/s via DeepInfra).
Does the highest score result prove overall model quality?
No. This benchmark measures one defined capability or task. The overall LLMBoard score uses a separate aggregation across eligible benchmark evidence.