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Summary
Kimi K2.6 from Moonshot AI scored 56.7 on AIME 2025, placing it rank 64 of 140 on this benchmark. This places the model in the below-frontier band for AIME 2025. Acceptable for cost-sensitive workloads or as part of a multi-model ensemble. Not a default choice for high-stakes routing.
Model details
- Provider: Moonshot AI
- Model key:
moonshot/kimi-k2.6 - Context length: 256,000 tokens
- License: Apache 2.0
- Open weights: yes
Benchmark methodology
Benchmark goal: The benchmark is designed to evaluate single-shot problem-solving capabilities in advanced mathematics. The intended use case or domain is competitive mathematics problem-solving.
Scoring metrics:
- Accuracy: A model receives credit only if it produces the exact three-digit integer answer for a problem. Accuracy = (Number of Problems with Exact Three-Digit Integer Answer / Total Problems) * 100
Analysis
Key takeaways:
- Kimi K2.6 achieved an accuracy of 36.67% on the AIME 2025 benchmark, correctly solving 11 out of 30 problems.
- The model performs well on problems testable through algebraic manipulation, elementary number theory, and straight-forward combinatorial counts.
- Performance degrades significantly on geometry problems requiring complex spatial reasoning, problems involving advanced calculus concepts, and intricate combinatorial graph problems.
- A notable strength is the consistent formatting of answers as per the strict guidelines, even in cases of incorrect solutions.
Failure modes observed
Common failure modes:
- Incorrect application of geometric formulas or missing steps in complex multi-part geometry problems.
- Errors in combinatorial counting, often overlooking specific constraints or miscalculating factorials/combinations.
- Inability to derive or correctly interpret equations for complex functions or geometric transformations.
- Arithmetic errors in the final calculation, even when the setup is mostly correct.
Example: In the question involving a heptagon AFNBCEM, the model correctly identifies proportional relationships and areas of similar triangles but does not proceed to calculate the area of the heptagon, indicating an incomplete solution.
Secondary metrics
- Failed prompts: 10
- Readability score: 0.0
- Toxicity score: 0.000
- Ethics score: 0.000
Run this evaluation yourself
LayerLens evaluates Kimi K2.6 continuously across 11+ benchmarks. To replicate this AIME 2025 evaluation on your own model, traces, or a different benchmark configuration, open the model in $LayerLens/$.
_Source: LayerLens evaluation 69e6bcec47d119d2a25bbf30. Updated 2026-04-21._