reasoning benchmark
AA Intelligence Index v4.3 is Version 4.3 of the Artificial Analysis Intelligence Index, with scores stored as fractions of 100.
Updated Sep 24, 2026
Higher score ranks better on this benchmark.
Rank | Model | Score | Percentile | Participants | Evidence | Evaluated |
|---|
| Rank01 | ModelXI | Score46.32% | Percentile100.00% | Participants1 | EvidenceC | Evaluated |
The leading models and scores on this benchmark.
The first five results on this benchmark, with official price and output speed added where the model identity can be matched.
Ranking basisThis aa intelligence index v4.3 AI model leaderboard uses descending score in the benchmark original unit. The leaderboard ranking keeps matched price and speed data separate from benchmark evidence.
Selection summary
MiMo-V2.6-Pro currently leads AA Intelligence Index v4.3 with 46.32%. It is the top model on this specific benchmark, while the best LLM for the broader task should also be checked against other benchmarks, price, and runtime.
Use this leaderboard with the supporting benchmark results and coverage details above. A leaderboard position summarizes the selected ranking signal; it does not replace workload-specific testing.
What AA Intelligence Index v4.3 measures and how its scores work.
AA Intelligence Index v4.3 is Version 4.3 of the Artificial Analysis Intelligence Index.
It reports a Score for the reasoning category, stored as a fraction of 100.
Scores are shown in ratio. This benchmark is not independently verified and has an evidence level of B.
LLM Stats. Benchmark scores retain their original unit. Overall score eligibility is shown separately.
Common questions about AA Intelligence Index v4.3.
MiMo-V2.6-Pro is currently ranked first with 46.32%.
The current leaders are MiMo-V2.6-Pro (46.32%).
MiMo-V2.6-Pro has the lowest matched official input price at $0.44 input / $0.87 output per 1M tokens.
The fastest matched records are MiMo-V2.6-Pro (11.79 tok/s via Xiaomi).
No. This benchmark measures one defined capability or task. The overall LLMBoard score uses a separate aggregation across eligible benchmark evidence.
It reports a Score for the reasoning category, stored as a fraction of 100.
Yes. Higher values rank better for this benchmark.
1 model results are currently shown.
No. This benchmark is shown for reference but does not contribute to the overall score.