reasoning benchmark
FinSearchComp T2&T3 is a combined benchmark for evaluating financial search and reasoning on Tier 2 and Tier 3 tasks.
Updated Sep 5, 2026
Higher score ranks better on this benchmark.
Rank | Model | Score | Percentile | Participants | Evidence | Evaluated |
|---|
| Rank01 | ModelMA | Score67.80% | 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 finsearchcomp t2&t3 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
Kimi K2.5 currently leads FinSearchComp T2&T3 with 67.80%. 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 FinSearchComp T2&T3 measures and how its scores work.
FinSearchComp T2&T3 is a reasoning benchmark covering financial search and reasoning tasks across Tier 2 and Tier 3.
It measures models' ability to retrieve and analyze complex financial information using tools, with 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.
LLM Stats. Benchmark scores retain their original unit. Overall score eligibility is shown separately.
Common questions about FinSearchComp T2&T3.
Kimi K2.5 is currently ranked first with 67.80%.
The current leaders are Kimi K2.5 (67.80%).
No matched official input price is currently available.
No matched runtime record is currently available.
No. This benchmark measures one defined capability or task. The overall LLMBoard score uses a separate aggregation across eligible benchmark evidence.
It measures models' ability to retrieve and analyze complex financial information using tools, with the Score metric reported as a ratio.
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.