FinRiskAtlas - Applied Review - Legal-Judgment Generation: leaderboard

Open-ended FinRiskAtlas review generation: writing a reasoned legal analysis supporting a disposition, scored by a fixed semantic rubric for correctness, coverage and evidence use with DeepSeek-V4-Flash as evaluator (FinRiskAtlas, arXiv 2608.25325v1, Appendix Table 10). Percent; higher is better. The evaluator's own self-scored row is excluded, as in the paper's comparisons.

Metric: Rubric Score (%; DeepSeek-V4-Flash judge). Source: arxiv.org. Saturation forecast: Around 2031. 32 models tracked.

Top models

#ModelScoreOverall rank
1GPT-5.446.36#83
2Gemini 2.5 Flash45.29#255
3GPT-5.6 Sol42.09#22
4GPT-5.6 Luna41.7#79
5GPT-5.6 Terra40.98#40
6Gemini 3 Flash (Preview)40.48#90
7Ling-2.6-1T40.27#307
8GPT-5.4 Mini39.86#228
9Qwen 3 235B A22B39.26#323
10DeepSeek V3 (0324)36.26#349
11Qwen 3.7 Max36.22#85
12Claude Opus 4.735.53#51
13Kimi K335.05#35
14Qwen 3 14B35.02#542
15Qwen 3 32B34.54#449

No result here: #3 Claude Opus 5.5, #6 GPT-6 Astra, #7 GPT-6.1 Sol.

Interactive version: theaggregate.ai/benchmark?slug=finriskatlas-applied-review-legal-judgment-generation · How It Works · Data refreshed daily, snapshot 2026-11-05.