FinReportBench: leaderboard
Metric: Provisional hierarchical score (0-100): mean over the 244 bilingual report-generation tasks of S = 100 (g1 + (S1/100) g2) / (d1 + d2), where g1, g2 are the weighted rubric points earned on the 4 report-identity (G1) and 27 institutional-completeness (G2) items, d1, d2 the points available and S1 the G1 percentage, and S = 0 when any of the 4 deliverability (G0) preflight checks fails; pass, partial and fail items earn 1, 0.5 and 0; GPT-5.6 Luna at medium reasoning effort judges extracted text and up to four rendered pages against the frozen 35-item rubric; no-skill condition. Source: arxiv.org. Saturation forecast: Around 2032. 9 models tracked.
Top models
| # | Model | Score |
|---|---|---|
| 1 | MiniMax-M2.7 | 22.6 |
| 2 | GLM-5.2 | 21.8 |
| 3 | MiniMax-M2.5 | 21.1 |
| 4 | DeepSeek V4 Flash | 20.2 |
| 5 | Qwen 3.7 Max | 19.1 |
| 6 | DeepSeek V4 Pro | 18.8 |
| 7 | MiniMax-M3 | 18.6 |
| 8 | Kimi K2.6 | 17.7 |
| 9 | Qwen 3.6 27B | 15.1 |
Interactive version: theaggregate.ai/benchmark?slug=finreportbench · How It Works · Data refreshed daily, snapshot 2026-09-29.