FinED-Bench: leaderboard
Metric: F1 (%; harmonic mean of pooled precision and recall over all injected errors in 973 Chinese financial documents from 2025, nine real-world scenarios; a predicted error counts as correct when the extracted sentence matches or contains the annotated sentence and the error type is classified correctly; the paper's error-detection prompt over each document, reasoning models with thinking on unless marked no thinking). Source: arxiv.org. Saturation forecast: Estimated already saturated. 11 models tracked.
Top models
| # | Model | Score |
|---|---|---|
| 1 | GPT-4o | 48.34 |
| 2 | Qwen 3 14B | 43.15 |
| 3 | Qwen 3 8B | 39.99 |
| 4 | Qwen 3 14B (Non-reasoning) | 27.19 |
| 5 | DeepSeek R1 0528 Qwen3 8B | 23.31 |
| 6 | GPT-4o Mini | 18.9 |
| 7 | Qwen 3 8B (Non-reasoning) | 17.44 |
| 8 | Qwen 2.5 7B Instruct | 9.85 |
| 9 | GPT-3.5 Turbo | 7.17 |
Interactive version: theaggregate.ai/benchmark?slug=fined-bench · How It Works · Data refreshed daily, snapshot 2026-09-26.