HG-Bench: leaderboard

HG-Bench (2026) tests page-aware answer-region grounding in multi-page handwritten K-12 homework: over 500 human-annotated samples, a vision-language model must box each complete answer region and its ordered step regions. This board is the step-level micro F1 scaled to 0-100, pooling step-box matches over all pages that contain gold steps, the metric the authors rank by; higher is better.

Metric: Step-level micro F1 (0-100), the paper's ranking metric: step-box true and false positives and false negatives pooled over all pages that have gold step boxes; 500 human-annotated multi-page handwritten K-12 homework samples; the model outputs page-aware question-level answer boxes and ordered step boxes as JSON with normalized 0-1000 coordinates, one shared prompt, default decoding, one format-reminder retry; higher is better. Source: arxiv.org. Saturation forecast: Around February 2027. 9 models tracked.

Top models

#ModelScoreOverall rank
1Gemini 3 Pro (Preview)48.22#113
2GLM-5V Turbo26.29#344
3Qwen 3.5 397B A17B18.15#246
4Kimi K2.57.42#256
5Claude Sonnet 4.61.63#161
6GPT-5.41.55#123

No result here: #1 Claude Fable 5.2, #2 Gemini 4 Carbon, #5 Claude Opus 5.5.

Interactive version: theaggregate.ai/benchmark?slug=hg-bench · How It Works · Data refreshed daily, snapshot 2026-11-13.