MedRepBench - Abnormal Flag Recall (OCR Text Only): leaderboard

Structured extraction from photographed, screenshotted and electronic Chinese laboratory reports, by text-only language models given the recognized OCR text; MedRepBench (Shang et al., 2025). Recall in percent of the reference items' abnormality flags, with items matched by normalized name within a budget of as many items as the reference lists; higher is better. Abnormality must be inferred by comparing the value with the range.

Metric: Field-level recall (%; abnormality flag of each ground-truth lab item, matched by exact normalized item name within the model's top-K items, K = number of reference items; text LLM on the OCR text). Source: arxiv.org. Saturation forecast: Estimated already saturated. 12 models tracked.

Top models

#ModelScoreOverall rank
1DeepSeek V389.06#705
2Qwen 3 235B A22B 250788.03#613
3Qwen 3 32B85.77#960
4Qwen 3 14B85.43#1235
5Qwen 3 235B A22B84.54#622
6DeepSeek R1 Distill Qwen 14B83.01#2594
7Qwen 3 30B A3B82.67#1124
8DeepSeek R1 Distill Qwen 32B82.29#1780
9Qwen 3 1.7B69.04#5551
10Qwen 3 8B68.5#1838
11DeepSeek-R1-Distill-Qwen-7B67.13#8045
12Qwen 3 4B64.29#2297

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

Interactive version: theaggregate.ai/benchmark?slug=medrepbench-abnormal-flag-recall-ocr-text-only · How It Works · Data refreshed daily, snapshot 2026-11-12.