GB/T-Bench - Diagnosis Recall - Terminology: leaderboard

GB/T-Bench (arXiv 2608.06312v1): review of 488 Chinese national standard documents seeded with 7,306 errors across 25 error types, by direct LLM review without the authors' multi-agent reviewer. Exact diagnosis recall for errors in the terminology review dimension, where defined terms and their use must align, percent (Table 3). Higher is better.

Metric: Diagnosis recall (%; exact section, dimension and error-type match). Source: arxiv.org. Saturation forecast: Around 2035. 14 models tracked.

Top models

#ModelScoreOverall rank
1Gemini 3.5 Flash25.97#66
2GPT-5.4 Mini25.4#228
3Claude Fable 524.77#20
4GPT-5.6 Sol22.94#22
5Qwen 3.7 Plus21.68#98
6GPT-5.320.15#104
7Qwen 3 235B A22B 2507 Instruct19.34#315
8GPT-5.519.09#33
9DeepSeek V4 Pro18.2#112
10Qwen 2.5 VL 72B Instruct18.2#383
11GPT-5.417.72#83
12DeepSeek V4 Flash16.26#155
13Claude Opus 4.813.19#39
14MiniMax-M2.711.97#270

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

Interactive version: theaggregate.ai/benchmark?slug=gb-t-bench-diagnosis-recall-terminology · How It Works · Data refreshed daily, snapshot 2026-11-05.