HELM TORR - Qtsumm - Robustness: leaderboard

HELM ToRR (release v1.0.0) robustness on QTSumm (query-focused summarization of tables; 52 instances): per instance, 1 minus the spread between the best and worst ROUGE-L across 35 prompt configurations (7 table serializations x original, row-shuffled, column-shuffled, transposed and padded tables), averaged. 0-100, higher is more consistent; a model that fails every configuration also scores high.

Metric: Robustness (0-100). Source: crfm.stanford.edu. Saturation forecast: Estimated already saturated. 14 models tracked.

Top models

#ModelScoreOverall rank
1GPT-4o (2024-11-20)79.31#392
2Claude 3.5 Sonnet (20241022)78.96#302
3GPT-4o Mini (2024-07-18)78.71#568
4Qwen 2 72B Instruct77.49#579
5DeepSeek V377.42#329
6Claude 3.5 Haiku (20241022)76.93#590
7Llama 3.1 70B Instruct75.39#567
8Gemini 1.5 Pro (002)73.47#368
9Llama 3.1 405B Instruct72.85#470
10Mistral 7B Instruct (v0.3)72.09#1255
11Mixtral 8x22B Instruct71.65#738
12Mixtral 8x7B Instruct66.1#1085
13Llama 3.1 8B Instruct65.76#1017
14Gemini 1.5 Flash (002)60.32#587

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

Interactive version: theaggregate.ai/benchmark?slug=helm-torr-qtsumm-robustness · How It Works · Data refreshed daily, snapshot 2026-11-05.