IndicBankBench - Bad Tool Response: leaderboard

The bad-tool-response axis of IndicBankBench (Paul et al., 2026): 36 retail-banking cases in which a tool returns a misleading or failed result. Percentage of cases passed in all three runs (strict pass^3), under deterministic safety and tool-use checks and a GLM-5.2 response judge; higher is better.

Metric: Strict pass^3 (%; 36 cases passed out of the 36 cases of the bad-tool-response axis (misleading or failed tool results); each case run three times at temperature 0.7 with the stated reasoning modes; a case passes only when all three runs pass the deterministic safety and tool-use gates and the GLM-5.2 response judge; scripted Indian retail-banking conversations over deterministic mock tools). Source: arxiv.org. Saturation forecast: Around January 2028. 11 models tracked.

Top models

#ModelScoreOverall rank
1Grok 4.6 (High)69.44#44 (Grok 4.6)
2DeepSeek V4 Pro (0813) (Max)66.67#81 (DeepSeek V4 Pro (0813))
3DeepSeek V4 Flash (0731) (Max)63.89#136 (DeepSeek V4 Flash (0731))
4Claude Opus 5 (Max)61.11#20 (Claude Opus 5)
5GLM-5.3 Flash (High)61.11#119 (GLM-5.3 Flash)
6Gemma 4 31B (IT) (Thinking)58.33#343 (Gemma 4 31B (IT))
7MiniMax-M350#265
8Gemma 4 E4B (IT) (Thinking)47.22
9gemma-4-26B-A4B-it (Thinking)38.89
10Gemini 3.8 Flash36.11#36

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

Interactive version: theaggregate.ai/benchmark?slug=indicbankbench-bad-tool-response · How It Works · Data refreshed daily, snapshot 2026-11-12.