IndicBankBench - Wrong Info: leaderboard

The wrong-information axis of IndicBankBench (Paul et al., 2026): 142 retail-banking cases in which the customer states a plausible but incorrect claim that the assistant must check against the records. 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 (%; 142 cases passed out of the 142 cases of the wrong-information axis (plausible but incorrect customer claims); 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 2029. 11 models tracked.

Top models

#ModelScoreOverall rank
1Claude Opus 5 (Max)40.14#20 (Claude Opus 5)
2Gemini 3.8 Flash38.03#36
3GLM-5.3 Flash (High)38.03#119 (GLM-5.3 Flash)
4DeepSeek V4 Flash (0731) (Max)34.51#136 (DeepSeek V4 Flash (0731))
5DeepSeek V4 Pro (0813) (Max)32.39#81 (DeepSeek V4 Pro (0813))
6Grok 4.6 (High)30.28#44 (Grok 4.6)
7MiniMax-M328.87#265
8Gemma 4 31B (IT) (Thinking)28.17#343 (Gemma 4 31B (IT))
9gemma-4-26B-A4B-it (Thinking)25.35
10Gemma 4 E4B (IT) (Thinking)19.01

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

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