AI BENCHY
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AI BENCHY Category Failures

Domain specific: Wrong answer

Domain specific
Wrong answer

See which AI models are most likely to hit Wrong answer on Domain specific, so you can spot weak points faster. Sort by: Response Time (avg) ↑.

Models Shown

15

Total Failures

314

Most Affected Model

GLM 5 2
Rank Model Company Wrong answer Count Category Score Tests Correct Response Time (avg)
#17 GLM 5 medium Z.ai 2 3.5 0/3 0ms
#52 Claude Sonnet 4.6 medium Anthropic 1 2.9 0/3 0ms
#160 LFM2-24B-A2B none Liquid 1 5.9 1/3 287ms
#163 Granite 4.1 8B none IBM Granite 3 3.0 0/3 357ms
#142 Mistral Small 4 none Mistral 2 5.3 1/3 367ms
#146 Laguna Xs.2 none Poolside 2 5.3 1/3 371ms
#154 Qwen3.5-9B none Qwen 3 3.0 0/3 464ms
#131 Qwen3.5-122B-A10B none Qwen 2 5.3 1/3 465ms
#117 Qwen3.5-35B-A3B none Qwen 1 7.7 2/3 485ms
#162 Nemotron 3 Nano Omni 30b A3b Reasoning none NVIDIA 3 3.6 0/3 489ms
#97 Gemini 2.5 Flash none Google 2 5.9 1/3 495ms
#155 Mercury 2 none Inception 2 5.3 1/3 534ms
#115 Qwen3.5-27B none Qwen 3 3.0 0/3 540ms
#152 MiMo-V2-Flash none Xiaomi 2 5.3 1/3 564ms
#106 Grok 4.20 Beta none X AI 3 3.0 0/3 611ms

Top Models by Wrong answer Count

Wrong answer Count vs Score

Top Models by Response Time (avg)

Top Models by Estimated Wasted Cost