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AI BENCHY Category Failures

Data parsing and extraction: Wrong answer

Data parsing and extraction
Wrong answer

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

Models Shown

15

Total Failures

35

Most Affected Model

Granite 4.1 8B 2
Rank Model Company Wrong answer Count Category Score Tests Correct Response Time (avg)
#163 Granite 4.1 8B none IBM Granite 2 3.0 0/2 575ms
#155 Mercury 2 none Inception 1 7.3 1/2 667ms
#160 LFM2-24B-A2B none Liquid 2 3.0 0/2 714ms
#136 Elephant Alpha medium Openrouter 1 6.5 1/2 979ms
#137 Elephant Alpha none Openrouter 1 6.5 1/2 1.04s
#81 Mercury 2 medium Inception 1 7.3 1/2 1.11s
#148 GPT-5.4 Nano none OpenAI 1 6.5 1/2 1.11s
#140 Qwen3 Coder Next none Qwen 1 6.5 1/2 1.32s
#162 Nemotron 3 Nano Omni 30b A3b Reasoning none NVIDIA 2 3.8 0/2 1.42s
#68 Claude Opus 4.8 none Anthropic 1 7.3 1/2 1.77s
#99 gpt-oss-120b medium OpenAI 1 6.4 1/2 1.98s
#118 Qwen3.6 27B none Qwen 1 7.3 1/2 2.06s
#57 Step 3.7 Flash low Stepfun 1 7.3 1/2 2.29s
#149 Nemotron 3 Nano Omni 30b A3b Reasoning medium NVIDIA 1 7.3 1/2 2.72s
#122 GLM 4.7 Flash none Z.ai 1 7.3 1/2 4.82s

Top Models by Wrong answer Count

Wrong answer Count vs Score

Top Models by Response Time (avg)

Top Models by Estimated Wasted Cost