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.
Failure Reasons
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| Rank | Model | Company | Wrong answer Count | Category Score | Total Cost | Tests Correct | Response Time (avg) |
|---|---|---|---|---|---|---|---|
| #275 | Nemotron 3.5 Lightning low | NVIDIA | 1 | 2.9 | $0.140 | 0/2 | 31.3s |
| #276 | GPT-5.4 Nano none | OpenAI | 1 | 6.5 | $0.041 | 1/2 | 1.11s |
| #277 | Trinity Large Thinking high | Arcee AI | 1 | 6.3 | $0.592 | 1/2 | 14.0s |
| #280 | GLM 4.7 Flash none | Z.ai | 1 | 7.3 | $0.016 | 1/2 | 4.82s |
| #285 | Cobuddy medium | Baidu | 1 | 6.3 | $0.000 | 1/2 | 17.4s |
| #286 | Mercury 2 none | Inception | 1 | 7.3 | $0.030 | 1/2 | 667ms |
| #287 | Granite 4.2 8B high | IBM Granite | 1 | 3.8 | $0.084 | 0/2 | 56.5s |
| #288 | Qwen3 Coder Next medium | Qwen | 1 | 6.5 | $0.034 | 1/2 | 81.8s |
| #293 | Elephant Alpha none | Openrouter | 1 | 6.5 | $0.000 | 1/2 | 1.04s |
| #295 | Elephant Alpha medium | Openrouter | 1 | 6.5 | $0.000 | 1/2 | 979ms |
| #305 | Grok Build 0.1 none | X AI | 1 | 3.8 | $0.547 | 0/2 | 9.33s |
| #307 | Ling 3.0 Tiny low | Inclusionai | 1 | 2.8 | $0.000 | 0/2 | 4.82s |
| #310 | Ling 3.0 Tiny medium | Inclusionai | 1 | 2.7 | $0.000 | 0/2 | 4.41s |
| #313 | Nemotron 3 Nano Omni 30b A3b Reasoning medium | NVIDIA | 1 | 7.3 | $0.000 | 1/2 | 2.72s |