| Category | Function | Share | Rank | Negative rate | Labels | Quadrant |
|---|---|---|---|---|---|---|
| Technical hiring assessments | Talent acquisition | 0% | 26 of 52 | 0% | 1 | under 10 labels · led by HackerRank at 28% |
| Model | First choice | Alternative | Mention | Negative | Labels |
|---|---|---|---|---|---|
| Claude Haiku 4.5 | 0 | 0 | 0 | 0 | 0 |
| GPT-5.4 mini | 0 | 0 | 0 | 0 | 0 |
| Gemini 3.5 Flash | 0 | 0 | 0 | 0 | 0 |
| Perplexity Sonar | 0 | 0 | 0 | 0 | 0 |
| Grok 4.1 Fast | 0 | 0 | 0 | 0 | 0 |
| Mistral Small | 0 | 1 | 0 | 0 | 1 |
| DeepSeek V4 Flash | 0 | 0 | 0 | 0 | 0 |
| Llama 4 Maverick | 0 | 0 | 0 | 0 | 0 |
| Qwen 3.7 Flash | 0 | 0 | 0 | 0 | 0 |
| Kimi K2 | 0 | 0 | 0 | 0 | 0 |
| GLM 4.7 FlashX | 0 | 0 | 0 | 0 | 0 |
| MiniMax M2.5 | 0 | 0 | 0 | 0 | 0 |
Verbatim evidence the judge attached to positive labels.
“Code Assess AI (for real-world debugging and pre-ATS filtering)” Mistral Small · Technical hiring assessm · negative prompt · alternative
Verbatim evidence attached to negative labels. A warning on a product with few labels is a warning; on a product with many, it is one voice among them.
Citations exist only for the models that return a source list, four of the twelve in this edition, so these counts come from 1 of the 1 answers that named Code Assess AI and are not a share of its labels.
Four of the five domain citations in answers naming Code Assess AI came from somebody else's page.
Pages are listed as the models cited them.
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