Two of twelve models named HiBob first on the direct prompt; two named ChartHop. HiBob was named by twelve of the twelve models and ChartHop by nine and HiBob carries 22 labels and ChartHop 29, so the shares are not directly comparable.
Named in sixteen categories this edition.
Named in seven categories this edition.
Share is the count of first choices across the direct, paraphrase, budget and scale prompts over all twelve models, for a mid-market B2B company; rank is within the category; every quote names the model and the prompt it came from. Both figures come from the people analytics page.
| Model | Direct | Paraphrase | Comparative | Budget-constrained | Scale-constrained | Negative |
|---|---|---|---|---|---|---|
| Claude Haiku 4.5 | ||||||
| GPT-5.4 mini | ||||||
| Gemini 3.5 Flash | ||||||
| Perplexity Sonar | ||||||
| Grok 4.1 Fast | ||||||
| Mistral Small | ||||||
| DeepSeek V4 Flash | ||||||
| Llama 4 Maverick | ||||||
| Qwen 3.7 Flash | ||||||
| Kimi K2 | ||||||
| GLM 4.7 FlashX | ||||||
| MiniMax M2.5 |
Bold names in an answer are the products the judge labeled a first choice; a model naming several gives each of them that label. The full answer text for every row is in the record.
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. One of one in this category shown.
“HiBob is designed for fast-growing mid-market companies (typically 50–2,000 employees) that want an all-in-one HRIS with embedded people analytics” Claude Haiku 4.5 · direct prompt · first choice
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Two of two in this category shown.
“avoid it if your main goal is engagement analytics, sentiment analysis, or performance management” Perplexity Sonar · negative prompt · hard negative
“*Warning:* While the entry cost is low, ChartHop is highly modular... which can quickly drive up the price.” Gemini 3.5 Flash · budget prompt · soft negative
Comparisons are drawn for the top eight products in each category, each against each. The output is the models' output; nothing here is a recommendation by the index.