Five of twelve models named Rippling first on the direct prompt; zero named Day Off. Rippling was named by eleven of the twelve models and Day Off by six and Rippling carries 27 labels and Day Off 12, so the shares are not directly comparable.
Named in twenty-eight categories this edition.
Named in one category 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 leave and absence management 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.
“Multiple reviews strongly caution against it for non-US / India-based teams” DeepSeek V4 Flash · negative prompt · hard negative
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Three of four in this category shown.
“Absolute lowest cost | Vacation Tracker ($2/user) or Day Off (free up to 10)” GLM 4.7 FlashX · budget prompt · first choice
“Also mentioned as solid, budget-friendly options for smaller businesses” Mistral Small · budget prompt · alternative
“Day Off (Great Free Alternative for Tiny Teams)” Grok 4.1 Fast · budget prompt · alternative
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.