Six of twelve models named Rippling first on the direct prompt; zero named Homebase. Rippling was named by ten of the twelve models and Homebase by twelve and Rippling carries 15 labels and Homebase 18, so the shares are not directly comparable.
Named in twenty-eight categories this edition.
Named in eleven 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 time and attendance 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. Two of two in this category shown.
“Rippling has become a dominant force in the mid-market space because of its unified HR, IT, and Finance platform... Rippling is the market leader.” Gemini 3.5 Flash · direct prompt · first choice
“my default recommendation is Rippling if you want the best balance of time & attendance, HR, payroll-adjacent workflows, and scalability” GPT-5.4 mini · direct prompt · first choice
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. One of one in this category shown.
“Limitation: Free version lacks real-time attendance monitoring and time-off tracking” Kimi K2 · 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.