Eight of twelve models named Rippling first on the direct prompt; zero named Paycor. Rippling was named by twelve of the twelve models and Paycor by eight and Rippling carries 44 labels and Paycor 12, so the shares are not directly comparable.
Named in twenty-eight categories this edition.
Named in sixteen 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 payroll software 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.
“Experts warn against using Rippling if you have fewer than 100 employees, as it is considered overkill and can be very costly for smaller businesses.” Mistral Small · negative prompt · soft negative
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Two of two in this category shown.
“Poor customer support as the top complaint ... Unexpected hidden fees and price increases.” GLM 4.7 FlashX · negative prompt · hard negative
“Paycor - Paycor is an HCM software provider designed for mid-market and enterprise organizations” Claude Haiku 4.5 · paraphrase prompt · first choice
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.