Six of fourteen models named Rippling first on the direct prompt; zero named Deputy. Rippling was named by twelve of the fourteen models and Deputy by fourteen and Rippling carries 24 labels and Deputy 28, so the shares are not directly comparable.
Named in twenty-nine categories this edition.
Named in ten categories this edition.
Share is the count of first choices across the direct, paraphrase, budget and scale prompts over all fourteen 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 workforce management suites 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 | ||||||
| GPT-6 Luna | ||||||
| Muse Glimmer 30B |
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.
No label in this category carried a quote.
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Three of three in this category shown.
“Small-business / lightweight tools like Homebase, When I Work, Connecteam, Deputy, and similar SMB-first tools” Llama 4 Maverick · negative prompt · hard negative
“Great for very small teams, but they often hit "walls" when trying to integrate with larger ERP or Payroll ecosystems.” Qwen 3.7 Flash · negative prompt · soft negative
“if looking for the strongest all-around fit for a mid-sized operation, I recommend Deputy.” Qwen 3.7 Flash · 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.