Seven of fourteen models named Pave first on the direct prompt; zero named Deel. Pave was named by fourteen of the fourteen models and Deel by nine and Pave carries 40 labels and Deel 13, so the shares are not directly comparable.
Named in five categories this edition.
Named in fifteen 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 compensation 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 4.20 | ||||||
| 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.
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Three of three in this category shown.
“Pave for benchmarking if you're outside its core tech/startup niche” DeepSeek V4 Flash · negative prompt · soft negative
“Choose a Modern Tech Platform (Pave, Comprehensive, Barley) if: You are a high-growth or tech company where equity is a significant portion of total rewards.” Gemini 3.5 Flash · comparative prompt · first choice
“Pave is frequently cited as the top choice for mid-market companies that need to unify both sales commissions and corporate compensation” Qwen 3.7 Flash · direct prompt · first choice
No label in this category carried a quote.
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.