Three of fourteen models named CaptivateIQ first on the direct prompt; one named Paycom. CaptivateIQ was named by eleven of the fourteen models and Paycom by nine and CaptivateIQ carries 18 labels and Paycom 17, so the shares are not directly comparable.
Named in two categories this edition.
Named in fourteen 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 4.1 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.
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Four of five in this category shown.
“most commission tools (like Spiff or CaptivateIQ) are prohibitively expensive for tight budgets” Gemini 3.5 Flash · budget prompt · soft negative
“CaptivateIQ is built for finance/comp admins who think in spreadsheets and need to model plan changes before rollout” Kimi K2 · comparative prompt · first choice
“CaptivateIQ (Best for Complex Plan Logic) ... The "industry standard" for mid-market to enterprise B2B teams” Gemini 3.5 Flash · direct prompt · first choice
“CaptivateIQ is my best default pick for a mid-market team” GPT-6 Luna · 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.