Seven of twelve models named Happeo first on the direct prompt; zero named Connecteam. Happeo was named by eleven of the twelve models and Connecteam by ten and Happeo carries 21 labels and Connecteam 14, so the shares are not directly comparable.
Named in two categories this edition.
Named in seventeen 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 internal communications and intranet 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. Four of five in this category shown.
“Happeo is less compelling outside Google Workspace environments” Claude Haiku 4.5 · negative prompt · soft negative
“Happeo - a best overall intranet platform for small and mid-sized companies, with fast setup, a search and knowledge layer” Llama 4 Maverick · direct prompt · first choice
“Happeo is the strongest default recommendation when your company already uses Google Workspace” Perplexity Sonar · direct prompt · first choice
“recommend platforms like Simpplr, Happeo, MangoApps, or Workvivo as strong fits” MiniMax M2.5 · scale 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.