Two of twelve models named Culture Amp first on the direct prompt; zero named PerformYard. Culture Amp was named by twelve of the twelve models and PerformYard by ten and Culture Amp carries 41 labels and PerformYard 18, so the shares are not directly comparable.
Named in ten categories this edition.
Named in three 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 360 feedback 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.
“platforms (like Lattice or Culture Amp) require expensive annual minimum contracts that cost thousands of dollars upfront” Gemini 3.5 Flash · budget 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.
“many tools (Effy AI, Primalogik, PerformYard, 15Five, Lattice) charge for every employee” DeepSeek V4 Flash · negative prompt · soft negative
“I'd generally recommend PerformYard first if you want a dedicated, mid-market-friendly multi-rater feedback / 360 review tool” Perplexity Sonar · 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.