Four of fourteen models named Leapsome first on the direct prompt; one named PerformYard. Leapsome was named by fourteen of the fourteen models and PerformYard by twelve and Leapsome carries 42 labels and PerformYard 20, so the shares are not directly comparable.
Named in twelve 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 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 360 feedback page.
Across every category in the October 2026 Edition, Leapsome and PerformYard were named in the same answer sixty-eight times, of the 309 answers naming Leapsome and the 151 naming PerformYard. In those answers PerformYard took the first choice six times and Leapsome six.
| 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. Two of two in this category shown.
“I'd start with PerformYard because it tends to be the least complicated path to a clean 360 process.” GPT-5.4 mini · paraphrase prompt · first choice
“my default pick is PerformYard” GPT-5.4 mini · direct 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.