Two of fourteen models named Origin first on the direct prompt; zero named Tapcheck. Origin was named by ten of the fourteen models and Tapcheck by seven and Origin carries 16 labels and Tapcheck 10, so the shares are not directly comparable.
Named in one category this edition.
Named in two 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 financial wellness platforms 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. Three of four in this category shown.
“If your B2B company offers variable compensation, sales commissions, or equity (options, RSUs, and ESPPs), Origin is the market leader.” Gemini 3.5 Flash · direct prompt · first choice
“such as LearnLux, Origin, or Brightside) that delivers three high-impact benefits in a single, turn-key software solution” Gemini 3.5 Flash · paraphrase prompt · first choice
“The ultimate "all-in-one" employee financial benefit... Best For: Companies looking for a comprehensive, highly modern tool” Gemini 3.5 Flash · comparative 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.