Six of fourteen models named Tipalti first on the direct prompt; zero named Corpay Cross-Border Payments. Tipalti was named by twelve of the fourteen models and Corpay Cross-Border Payments by nine and Tipalti carries 18 labels and Corpay Cross-Border Payments 15, so the shares are not directly comparable.
Named in eighteen categories this edition.
Named in one category 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 Cross-border payments and FX 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.
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. Three of four in this category shown.
“I'd generally recommend Corpay if your top priority is a serious FX hedging and international payments platform” GPT-5.4 mini · paraphrase prompt · first choice
“Best Overall for Traditional Mid-Sized Corporates” Gemini 3.5 Flash · paraphrase prompt · first choice
“a platform that enables businesses to make international payments, manage currency risk, and move money globally in over 140 currencies” Llama 4 Maverick · paraphrase prompt · alternative
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.