Versapay vs Billtrust
One of fourteen models named Versapay first on the direct prompt; one named Billtrust. Versapay was named by thirteen of the fourteen models and Billtrust by thirteen and Versapay carries 35 labels and Billtrust 42, so the shares are not directly comparable.
Named in seven categories this edition.
Named in nine 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 cash application page.
By framing
VersapayFirst choices, of fourteen modelsBilltrust
Across every category in the October 2026 Edition, Versapay and Billtrust were named in the same answer 135 times, of the 213 answers naming Versapay and the 324 naming Billtrust. In those answers Billtrust took the first choice thirteen times and Versapay sixteen.
Every model, every framing
| 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 | | | | |
Versapay Billtrust first choice named as an alternative argued againstblank: not namedEach cell is one answer, Versapay on the left and Billtrust on the right.The direct prompt
Versapay first, Billtrust not the choice
1 of 14 modelsBilltrust was named in the answer but not as the choice, or not at all.Billtrust first, Versapay not the choice
1 of 14 modelsVersapay was named in the answer but not as the choice, or not at all.Neither was the first choice, one was named
7 of 14 modelsThe answer put something else first and named one of the two as an alternative.Neither was named
5 of 14 modelsThe answer made no first choice from these two in this category.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.
By buyer segment
Versapay0%#11 of 16Billtrust0%#14 of 16Billtrust4%#2 of 8Versapay0%#7 of 8What the models said about Versapay
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Four of four in this category shown.
“"Avoid for Your Criteria - Billtrust, Serrala, Esker, Versapay: Custom/transaction-based"” Muse Glimmer 30B · negative prompt · hard negative
“generally not recommended for smaller businesses or those outside its target scale” Mistral Small · negative prompt · hard negative
“Go with Versapay. Its collaborative portal forces buyers to map payments to invoices directly, cutting out the need for complex manual reconciliation.” Gemini 3.5 Flash · direct prompt · first choice
“VersaPay and Bill.com are the top choices due to their strong matching capabilities, scalability, and integration options.” Mistral Small · paraphrase prompt · first choice
What the models said about Billtrust
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Four of four in this category shown.
“"Avoid for Your Criteria - Billtrust, Serrala, Esker, Versapay: Custom/transaction-based"” Muse Glimmer 30B · negative prompt · hard negative
“The biggest red flags are HighRadius and Billtrust for standard contract terms” DeepSeek V4 Flash · negative prompt · hard negative
“Recommended to negotiate carefully or avoid standard contracts due to high costs” Mistral Small · negative prompt · hard negative
“I'd start with Billtrust. Its cash-application product is specifically focused on bringing together payment and remittance data” GPT-6 Luna · 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.