Finance AI Index
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Cross-border payments and FX · September 2026 Edition

Corpay Cross-Border vs Thunes

Zero of twelve models named Corpay Cross-Border first on the direct prompt; one named Thunes. Corpay Cross-Border was named by eleven of the twelve models and Thunes by eight and Corpay Cross-Border carries 16 labels and Thunes 13, so the shares are not directly comparable.

Corpay Cross-Border

accepted challenger

Named in one category this edition.

Thunes

accepted challenger

Named in one category this edition.

First-choice share7%2%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate0%0%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#3#5A position in a field of 11; printed, not drawn.
Labels1613A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, Corpay Cross-Border reading right to left. Rank and label count are printed, not drawn.Wise Business was named alongside these two in eleven of the twelve direct answers. Wise Business vs Corpay Cross-Border · Wise Business vs Thunes · Airwallex vs Corpay Cross-Border

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 Cross-border payments and FX page.

By framing

How many of the twelve models made each the first choice, per way of asking, and how many argued against it.
Corpay Cross-BorderFirst choices, of twelve modelsThunes
Direct01
Paraphrase30
Comparative02
Budget-constrained00
Scale-constrained00
Negative00
Bars are first choices, 0 to 12 each sideModels that argued againstA model can name both, so the two sides of a row do not sum to twelve.

Every model, every framing

The seventy-two answers behind the chart above, one cell each: where Corpay Cross-Border and Thunes stood in it.
ModelDirectParaphraseComparativeBudget-constrainedScale-constrainedNegative
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
Corpay Cross-Border Thunes first choice named as an alternative argued againstblank: not namedEach cell is one answer, Corpay Cross-Border on the left and Thunes on the right.

The direct prompt

The plain question, one answer per model, grouped by where Corpay Cross-Border and Thunes stood in it.

Thunes first, Corpay Cross-Border not the choice

1 of 12 modelsCorpay Cross-Border was named in the answer but not as the choice, or not at all.
Mistral SmallThunes, Wise Business alternatives: Airwallex, Nium

Neither was the first choice, one was named

6 of 12 modelsThe answer put something else first and named one of the two as an alternative.
Claude Haiku 4.5Wise Business alternatives: Thunes, Tipalti
Gemini 3.5 FlashAirwallex alternatives: Convera, Corpay Cross-Border, Tipalti, TransferMate, Wise Business
Grok 4.1 FastAirwallex, Wise Business alternatives: Nium, Rapyd, Stripe Treasury, Thunes, Tipalti
Kimi K2Airwallex alternatives: Corpay Cross-Border, Tipalti, Wise Business
GLM 4.7 FlashXAirwallex alternatives: Banking Circle, Cedar Money, PhotonPay, Stripe, Thunes, Tipalti, Wise Business
MiniMax M2.5Airwallex alternatives: Stripe, Thunes, Wise Business

Neither was named

5 of 12 modelsThe answer made no first choice from these two in this category.
GPT-5.4 miniAirwallex alternatives: Payoneer, Stripe, Wise Business
Perplexity SonarAirwallex, Tipalti alternatives: Currencycloud, Payoneer, Stripe, Wise Business
DeepSeek V4 FlashAirwallex alternatives: Convera, OFX, Tipalti, Wise Business
Llama 4 Maverickno first choice
Qwen 3.7 FlashAirwallex, Wise Business alternatives: Currencycloud, Revolut Business

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

The same question asked on behalf of a different buyer. Each standing is computed within its segment and they are never added together. The figures above are the mid-market standing, which is the one the category orders by.
Small business
Corpay Cross-Border leads by five points.
Corpay Cross-Border5%#– of 8
Thunes0%#7 of 8
The full small business standing →
Mid-marketThe figures above
Corpay Cross-Border leads by four points.
Corpay Cross-Border7%#3 of 11
Thunes2%#5 of 11
The full mid-market standing →
Enterprise
The order flips: Thunes leads at enterprise.
Thunes22%#1 of 12
Corpay Cross-Border8%#5 of 12
The full enterprise standing →

What the models said about Corpay Cross-Border

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 Cross-Border if your priority is both FX hedging and international payments in one platform” GPT-5.4 mini · paraphrase prompt · first choice
“Recommendation: Corpay Cross-Border (or OFX)” Qwen 3.7 Flash · paraphrase prompt · first choice
“I'd suggest starting with Kantox or Corpay” MiniMax M2.5 · paraphrase prompt · first choice

What the models said about Thunes

Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Three of four in this category shown.

“Thunes: Best overall for global B2B payouts at scale, covering 140+ countries and 90 currencies.” Mistral Small · comparative prompt · first choice
“Thunes is considered the best overall for global B2B payouts” Mistral Small · direct prompt · first choice
“Thunes (Best for Enterprise & Infrastructure)” Qwen 3.7 Flash · comparative prompt · first choice
Also compared
Wise Business vs Corpay Cross-BorderWise Business vs ThunesAirwallex vs Corpay Cross-BorderAirwallex vs ThunesCorpay Cross-Border vs OFXCorpay Cross-Border vs TipaltiOFX vs ThunesThunes vs TipaltiAll fifteen head-to-head pages and the full cross-border payments standing

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.