Mondu vs Fundbox
One of fourteen models named Mondu first on the direct prompt; one named Fundbox. Mondu was named by thirteen of the fourteen models and Fundbox by nine and Mondu carries 32 labels and Fundbox 14, 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 B2B BNPL and net terms page.
By framing
MonduFirst choices, of fourteen modelsFundbox
Across every category in the October 2026 Edition, Mondu and Fundbox were named in the same answer sixteen times, of the 76 answers naming Mondu and the 39 naming Fundbox. In those answers Fundbox took the first choice one time and Mondu one.
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 | | | |
Mondu Fundbox first choice named as an alternative argued againstblank: not namedEach cell is one answer, Mondu on the left and Fundbox on the right.The direct prompt
Mondu first, Fundbox an alternative
1 of 14 modelsFundbox was named in the answer but not as the choice, or not at all.Fundbox first, Mondu not the choice
1 of 14 modelsMondu was named in the answer but not as the choice, or not at all.Neither was the first choice, one was named
6 of 14 modelsThe answer put something else first and named one of the two as an alternative.Neither was named
6 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
Mondu2%#5 of 12Fundbox2%#7 of 12Mondu3%#3 of 9Fundbox0%#– of 9What the models said about Mondu
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Four of five in this category shown.
“Aggressive collections automation (Mondu being the most flagged)” DeepSeek V4 Flash · negative prompt · soft negative
“Prioritize providers with strong Trustpilot scores (4.5+), EMI licensing, ISO 27001, and non-recourse models: e.g., Mondu (generally positive)” Grok 4.1 Fast · negative prompt · first choice
“Mondu and Billie are the top choices due to their B2B specialization and flexibility” Mistral Small · direct prompt · first choice
“Choose Mondu if you want a broader European pay-later stack with multiple buyer payment modes.” GPT-5.4 mini · comparative prompt · alternative
What the models said about Fundbox
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Five of six in this category shown.
“Generally not recommended for mid-market due to very high APRs (80–240%+) and limited AR automation” Kimi K2 · direct prompt · hard negative
“BBB complaint summary: 26 total complaints in the last 3 years... frustrations regarding unexpected automated payment system glitches and sudden strict restrictions on new credit line draws” Muse Glimmer 30B · negative prompt · soft negative
“Start with Resolve or Fundbox.” Qwen 3.7 Flash · direct prompt · first choice
“more of an embedded financing / capital platform, but it can power net terms and installment options in B2B commerce” GPT-5.4 mini · comparative prompt · alternative
“Fundbox offers robust B2B purchasing credits and Net Terms options for vendors” Qwen 3.7 Flash · comparative 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.