Ramp vs Expensify
Seven of fourteen models named Ramp first on the direct prompt; two named Expensify. Both were named by all fourteen models and Ramp carries 53 labels and Expensify 64, so the shares are not directly comparable.
Named in seventeen categories this edition.
Named in five 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 expense management page.
By framing
RampFirst choices, of fourteen modelsExpensify
Across every category in the October 2026 Edition, Ramp and Expensify were named in the same answer 202 times, of the 1084 answers naming Ramp and the 256 naming Expensify. In those answers Expensify took the first choice fifteen times and Ramp seventy-six.
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 | | | | |
Ramp Expensify first choice named as an alternative argued againstblank: not namedEach cell is one answer, Ramp on the left and Expensify on the right.The direct prompt
Both were the first choice
1 of 14 modelsThe answer named them together, and the judge labeled each a first choice.Ramp first, Expensify an alternative
6 of 14 modelsExpensify was named in the answer but not as the choice, or not at all.Expensify first, Ramp an alternative
1 of 14 modelsRamp was named in the answer but not as the choice, or not at all.Neither was the first choice, one was named
4 of 14 modelsThe answer put something else first and named one of the two as an alternative.Neither was named
2 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
What the models said about Ramp
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Two of two in this category shown.
“Ramp or Brex (Best for Card-First, Modern Spend Management): Free platform fees, incredibly fast to set up, highly modern UI, and top-tier AI receipt matching.” Gemini 3.5 Flash · scale prompt · first choice
“Ramp (Best Overall Free Option) ... Go with Ramp. It will save your team dozens of hours of manual receipt-chasing, and you will pay $0 in software fees.” Gemini 3.5 Flash · budget prompt · first choice
What the models said about Expensify
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Five of six in this category shown.
“criticized for complex and unintuitive interfaces, unexpected fees, unreliable credit card syncing, and poor customer support” Mistral Small · negative prompt · hard negative
“Came under fire for receipt scanning methodology using third-party ML services... recurring technical and syncing problems” MiniMax M2.5 · negative prompt · hard negative
“Expensify | Small to mid-sized businesses, SMBs, distributed teams | $5/user/month ... Simple onboarding, fast expense submission, excellent value for money” GLM 4.7 FlashX · comparative prompt · first choice
“### 1. Expensify (Best All-Rounder) ... Choose Expensify if: You want the safest bet with the widest range of accounting software connections.” Qwen 3.7 Flash · paraphrase prompt · first choice
“I'd recommend Expensify as the default choice if you want a strong balance of ease of use, automation, and cost” Perplexity Sonar · paraphrase 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.