Corporate travel management · October 2026 Edition
Booking.com for Business vs Ramp
Zero of fourteen models named Booking.com for Business first on the direct prompt; zero named Ramp. Booking.com for Business was named by twelve of the fourteen models and Ramp by thirteen and Booking.com for Business carries 28 labels and Ramp 38, so the shares are not directly comparable.
Named in one category this edition.
Named in seventeen categories this edition.
First-choice share14%5%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate25%8%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#3#4A position in a field of 12; printed, not drawn.
Labels2838A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, Booking.com for Business reading right to left. Rank and label count are printed, not drawn.TravelPerk was named alongside these two in thirteen of the fourteen direct answers. Navan vs Booking.com for Business · Navan vs Ramp · TravelPerk vs Booking.com for Business
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 corporate travel management page.
By framing
How many of the fourteen models made each the first choice, per way of asking, and how many argued against it.
Booking.com for BusinessFirst choices, of fourteen modelsRamp
Direct00
Paraphrase11
Comparative001 against Ramp
Budget-constrained72
Scale-constrained001 against Ramp
Negative007 against Booking.com for Business · 1 against Ramp
Bars are first choices, 0 to 14 each sideModels that argued againstA model can name both, so the two sides of a row do not sum to fourteen.
Every model, every framing
The eighty-four answers behind the chart above, one cell each: where Booking.com for Business and Ramp stood in it.
| 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 | | | | |
Booking.com for Business Ramp first choice named as an alternative argued againstblank: not namedEach cell is one answer, Booking.com for Business on the left and Ramp on the right.The direct prompt
The plain question, one answer per model, grouped by where Booking.com for Business and Ramp stood in it.
Neither was the first choice, one was named
9 of 14 modelsThe answer put something else first and named one of the two as an alternative.Claude Haiku 4.5Navan alternatives: Amex GBT Egencia, BCD Travel, Ramp, TravelPerk
Gemini 3.5 FlashNavan alternatives: Amex GBT Egencia, Brex, Ramp, TravelPerk
Perplexity SonarTravelPerk alternatives: Booking.com for Business, Corporate Traveler, Navan, Routespring
Grok 4.1 FastNavan alternatives: Ramp, TravelPerk
Mistral SmallNavan alternatives: Booking.com for Business, Certify, Routespring
Kimi K2Navan, TravelPerk alternatives: Ramp, Routespring, SAP Concur
GLM 4.7 FlashXNavan, TravelPerk alternatives: Ramp, SAP Concur
GPT-6 LunaNavan alternatives: Ramp, TravelPerk
Muse Glimmer 30BNavan, formerly TripActions alternatives: Booking.com for Business, Ramp, SAP Concur, TravelPerk
Neither was named
5 of 14 modelsThe answer made no first choice from these two in this category.GPT-5.4 miniNavan alternatives: Amex GBT Egencia, SAP Concur, TravelPerk
DeepSeek V4 FlashNavan alternatives: Amex GBT Egencia, SAP Concur, TravelPerk
Llama 4 MaverickNavan, Routespring, TravelPerk
Qwen 3.7 FlashTravelPerk alternatives: Navan, Spotnana
MiniMax M2.5Navan, TravelPerk alternatives: Spotnana
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
Booking.com for Business leads by twelve points.
Booking.com for Business20%#3 of 12Ramp8%#4 of 12Mid-marketThe figures above
Booking.com for Business leads by eight points.
Booking.com for Business14%#3 of 12Ramp5%#4 of 12Enterprise
The order flips: Ramp leads at enterprise.
Ramp4%#5 of 11Booking.com for Business0%#11 of 11What the models said about Booking.com for Business
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of eight in this category shown.
“Consumer booking sites like Expedia or Booking.com used as a business travel system ... generally lack policy enforcement” Perplexity Sonar · negative prompt · hard negative
“PissedConsumer rates them low (1.6-1.9/5) for refunds and support—avoid for corporate needs” Grok 4.1 Fast · negative prompt · hard negative
“their financial handling is often cited as problematic” Qwen 3.7 Flash · negative prompt · hard negative
“the strongest default choice is Booking.com for Business because it is positioned as a free, self-service business travel platform” Perplexity Sonar · budget prompt · first choice
“praised for being a free, self-service tool that minimizes costs while still providing robust travel booking and management features” Mistral Small · paraphrase prompt · first choice
“For a limited budget, Booking.com for Business and Perk are often the most cost-effective and user-friendly options” Mistral Small · budget prompt · first choice
What the models said about Ramp
No label in this category carried a quote.
Also compared
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.