Airbase vs Spendesk
Three of fourteen models named Airbase first on the direct prompt; one named Spendesk. Airbase was named by fourteen of the fourteen models and Spendesk by thirteen and Airbase carries 39 labels and Spendesk 28, so the shares are not directly comparable.
Named in eight categories this edition.
Named in four 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 spend management platforms page.
By framing
AirbaseFirst choices, of fourteen modelsSpendesk
Across every category in the October 2026 Edition, Airbase and Spendesk were named in the same answer thirty-three times, of the 171 answers naming Airbase and the 90 naming Spendesk. In those answers Spendesk took the first choice one time and Airbase four.
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 | | | |
Airbase Spendesk first choice named as an alternative argued againstblank: not namedEach cell is one answer, Airbase on the left and Spendesk 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.Airbase first, Spendesk not the choice
2 of 14 modelsSpendesk 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
4 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
Airbase17%#2 of 12Spendesk4%#5 of 12Spendesk2%#9 of 14Airbase0%#14 of 14What the models said about Airbase
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Three of three in this category shown.
“for buyers who want a standalone finance vendor... verify the product's roadmap, support ownership, and integration priorities fit your needs” GPT-6 Luna · negative prompt · soft negative
“Caveat: No longer sold as standalone; requires Paylocity relationship” Kimi K2 · paraphrase prompt · soft negative
“Most mid-sized B2B companies find that Ramp or Airbase provide the best balance of features, ease of use, and value for money.” GLM 4.7 FlashX · paraphrase prompt · first choice
What the models said about Spendesk
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Five of six in this category shown.
“several users report it may be too expensive for smaller teams and lacks depth in critical operational areas” GLM 4.7 FlashX · negative prompt · soft negative
“Be cautious if you have high transaction volumes with many recurring vendors and are cost-sensitive.” Muse Glimmer 30B · negative prompt · soft negative
“High cost relative to competitors, Approval delays, Customer service response time concerns” MiniMax M2.5 · negative prompt · soft negative
“Spendesk - Combines company cards, expense management, accounts payable, procurement, budgeting, and spend controls. Suitable for mid-sized teams” Llama 4 Maverick · paraphrase prompt · first choice
“If you want maximum adoption signal for SMB/mid-market CFOs today, Spendesk leads the reported adoption share.” Muse Glimmer 30B · 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.