Business banking · November 2026 Edition
Bluevine vs Bank of America
Zero of fourteen models named Bluevine first on the direct prompt; one named Bank of America. Bluevine was named by thirteen of the fourteen models and Bank of America by fourteen and Bluevine carries 35 labels and Bank of America 31, so the shares are not directly comparable.
Named in two categories this edition.
Named in six categories this edition.
First-choice share13%2%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate11%26%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#2#8A position in a field of 16; printed, not drawn.
Labels3531A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, Bluevine reading right to left. Rank and label count are printed, not drawn.Mercury vs Bluevine · Mercury vs Bank of America · Bluevine vs Brex
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 business banking page.
By framing
How many of the fourteen models made each the first choice, per way of asking, and how many argued against it.
BluevineFirst choices, of fourteen modelsBank of America
Direct01
Paraphrase101 against Bluevine · 1 against Bank of America
Comparative00
Budget-constrained601 against Bank of America
Scale-constrained00
Negative003 against Bluevine · 6 against Bank of America
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.
Across every category in the November 2026 Edition, Bluevine and Bank of America were named in the same answer thirty-three times, of the 115 answers naming Bluevine and the 131 naming Bank of America. In those answers Bank of America took the first choice two times and Bluevine three.
Every model, every framing
The eighty-four answers behind the chart above, one cell each: where Bluevine and Bank of America 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 4.20 | | | | | | |
| 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 | | | | |
Bluevine Bank of America first choice named as an alternative argued againstblank: not namedEach cell is one answer, Bluevine on the left and Bank of America on the right.The direct prompt
The plain question, one answer per model, grouped by where Bluevine and Bank of America stood in it.
Bank of America first, Bluevine an alternative
1 of 14 modelsBluevine was named in the answer but not as the choice, or not at all.Grok 4.20Bank of America alternatives: Bluevine, Brex, Chase Business Banking, Citibank, Mercury, PNC Bank, Texas Capital Bank
Neither was the first choice, one was named
5 of 14 modelsThe answer put something else first and named one of the two as an alternative.GPT-5.4 miniJ.P. Morgan Commercial Banking alternatives: Bank of America
Perplexity SonarChase Commercial Banking alternatives: Airwallex, Bank of America, Brex, Mercury, Ramp, Rho, U.S. Bank
Kimi K2Brex alternatives: Bank of America, First Internet Bank, Mercury
GPT-6 LunaJ.P. Morgan Commercial Banking alternatives: Bank of America, Citibank
Muse Glimmer 30BPNC Bank alternatives: Bank of America, Brex, First Internet Bank
Neither was named
8 of 14 modelsThe answer made no first choice from these two in this category.Claude Haiku 4.5Brex alternatives: Chase Business Banking, Mercury, Relay
Gemini 3.5 FlashJPMorgan Chase – Middle Market Banking & Specialized Industries alternatives: Bank of America Global Commercial Banking, Brex, PNC Bank – Treasury Management, Ramp, Silicon Valley Bank, Wells Fargo – Commercial Banking
Mistral SmallPNC Bank, TD Business Premier Checking alternatives: Axos Bank Basic Business Checking, Capital One Business Savings & Checking, Chase Business Banking
DeepSeek V4 FlashChase Performance Business Checking alternatives: Capital One Enhanced Checking, KeyBank Business Reward Checking, Mercury, PNC Bank, Rho
Llama 4 Maverickno first choice
Qwen 3.7 FlashCamber, Mercury alternatives: Bank of America Business Advantage Fundamentals, Signature Bank, TD Bank Business Checking, Umpqua Bank
GLM 4.7 FlashXBank of America - Business Advantage 360, PNC Bank - Treasury Enterprise Plan alternatives: Chase - Performance Business Checking, First Internet Bank - Commercial Analyzed Checking, Frost Business Checking Plus
MiniMax M2.5Chase Performance Business Checking alternatives: American Express Business Checking, Mercury, PNC Bank, TD Business Premier Checking
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
Bluevine leads by twenty-four points.
Bluevine24%#2 of 14Bank of America0%#12 of 14Mid-marketThe figures above
Bluevine leads by eleven points.
Bluevine13%#2 of 16Bank of America2%#8 of 16Enterprise
The order flips: Bank of America leads at enterprise.
Bank of America8%#4 of 13Bluevine0%#– of 13What the models said about Bluevine
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of eight in this category shown.
“Similar rate (13.2 negative reviews/month), with ~44% tied to freezes/closures.” Grok 4.20 · negative prompt · hard negative
“platforms (like Relay or Bluevine) often fall short on ERP integrations, custom approval workflows, high transaction limits” Gemini 3.5 Flash · paraphrase prompt · soft negative
“I wouldn't say "avoid" across the board. I would treat them as products to vet carefully” GPT-6 Luna · negative prompt · soft negative
“Start with Mercury (treasury + invoicing + payroll) or Bluevine (low fees + high yields). Both have strong track records” GLM 4.7 FlashX · paraphrase prompt · first choice
“Bluevine Business Checking Standard is my best default for a company on a tight budget” GPT-6 Luna · budget prompt · first choice
“Bluevine is highly recommended for fee-free checking, high APYs” Mistral Small · budget prompt · first choice
What the models said about Bank of America
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Five of five in this category shown.
“Receives a high volume of complaints, often regarding fees and customer service” Claude Haiku 4.5 · negative prompt · hard negative
“Bank of America: It has an enforcement order that has not been terminated.” Llama 4 Maverick · negative prompt · hard negative
“Start with Bank of America for a balanced, proven mid-market solution” Grok 4.20 · direct prompt · first choice
“Traditional banks (Chase, Wells Fargo, Bank of America, regional banks) can offer more comprehensive commercial lending.” DeepSeek V4 Flash · scale prompt · alternative
“is also a strong option, especially if you want broad treasury services and a large U.S. branch footprint” GPT-5.4 mini · direct prompt · alternative
Also compared
Mercury vs BluevineMercury vs Bank of AmericaBluevine vs BrexBluevine vs RhoBluevine vs PNC BankBluevine vs American Express Business CheckingBluevine vs Axos Bank Basic Business CheckingBrex vs Bank of AmericaRho vs Bank of AmericaPNC Bank vs Bank of AmericaAmerican Express Business Checking vs Bank of AmericaAxos Bank Basic Business Checking vs Bank of AmericaAll twenty-eight head-to-head pages and the full business banking 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.