Basis vs Google Display & Video 360
Zero of fourteen models named Basis first on the direct prompt; zero named Google Display & Video 360. Basis was named by ten of the fourteen models and Google Display & Video 360 by thirteen and Basis carries 16 labels and Google Display & Video 360 32, so the shares are not directly comparable.
By BASIS International, Albuquerque, founded 1985. Named in five categories this edition.
By Google, Mountain View, California, United States, founded 1998. Named in three 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 programmatic and display advertising page.
By framing
BasisFirst choices, of fourteen modelsGoogle Display & Video 360
Across every category in the October 2026 Edition, Basis and Google Display & Video 360 were named in the same answer twenty-two times, of the 58 answers naming Basis and the 176 naming Google Display & Video 360. In those answers Google Display & Video 360 took the first choice two times and Basis two.
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 | | | |
Basis Google Display & Video 360 first choice named as an alternative argued againstblank: not namedEach cell is one answer, Basis on the left and Google Display & Video 360 on the right.The direct prompt
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
8 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
Google Display & Video 3602%#11 of 15Basis0%#– of 15Basis2%#7 of 13Google Display & Video 3602%#8 of 13Google Display & Video 36010%#3 of 10Basis0%#9 of 10What the models said about Basis
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. One of one in this category shown.
“Basis Technologies (formerly Centro): Excellent workflow automation tools, great for regional or mid-market companies” Gemini 3.5 Flash · scale prompt · first choice
What the models said about Google Display & Video 360
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of seven in this category shown.
“($35K–$50K+/month, no self-serve) ... have high thresholds, complex contracts ... aren't practical for small budgets” Grok 4.1 Fast · budget prompt · hard negative
“What I'd Avoid for Mid-Sized B2B: ... $50K+/month minimum, complex, overkill for mid-market” Kimi K2 · paraphrase prompt · hard negative
“The Caution: In a major 2025 report by Adalytics, it was found that programmatic ads from major advertisers were served on a website hosting child sexual abuse material” GLM 4.7 FlashX · negative prompt · soft negative
“Industry standards like Google DV360, The Trade Desk, and Amazon DSP are generally considered to offer better safety controls” MiniMax M2.5 · negative prompt · first choice
“Prioritize platforms like Google DV360, The Trade Desk, MediaMath, or Amazon DSP, but test via demos or pilots.” Grok 4.1 Fast · scale prompt · first choice
“If you prioritize Google's ecosystem ... DV360 is often the best choice.” GLM 4.7 FlashX · comparative 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.