StackAdapt vs Taboola
Twelve of fourteen models named StackAdapt first on the direct prompt; zero named Taboola. Both were named by all fourteen models and StackAdapt carries 41 labels and Taboola 61, so the shares are not directly comparable.
Named in eight categories this edition.
New York City, United States, founded 2007. 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 native and content advertising page.
By framing
StackAdaptFirst choices, of fourteen modelsTaboola
Across every category in the October 2026 Edition, StackAdapt and Taboola were named in the same answer eighty-six times, of the 388 answers naming StackAdapt and the 186 naming Taboola. In those answers Taboola took the first choice seventeen times and StackAdapt thirty.
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 4.20 | | | | | | |
| 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 | | | | | | |
StackAdapt Taboola first choice named as an alternative argued againstblank: not namedEach cell is one answer, StackAdapt on the left and Taboola on the right.The direct prompt
StackAdapt first, Taboola an alternative
12 of 14 modelsTaboola was named in the answer but not as the choice, or not at all.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
StackAdapt12%#4 of 8Taboola6%#5 of 8StackAdapt41%#1 of 9Taboola4%#6 of 9StackAdapt18%#2 of 10Taboola16%#3 of 10What the models said about StackAdapt
No label in this category carried a quote.
What the models said about Taboola
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Five of six in this category shown.
“Avoid the "big two" (Taboola/Outbrain)” Kimi K2 · budget prompt · hard negative
“Taboola served 61.1% of all problematic native ads analyzed ... While Taboola is safe for massive brands with strict compliance teams, if you are a smaller advertiser, you risk your brand” GLM 4.7 FlashX · negative prompt · soft negative
“"Best all-round reach: Taboola, through its Realize platform—450 billion recommendations a month, and the deepest, most liquid auction on the open web."” Muse Glimmer 30B · comparative prompt · first choice
“Best for: Massive reach, brand awareness, large-scale campaigns ... Deepest liquidity in the open web, massive scale” Kimi K2 · comparative prompt · first choice
“The undisputed leader in sheer volume and liquidity... If your goal is volume, start with Taboola or Teads.” Qwen 3.7 Flash · 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.