StackAdapt vs Meta Ads
Eleven of fourteen models named StackAdapt first on the direct prompt; zero named Meta Ads. StackAdapt was named by fourteen of the fourteen models and Meta Ads by eight and StackAdapt carries 60 labels and Meta Ads 10, so the shares are not directly comparable.
Named in eight categories this edition.
By Meta Platforms, Menlo Park, United States, founded 2004. Named in seven 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
StackAdaptFirst choices, of fourteen modelsMeta Ads
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 | | | | | |
StackAdapt Meta Ads first choice named as an alternative argued againstblank: not namedEach cell is one answer, StackAdapt on the left and Meta Ads on the right.The direct prompt
StackAdapt first, Meta Ads not the choice
11 of 14 modelsMeta Ads was named in the answer but not as the choice, or not at all.Neither was named
3 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
StackAdapt43%#1 of 15Meta Ads8%#3 of 15StackAdapt48%#1 of 13Meta Ads3%#6 of 13What the models said about StackAdapt
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Three of three in this category shown.
“Good self-serve option too, but it's generally positioned more as an advanced multichannel DSP with custom usage-based pricing rather than an obviously low-entry-budget tool.” GPT-5.4 mini · budget prompt · soft negative
“often considered by smaller teams, but I'd want to verify your exact use case before recommending it over The Trade Desk or Demandbase” GPT-5.4 mini · direct prompt · soft negative
“strong for smaller agencies, but the budget guidance in the results suggests it is better once spend is a bit higher” Perplexity Sonar · budget prompt · soft negative
What the models said about Meta Ads
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Two of two in this category shown.
““very public quality-control challenges for platforms like YouTube and Facebook. Advertisers are worried their ads will show up next to offensive content”” Muse Glimmer 30B · negative prompt · soft negative
“Google Ads or Meta Ads are the best choices—no minimum spend, flexible daily budgets, and powerful targeting.” GLM 4.7 FlashX · budget 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.