StackAdapt vs MGID
Six of fourteen models named StackAdapt first on the direct prompt; zero named MGID. StackAdapt was named by thirteen of the fourteen models and MGID by fourteen and both carry 43 labels, so the shares below are directly comparable.
Named in seven categories this edition.
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 native and content advertising page.
By framing
StackAdaptFirst choices, of fourteen modelsMGID
Across every category in the November 2026 Edition, StackAdapt and MGID were named in the same answer sixty-one times, of the 418 answers naming StackAdapt and the 130 naming MGID. In those answers MGID took the first choice thirteen times and StackAdapt thirteen.
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 MGID first choice named as an alternative argued againstblank: not namedEach cell is one answer, StackAdapt on the left and MGID on the right.The direct prompt
StackAdapt first, MGID an alternative
6 of 14 modelsMGID was named in the answer but not as the choice, or not at all.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
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
StackAdapt29%#1 of 10MGID12%#3 of 10StackAdapt29%#1 of 10MGID0%#9 of 10What 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.
“Avoid Taboola, Outbrain, and StackAdapt if your budget is under $600–$2,000/month” DeepSeek V4 Flash · budget prompt · hard negative
“StackAdapt: ~$2,000+ monthly minimum” Kimi K2 · budget prompt · hard negative
“focus on platforms with strong contextual targeting, brand safety controls, and transparent reporting, such as StackAdapt, Viant Technology, or Quantcast Platform” Mistral Small · negative prompt · first choice
What the models said about MGID
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of eight in this category shown.
“Frequently cited as an arbitrage platform with low-quality publisher mix.” GLM 4.7 FlashX · negative prompt · hard negative
“These smaller networks carry elevated invalid traffic baselines” Kimi K2 · negative prompt · hard negative
“appear in "top lists" but have scattered complaints about traffic quality or stricter policies—treat them as mid-tier with due diligence” Grok 4.20 · negative prompt · soft negative
“MGID stands out as the best native advertising platform for companies with a limited budget.” Grok 4.20 · budget prompt · first choice
“MGID is likely the best starting point for a company with a limited budget.” Perplexity Sonar · budget prompt · first choice
“or MGID for a mainstream self-serve native network with a $100 minimum deposit” Muse Glimmer 30B · 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.