# MGID vs Teads: which do AI models recommend for native ads, October 2026

GTM AI Recommendation Index, October 2026 Edition, Native and content advertising. Zero of fourteen models named MGID first on the direct prompt; zero named Teads. Page: https://gtm-ai-index.com/marketing/native-and-content-advertising/mgid-vs-teads/

| | First-choice share | Rank | Negative rate | Labels | Models naming it |
|---|---|---|---|---|---|
| MGID | 12% | #3 of 9 | 30% | 46 | 14 of 14 |
| Teads | 4% | #5 of 9 | 22% | 74 | 14 of 14 |

## The direct prompt, model by model

- Claude Haiku 4.5: neither first, one named (first choices: StackAdapt) (alternatives: LinkedIn Sponsored Content, Teads)
- Grok 4.20: neither first, one named (first choices: StackAdapt) (alternatives: Sharethrough, Taboola, Teads)
- Qwen 3.7 Flash: neither first, one named (first choices: StackAdapt) (alternatives: Raptive, Simpli.fi, Taboola, Teads)
- Kimi K2: neither first, one named (first choices: StackAdapt) (alternatives: LinkedIn Sponsored Content, Taboola, Teads)
- Muse Glimmer 30B: neither first, one named (first choices: StackAdapt) (alternatives: Taboola / Realize, Teads)
- GPT-5.4 mini: neither named (first choices: StackAdapt) (alternatives: AdRoll ABM, Demandbase, Microsoft Advertising Audience Ads)
- Gemini 3.5 Flash: neither named (first choices: LinkedIn Sponsored Content) (alternatives: 6sense, AdLib, Basis, Demandbase, Dianomi)
- Perplexity Sonar: neither named (first choices: StackAdapt) (alternatives: Taboola)
- Mistral Small: neither named (first choices: StackAdapt)
- DeepSeek V4 Flash: neither named (first choices: StackAdapt) (alternatives: LinkedIn Sponsored Content, NetLine, ViB)
- Llama 4 Maverick: neither named (first choices: StackAdapt) (alternatives: Abmatic AI, Demandbase)
- GLM 4.7 FlashX: neither named (first choices: StackAdapt) (alternatives: LinkedIn Sponsored Content, Microsoft Advertising)
- MiniMax M2.5: neither named (first choices: StackAdapt) (alternatives: LinkedIn Sponsored Content, Microsoft Advertising, SmartyAds DSP)
- GPT-6 Luna: neither named (first choices: LinkedIn Sponsored Content) (alternatives: AdRoll ABM)

## What the models said about MGID

- "What I'd Avoid or Use with Caution - MGID – Heavy entertainment/clickbait inventory" (DeepSeek V4 Flash, paraphrase prompt, hard negative)
- "High-volume, low-CPC affiliate-style networks such as MGID and RichAds: ... they can need substantial filtering to avoid invalid traffic and low-quality placements." (Perplexity Sonar, negative prompt, soft negative)
- "Many advertisers limit MGID, Revcontent and similar performance networks to direct-response use cases with strict creative compliance" (Muse Glimmer 30B, negative prompt, soft negative)
- "For the tightest budget, MGID appears to be the best starting point due to its lower CPCs and accessibility for beginners." (MiniMax M2.5, budget prompt, first choice)
- "The Overall Best Choice: MGID ... most accessible and cost-effective native ad network for small businesses" (Gemini 3.5 Flash, budget prompt, first choice)
- "MGID stands out as the best native advertising platform for companies with a limited budget." (Grok 4.20, budget prompt, first choice)

## What the models said about Teads

- "Avoid the "big two" (Taboola/Outbrain)" (Kimi K2, budget prompt, hard negative)
- "be very careful reading Taboola or Outbrain agreements. They historically include aggressive exclusivity clauses and auto-renewal traps." (Gemini 3.5 Flash, negative prompt, soft negative)
- "Reputable alternatives (fewer complaints): Outbrain, Taboola (with controls), Sharethrough." (Grok 4.20, negative prompt, first choice)
- "Best for: Performance marketing, content-driven brands, premium publisher environments" (Kimi K2, comparative prompt, first choice)
- "Choose Taboola or Outbrain if you want scale and mainstream publisher reach" (Perplexity Sonar, comparative prompt, first choice)

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. Comparisons are drawn for the top eight products in each category. Published under CC BY 4.0; the output is the models' output, and nothing here is a recommendation by the index.