# YouTube Ads vs MNTN: which do AI models recommend for video ads, October 2026

GTM AI Recommendation Index, October 2026 Edition, Video advertising. One of fourteen models named YouTube Ads first on the direct prompt; zero named MNTN. Page: https://gtm-ai-index.com/marketing/video-advertising/youtube-ads-vs-mntn/

| | First-choice share | Rank | Negative rate | Labels | Models naming it |
|---|---|---|---|---|---|
| YouTube Ads | 15% | #2 of 13 | 15% | 46 | 14 of 14 |
| MNTN | 2% | #6 of 13 | 0% | 15 | 10 of 14 |

## The direct prompt, model by model

- Kimi K2: youtube ads first (first choices: LinkedIn Video Ads, YouTube Ads) (alternatives: Hey Sid, StackAdapt)
- Claude Haiku 4.5: neither first, one named (first choices: StackAdapt) (alternatives: LinkedIn Video Ads, MNTN, Vibe.co)
- GPT-5.4 mini: neither first, one named (first choices: LinkedIn Campaign Manager) (alternatives: YouTube Ads)
- Gemini 3.5 Flash: neither first, one named (first choices: LinkedIn Video Ads) (alternatives: Meta Ads, StackAdapt, Vibe.co, YouTube Ads)
- Grok 4.1 Fast: neither first, one named (first choices: LinkedIn Campaign Manager) (alternatives: YouTube Ads)
- Mistral Small: neither first, one named (first choices: StackAdapt) (alternatives: Demandbase, YouTube Ads)
- DeepSeek V4 Flash: neither first, one named (first choices: LinkedIn Video Ads) (alternatives: StackAdapt, YouTube Ads)
- GLM 4.7 FlashX: neither first, one named (first choices: LinkedIn Video Ads) (alternatives: Demandbase, StackAdapt, YouTube Ads)
- GPT-6 Luna: neither first, one named (first choices: LinkedIn Campaign Manager) (alternatives: StackAdapt, YouTube Ads)
- Muse Glimmer 30B: neither first, one named (first choices: LinkedIn Sponsored Video / LinkedIn Campaign Manager) (alternatives: Google Video, StackAdapt, YouTube Ads)
- Perplexity Sonar: neither named (first choices: StackAdapt) (alternatives: AdRoll ABM, LinkedIn Video Ads, The Trade Desk, Vibe.co)
- Llama 4 Maverick: neither named (first choices: StackAdapt)
- Qwen 3.7 Flash: neither named (first choices: LinkedIn Video Ads, StackAdapt) (alternatives: Google Ads)
- MiniMax M2.5: neither named (first choices: StackAdapt) (alternatives: AdRoll, Demandbase, Hey Sid)

## What the models said about YouTube Ads

- "major platforms like YouTube and Meta (Facebook/Instagram) have strict advertising policies. Violations can result in harsh penalties, such as ad account suspension." (Mistral Small, negative prompt, soft negative)
- "YouTube has faced brand safety scandals involving obscene comments on videos of children and major brands being shown alongside inappropriate content" (Claude Haiku 4.5, negative prompt, soft negative)
- "if you want broad reach and can support a somewhat higher ongoing test budget; one source suggests $500–1,000/month" (Perplexity Sonar, budget prompt, soft negative)
- "YouTube allows you to set flexible budgets, often starting as low as $1–$5 per day, making it highly accessible for small budgets." (Mistral Small, budget prompt, first choice)
- "Best for: broad reach, intent-driven video, and strong measurement across YouTube, Google TV, and partner inventory." (GPT-5.4 mini, comparative prompt, first choice)
- "Best For: Full-funnel marketing, search-intent audiences, and reaching viewers on both mobile and TV screens." (Qwen 3.7 Flash, comparative prompt, first choice)

## What the models said about MNTN

- "StackAdapt and MNTN are the best choices for dedicated CTV and online video advertising" (Mistral Small, paraphrase prompt, first choice)
- "MNTN is built for brands that don't have in-house video production, with higher budget minimums and managed service overhead." (Claude Haiku 4.5, comparative prompt, alternative)
- "have democratized CTV for growth marketers and SMBs by offering self-serve buying with budgets as low as $50/day" (Gemini 3.5 Flash, comparative prompt, alternative)

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.