# MarqVision vs ZeroFox: which do AI models recommend for brand protection, October 2026

GTM AI Recommendation Index, October 2026 Edition, Brand protection platforms. Two of fourteen models named MarqVision first on the direct prompt; one named ZeroFox. Page: https://gtm-ai-index.com/marketing/brand-protection/marqvision-vs-zerofox/

| | First-choice share | Rank | Negative rate | Labels | Models naming it |
|---|---|---|---|---|---|
| MarqVision | 6% | #4 of 8 | 19% | 32 | 13 of 14 |
| ZeroFox | 4% | #5 of 8 | 15% | 27 | 14 of 14 |

## The direct prompt, model by model

- Llama 4 Maverick: marqvision first (first choices: MarqVision) (alternatives: Bolster, Red Points)
- Qwen 3.7 Flash: marqvision first (first choices: Bolster, MarqVision) (alternatives: BrandVerity, Redpoints)
- Gemini 3.5 Flash: zerofox first (first choices: ZeroFox) (alternatives: Bolster AI, BrandShield, Netcraft, Red Points)
- Perplexity Sonar: neither first, one named (first choices: BrandShield, Red Points) (alternatives: Bolster, PriceSpider, TrackStreet, ZeroFox)
- Grok 4.1 Fast: neither first, one named (first choices: BrandShield) (alternatives: MarqVision, Red Points, ZeroFox)
- Mistral Small: neither first, one named (first choices: Red Points) (alternatives: BrandShield, MarqVision)
- GLM 4.7 FlashX: neither first, one named (first choices: Red Points) (alternatives: Bolster, BrandShield, ZeroFox)
- GPT-6 Luna: neither first, one named (first choices: Bolster) (alternatives: Doppel, Red Points, ZeroFox)
- Muse Glimmer 30B: neither first, one named (first choices: BrandShield) (alternatives: MarqVision, Red Points)
- Claude Haiku 4.5: neither named
- GPT-5.4 mini: neither named (first choices: Red Points) (alternatives: BrandShield, Corsearch)
- DeepSeek V4 Flash: neither named (first choices: Red Points) (alternatives: Bolster, BrandShield, Corsearch)
- Kimi K2: neither named (first choices: Red Points) (alternatives: BrandVerity, Corsearch, PhishEye)
- MiniMax M2.5: neither named (first choices: BrandShield, Red Points)

## What the models said about MarqVision

- "What to Avoid ... pricing starts at $25K–$100K/year—enterprise-focused" (Kimi K2, paraphrase prompt, hard negative)
- "rated strongest for scale but "its custom pricing and advanced features may not be suitable for small businesses with limited budgets."" (Muse Glimmer 30B, budget prompt, soft negative)
- "the platform can be slow to remove reported listings... This lag in enforcement could leave your brand exposed" (Mistral Small, negative prompt, soft negative)
- "Select Red Points or MarqVision if you sell physical goods and are losing major revenue to unauthorized copies of your products online." (Gemini 3.5 Flash, comparative prompt, first choice)
- "MarqVision (Best for E-Commerce & Mid-Market Brands) ... much more affordable than legacy enterprise competitors" (Gemini 3.5 Flash, budget prompt, first choice)
- "the consensus among recent reviews points to MarqVision and Bolster as the strongest fits" (Qwen 3.7 Flash, direct prompt, first choice)

## What the models said about ZeroFox

- "ZeroFox ⚠️ User complaints include: Inefficient alerts ... Frequent false alarms" (Kimi K2, negative prompt, hard negative)
- "Don't pay for enterprise platforms (Red Points, BrandShield, ZeroFox)" (DeepSeek V4 Flash, budget prompt, hard negative)
- "ZeroFox ... Why to avoid: Inefficient alerts" (GLM 4.7 FlashX, negative prompt, hard negative)
- "ZeroFox is a top choice. It bridges the gap between traditional security and brand monitoring." (Gemini 3.5 Flash, direct prompt, first choice)
- "a good "sweet spot" for a mid-sized B2B company is BrandShield or ZeroFox" (MiniMax M2.5, paraphrase prompt, first choice)
- "ZeroFox is often considered the gold standard for Fortune 500 companies." (Qwen 3.7 Flash, 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.