# Kompyte vs SpyFu: which do AI models recommend for competitive intel, October 2026

GTM AI Recommendation Index, October 2026 Edition, Competitive intelligence tools. Nine of fourteen models named Kompyte first on the direct prompt; zero named SpyFu. Page: https://gtm-ai-index.com/marketing/competitive-intelligence/kompyte-vs-spyfu/

| | First-choice share | Rank | Negative rate | Labels | Models naming it |
|---|---|---|---|---|---|
| Kompyte | 38% | #1 of 12 | 11% | 56 | 14 of 14 |
| SpyFu | 6% | #4 of 12 | 21% | 19 | 13 of 14 |

## The direct prompt, model by model

- GPT-5.4 mini: kompyte first (first choices: Kompyte) (alternatives: Crayon, Klue, Similarweb)
- Perplexity Sonar: kompyte first (first choices: Kompyte) (alternatives: Crayon, Similarweb, ZoomInfo)
- Grok 4.1 Fast: kompyte first (first choices: Kompyte) (alternatives: Semrush)
- Mistral Small: kompyte first (first choices: Klue, Kompyte)
- DeepSeek V4 Flash: kompyte first (first choices: Kompyte) (alternatives: Klue)
- Llama 4 Maverick: kompyte first (first choices: Kompyte)
- Kimi K2: kompyte first (first choices: Kompyte) (alternatives: Klue, Semrush)
- GLM 4.7 FlashX: kompyte first (first choices: Kompyte) (alternatives: Crayon, Klue)
- Muse Glimmer 30B: kompyte first (first choices: Kompyte) (alternatives: Crayon, Klue)
- Claude Haiku 4.5: neither first, one named (first choices: Klue) (alternatives: Crayon, Kompyte)
- Gemini 3.5 Flash: neither first, one named (first choices: Klue) (alternatives: BattleReady, Crayon, Kompyte)
- Qwen 3.7 Flash: neither first, one named (first choices: Klue) (alternatives: Ahrefs, Clutch, Crayon, G2 Buyer Intent, Kompyte, Semrush)
- MiniMax M2.5: neither named (first choices: ZoomInfo) (alternatives: Google Alerts, Mention, Semrush)
- GPT-6 Luna: neither named (first choices: Klue) (alternatives: Crayon)

## What the models said about Kompyte

- "Avoid if you work in a fast-moving industry." (DeepSeek V4 Flash, negative prompt, hard negative)
- "Products such as Crayon, Klue, and Kompyte ... do not explain buyer decision-making or deal-level context" (Perplexity Sonar, negative prompt, soft negative)
- "some users report it can become pricey relative to its utility if you only need basic tracking" (Qwen 3.7 Flash, negative prompt, soft negative)
- "The best competitive intelligence tool for a mid-market B2B company is Kompyte, as it is considered the strongest mid-market option" (Llama 4 Maverick, direct prompt, first choice)
- "Kompyte is consistently ranked as the best dedicated competitive intelligence platform for companies on a tight budget" (Qwen 3.7 Flash, budget prompt, first choice)
- "Pick Crayon or Kompyte. These tools are built to surface competitor updates in a format sellers can use quickly." (GPT-5.4 mini, comparative prompt, first choice)

## What the models said about SpyFu

- "Verdict: Use only for basic PPC keyword research, not for comprehensive competitive intelligence." (GLM 4.7 FlashX, negative prompt, hard negative)
- "Examples to scrutinize: Tools like some SEO/spy suites (e.g., SpyFu, certain features in SEMrush/Ahrefs) or generic scrapers." (Grok 4.1 Fast, negative prompt, soft negative)
- "Tools like Semrush, Ahrefs, and SpyFu ... are not full competitive-intelligence platforms" (Perplexity Sonar, negative prompt, soft negative)
- "For the tightest budget, SpyFu appears to be the most cost-effective option specifically designed for competitor research." (MiniMax M2.5, budget prompt, first choice)
- "My top overall recommendation: If you can afford ~$29/month, SpyFu gives you the most actionable competitive intelligence" (DeepSeek V4 Flash, budget prompt, first choice)
- "Best low-budget choice: SpyFu—if your competitive intelligence is mainly about SEO and Google Ads." (GPT-6 Luna, budget 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.