Three of fourteen models named Apollo.io first on the direct prompt; four named Crayon. Apollo.io was named by eleven of the fourteen models and Crayon by fourteen and Apollo.io carries 20 labels and Crayon 42, so the shares are not directly comparable.
San Francisco, United States, founded 2015. Named in twenty-six categories this edition.
Named in five 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 market intelligence platforms page.
| Model | Direct | Paraphrase | Comparative | Budget-constrained | Scale-constrained | Negative |
|---|---|---|---|---|---|---|
| Claude Haiku 4.5 | ||||||
| GPT-5.4 mini | ||||||
| Gemini 3.5 Flash | ||||||
| Perplexity Sonar | ||||||
| Grok 4.1 Fast | ||||||
| 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 |
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.
No label in this category carried a quote.
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 enterprise-oriented platforms like Crayon, Klue, or AlphaSense if budget is the main constraint” Perplexity Sonar · budget prompt · hard negative
“Avoid enterprise platforms — Klue, Crayon, AlphaSense, and ZoomInfo” Kimi K2 · budget prompt · hard negative
“Pick Crayon if you want the most balanced "mid-market CI platform" for day-to-day competitive tracking and sales enablement.” GPT-5.4 mini · direct 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.