Five of fourteen models named Intercom first on the direct prompt; three named HubSpot Marketing Hub. Intercom was named by fourteen of the fourteen models and HubSpot Marketing Hub by eight and Intercom carries 54 labels and HubSpot Marketing Hub 13, so the shares are not directly comparable.
United States, founded 2011. Named in twelve categories this edition.
By HubSpot, Cambridge, United States, founded 2006. Named in twenty-eight 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 conversational marketing 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.
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Two of two in this category shown.
“Top picks: Intercom (sales-focused), HubSpot (all-in-one CRM), Drift (conversational AI), Tidio/Zendesk (affordable multi-channel).” Grok 4.1 Fast · scale prompt · first choice
“Choose Intercom if you need a single tool for both buyer-facing sales qualification and post-sale/support, with Fin AI deflection” Muse Glimmer 30B · direct prompt · first choice
No label in this category carried a quote.
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.