HubSpot Breeze Intelligence vs Cognism
One of fourteen models named HubSpot Breeze Intelligence first on the direct prompt; zero named Cognism. Both were named by all fourteen models and HubSpot Breeze Intelligence carries 52 labels and Cognism 48, so the shares are not directly comparable.
By HubSpot, Cambridge, United States, founded 2006. Named in eleven categories this edition.
Named in eleven 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 data enrichment page.
By framing
HubSpot Breeze IntelligenceFirst choices, of fourteen modelsCognism
Across every category in the October 2026 Edition, HubSpot Breeze Intelligence and Cognism were named in the same answer 117 times, of the 250 answers naming HubSpot Breeze Intelligence and the 402 naming Cognism. In those answers Cognism took the first choice six times and HubSpot Breeze Intelligence two.
Every model, every framing
| 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 | | | |
HubSpot Breeze Intelligence Cognism first choice named as an alternative argued againstblank: not namedEach cell is one answer, HubSpot Breeze Intelligence on the left and Cognism on the right.The direct prompt
HubSpot Breeze Intelligence first, Cognism not the choice
1 of 14 modelsCognism was named in the answer but not as the choice, or not at all.Neither was the first choice, one was named
12 of 14 modelsThe answer put something else first and named one of the two as an alternative.Neither was named
1 of 14 modelsThe answer made no first choice from these two in this category.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.
By buyer segment
HubSpot Breeze Intelligence0%#5 of 10Cognism0%#9 of 10HubSpot Breeze Intelligence4%#4 of 12Cognism2%#5 of 12Cognism2%#5 of 9HubSpot Breeze Intelligence0%#8 of 9What the models said about HubSpot Breeze Intelligence
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Four of four in this category shown.
“Users report a loss of functionality and flexibility, making it less reliable for those who previously relied on Clearbit's standalone features.” Mistral Small · negative prompt · hard negative
“Reduced functionality: Some features are no longer available or are locked behind HubSpot's ecosystem.” Mistral Small · negative prompt · hard negative
“HubSpot says Breeze does not provide contact email addresses or phone numbers—so it isn’t a replacement for a contact-finding database” GPT-6 Luna · comparative prompt · soft negative
“If I had to pick one default recommendation for a mid-sized B2B company, it would be Clearbit/Breeze Intelligence” GPT-5.4 mini · paraphrase prompt · first choice
What the models said about Cognism
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Three of three in this category shown.
“often Cognism — both are generally positioned as enterprise tools” GPT-5.4 mini · budget prompt · hard negative
“use European compliance-first data providers like Cognism or Dropcontact, which strictly adhere to GDPR” Gemini 3.5 Flash · negative prompt · first choice
“Cognism | GDPR/CCPA certified, human-verified mobile numbers” Kimi K2 · negative 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.