One of twelve models named Cognism first on the direct prompt; two named Cleanlist. Cognism was named by twelve of the twelve models and Cleanlist by eight and Cognism carries 50 labels and Cleanlist 20, so the shares are not directly comparable.
Named in eight categories this edition.
Named in six categories this edition.
Share is the count of first choices across the direct, paraphrase, budget and scale prompts over all twelve 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.
| 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 |
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. Four of four in this category shown.
“Data quality gaps outside the "Diamond Data" verified subset; Limited US coverage” MiniMax M2.5 · negative prompt · hard negative
“Avoid enterprise tools like ZoomInfo/Cognism ($15K+/yr)—not budget-friendly” Grok 4.1 Fast · budget prompt · hard negative
“I'd generally recommend Cognism if your priority is high-quality contact data, CRM enrichment, and compliance-conscious prospecting” GPT-5.4 mini · paraphrase prompt · first choice
“For mid-market companies, Apollo.io, Amplemarket, or Cognism offer a good balance of features and price depending on geography.” Claude Haiku 4.5 · 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.