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Data enrichment · September 2026 Edition

Cognism vs Cleanlist

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.

Cognism

accepted challenger

Named in eight categories this edition.

Cleanlist

accepted challenger

Named in six categories this edition.

First-choice share4%4%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate18%0%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#4#5A position in a field of 10; printed, not drawn.
Labels5020A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, Cognism reading right to left. Rank and label count are printed, not drawn.Apollo.io was named alongside these two in eleven of the twelve direct answers. Apollo.io vs Cognism · Apollo.io vs Cleanlist · Clay vs Cognism

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.

By framing

How many of the twelve models made each the first choice, per way of asking, and how many argued against it.
CognismFirst choices, of twelve modelsCleanlist
Direct123 against Cognism
Paraphrase10
Comparative11
Budget-constrained001 against Cognism
Scale-constrained00
Negative105 against Cognism
Bars are first choices, 0 to 12 each sideModels that argued againstA model can name both, so the two sides of a row do not sum to twelve.

Every model, every framing

The seventy-two answers behind the chart above, one cell each: where Cognism and Cleanlist stood in it.
ModelDirectParaphraseComparativeBudget-constrainedScale-constrainedNegative
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
Cognism Cleanlist first choice named as an alternative argued againstblank: not namedEach cell is one answer, Cognism on the left and Cleanlist on the right.

The direct prompt

The plain question, one answer per model, grouped by where Cognism and Cleanlist stood in it.

Cognism first, Cleanlist not the choice

1 of 12 modelsCleanlist was named in the answer but not as the choice, or not at all.
Claude Haiku 4.5Amplemarket, Apollo.io, Cognism

Cleanlist first, Cognism an alternative

2 of 12 modelsCognism was named in the answer but not as the choice, or not at all.
DeepSeek V4 FlashCleanlist alternatives: Apollo.io, Clay, Snov.io, UpLead
MiniMax M2.5Apollo.io, Cleanlist alternatives: Amplemarket, Cognism, ZoomInfo

Neither was the first choice, one was named

8 of 12 modelsThe answer put something else first and named one of the two as an alternative.
GPT-5.4 miniApollo.io alternatives: Clearbit/HubSpot-native enrichment, Cognism
Gemini 3.5 FlashApollo.io, Clay alternatives: Cognism, HubSpot Breeze Intelligence
Perplexity SonarApollo.io alternatives: Clay, Cognism, UpLead, ZoomInfo
Grok 4.1 FastApollo.io alternatives: Clay, Cleanlist, UpLead
Mistral SmallApollo.io alternatives: Cleanlist, UpLead
Qwen 3.7 FlashApollo.io alternatives: Cognism, HubSpot Breeze Intelligence, UpLead
Kimi K2Apollo.io alternatives: Cleanlist, Cognism, UpLead
GLM 4.7 FlashXApollo.io alternatives: Clay, Cognism, Lusha, UpLead

Neither was named

1 of 12 modelsThe answer made no first choice from these two in this category.
Llama 4 Maverickno first choice

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

The same question asked on behalf of a different buyer. Each standing is computed within its segment and they are never added together. The figures above are the mid-market standing, which is the one the category orders by.
Small business
Level: the same share of first choices.
Cognism0%#9 of 10
Cleanlist0%#7 of 10
The full small business standing →
Mid-marketThe figures above
Level: the same share of first choices.
Cognism4%#4 of 10
Cleanlist4%#5 of 10
The full mid-market standing →
Enterprise
Cognism leads by ten points.
Cognism12%#2 of 9
Cleanlist2%#– of 9
The full enterprise standing →

What the models said about Cognism

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

What the models said about Cleanlist

No label in this category carried a quote.

Also compared

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.