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Data enrichment · October 2026 Edition

Clay vs Lusha

One of fourteen models named Clay first on the direct prompt; zero named Lusha. Both were named by all fourteen models and Clay carries 37 labels and Lusha 45, so the shares are not directly comparable.

Clay

accepted challenger

Named in eleven categories this edition.

Lusha

accepted challenger

By Lusha Systems, Boston, United States, founded 2016. Named in five categories this edition.

First-choice share6%2%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate11%16%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#2#6A position in a field of 12; printed, not drawn.
Labels3745A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, Clay reading right to left. Rank and label count are printed, not drawn.Apollo.io was named alongside these two in thirteen of the fourteen direct answers. Apollo.io vs Clay · Apollo.io vs Lusha · Clay vs ZoomInfo

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

How many of the fourteen models made each the first choice, per way of asking, and how many argued against it.
ClayFirst choices, of fourteen modelsLusha
Direct10
Paraphrase10
Comparative101 against Clay
Budget-constrained011 against Clay
Scale-constrained10
Negative012 against Clay · 7 against Lusha
Bars are first choices, 0 to 14 each sideModels that argued againstA model can name both, so the two sides of a row do not sum to fourteen.

Across every category in the October 2026 Edition, Clay and Lusha were named in the same answer ninety times, of the 234 answers naming Clay and the 340 naming Lusha. In those answers Lusha took the first choice two times and Clay six.

Every model, every framing

The eighty-four answers behind the chart above, one cell each: where Clay and Lusha 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
GPT-6 Luna
Muse Glimmer 30B
Clay Lusha first choice named as an alternative argued againstblank: not namedEach cell is one answer, Clay on the left and Lusha on the right.

The direct prompt

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

Clay first, Lusha not the choice

1 of 14 modelsLusha was named in the answer but not as the choice, or not at all.
Gemini 3.5 FlashClay alternatives: Apollo.io, Cognism, HubSpot Breeze Intelligence, ZoomInfo

Neither was the first choice, one was named

6 of 14 modelsThe answer put something else first and named one of the two as an alternative.
GPT-5.4 miniApollo.io alternatives: Lusha, ZoomInfo
Mistral SmallZoomInfo alternatives: Clay, HubSpot Breeze Intelligence, UpLead
DeepSeek V4 FlashApollo.io alternatives: Cleanlist, Cognism, HubSpot Breeze Intelligence, Lusha
Kimi K2Apollo.io alternatives: Clay, HubSpot Breeze Intelligence
GLM 4.7 FlashXApollo.io alternatives: Clay, Cognism, HubSpot Breeze Intelligence
GPT-6 LunaApollo.io alternatives: Clay, Cognism, HubSpot Breeze Intelligence

Neither was named

7 of 14 modelsThe answer made no first choice from these two in this category.
Claude Haiku 4.5Apollo.io alternatives: Cleanlist, Cognism, ZoomInfo
Perplexity SonarApollo.io alternatives: Cognism, UpLead
Grok 4.1 FastApollo.io alternatives: Cognism, UpLead
Llama 4 MaverickApollo.io alternatives: HubSpot Breeze Intelligence, UpLead
Qwen 3.7 FlashUpLead alternatives: Apollo.io, HubSpot Breeze Intelligence
MiniMax M2.5Apollo.io, HubSpot Breeze Intelligence alternatives: ZoomInfo
Muse Glimmer 30BApollo.io alternatives: Cognism, HubSpot Sales Hub

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
Clay leads by two points.
Clay4%#3 of 10
Lusha2%#4 of 10
The full small business standing →
Mid-marketThe figures above
Clay leads by four points.
Clay6%#2 of 12
Lusha2%#6 of 12
The full mid-market standing →
Enterprise
Clay leads by six points.
Clay6%#4 of 9
Lusha0%#9 of 9
The full enterprise standing →

What the models said about Clay

Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of seven in this category shown.

“multi-provider setups built with tools such as Apollo’s waterfall feature or Clay... may make it harder to trace where a particular field came from” GPT-6 Luna · negative prompt · soft negative
“Don't adopt Clay unless you have technical staff to manage workflows.” DeepSeek V4 Flash · negative prompt · soft negative
“requires 3 to 4 additional tools and has unpredictable credit costs” Claude Haiku 4.5 · comparative prompt · soft negative
“Choose Clay if you have a modern, tech-savvy sales/marketing team ... wants the best possible email-finding coverage” Gemini 3.5 Flash · paraphrase prompt · first choice
“Clay (Best for Workflow Orchestration & Waterfall Enrichment): Clay is a market leader for modern GTM teams.” Gemini 3.5 Flash · scale prompt · first choice
“If your strategy is personalized outbound and you want maximum data coverage: Go with Clay.” Gemini 3.5 Flash · comparative prompt · first choice

What the models said about Lusha

Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Five of five in this category shown.

“Low email accuracy: Independent checks suggest only about 68% email return at roughly 82% accuracy, which is below industry standards.” Mistral Small · negative prompt · hard negative
“Tools that have faced regulatory actions (e.g., Lusha's Italy fine) should be avoided in sensitive jurisdictions.” GLM 4.7 FlashX · negative prompt · hard negative
“Some users report issues with outdated contact information and relatively high pricing for infrequent use.” Claude Haiku 4.5 · negative prompt · soft negative
“Safer bets from reviews: Tools like Lusha (98% email accuracy, free tier)” Grok 4.1 Fast · negative prompt · first choice
“Apollo.io or Lusha are the right entry points. Both offer free tiers” Claude Haiku 4.5 · budget prompt · first choice
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.