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Email verification · September 2026 Edition

Kickbox vs NeverBounce

One of twelve models named Kickbox first on the direct prompt; zero named NeverBounce. Both were named by all twelve models and Kickbox carries 27 labels and NeverBounce 39, so the shares are not directly comparable.

Kickbox

accepted challenger

Named in one category this edition.

NeverBounce

accepted challenger

Vancouver, founded 2014. Named in three categories this edition.

First-choice share4%2%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate0%8%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#5#8A position in a field of 11; printed, not drawn.
Labels2739A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, Kickbox reading right to left. Rank and label count are printed, not drawn.ZeroBounce was named alongside these two in ten of the twelve direct answers. ZeroBounce vs Kickbox · ZeroBounce vs NeverBounce · Bouncer vs Kickbox

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 email verification page.

By framing

How many of the twelve models made each the first choice, per way of asking, and how many argued against it.
KickboxFirst choices, of twelve modelsNeverBounce
Direct10
Paraphrase11
Comparative001 against NeverBounce
Budget-constrained00
Scale-constrained00
Negative112 against NeverBounce
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.

Across every category in the September 2026 Edition, Kickbox and NeverBounce were named in the same answer sixty-six times, of the 88 answers naming Kickbox and the 135 naming NeverBounce. In those answers NeverBounce took the first choice four times and Kickbox four.

Every model, every framing

The seventy-two answers behind the chart above, one cell each: where Kickbox and NeverBounce 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
Kickbox NeverBounce first choice named as an alternative argued againstblank: not namedEach cell is one answer, Kickbox on the left and NeverBounce on the right.

The direct prompt

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

Kickbox first, NeverBounce not the choice

1 of 12 modelsNeverBounce was named in the answer but not as the choice, or not at all.
Llama 4 MaverickClearout, Hunter, Kickbox

Neither was the first choice, one was named

7 of 12 modelsThe answer put something else first and named one of the two as an alternative.
Claude Haiku 4.5Bouncer, Skrapp alternatives: NeverBounce, ZeroBounce
Gemini 3.5 FlashBouncer alternatives: Allegrow, BounceBan, NeverBounce, ZeroBounce
Grok 4.1 FastHunter, ZeroBounce alternatives: Bouncer, Clearout, Kickbox
Mistral SmallZeroBounce alternatives: Bouncer, Clearout, Hunter, NeverBounce
DeepSeek V4 FlashBouncer alternatives: Hunter, NeverBounce, ZeroBounce
Qwen 3.7 FlashZeroBounce alternatives: Bouncer, EmailListVerify, Kickbox, MillionVerifier
GLM 4.7 FlashXClearout alternatives: Hunter, Kickbox

Neither was named

4 of 12 modelsThe answer made no first choice from these two in this category.
GPT-5.4 miniZeroBounce alternatives: Hunter
Perplexity SonarBouncer alternatives: Hunter, MillionVerifier, ZeroBounce
Kimi K2ZeroBounce alternatives: Bouncer, Clearout, Hunter
MiniMax M2.5ZeroBounce alternatives: Hunter

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.
Kickbox4%#5 of 10
NeverBounce4%#7 of 10
The full small business standing →
Mid-marketThe figures above
Kickbox leads by two points.
Kickbox4%#5 of 11
NeverBounce2%#8 of 11
The full mid-market standing →
Enterprise
The order flips: NeverBounce leads at enterprise.
NeverBounce6%#2 of 9
Kickbox4%#5 of 9
The full enterprise standing →

What the models said about Kickbox

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

“The best email verification service for a mid-market B2B company is Hunter, Clearout, or Kickbox” Llama 4 Maverick · direct prompt · first choice
“or Kickbox if you want point-of-entry validation integrated into your existing tech stack.” Claude Haiku 4.5 · paraphrase prompt · first choice
“include Bouncer, ZeroBounce, Kickbox, and NeverBounce” Kimi K2 · negative prompt · first choice

What the models said about NeverBounce

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

“Verdict: Avoid for critical campaigns due to reliability and support issues” Mistral Small · negative prompt · hard negative
“NeverBounce charges for unknowns... NeverBounce slowest (~200 min for 10K)” DeepSeek V4 Flash · comparative prompt · soft negative
“include Bouncer, ZeroBounce, Kickbox, and NeverBounce” Kimi K2 · negative prompt · first choice
“NeverBounce is the strongest pick for bulk list hygiene at scale.” Claude Haiku 4.5 · paraphrase prompt · first choice
“NeverBounce (Subscription Model) — Best Predictable Micro-Budget ... Starts at $10/month for 1,000 verifications.” Qwen 3.7 Flash · budget prompt · alternative
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.