ZeroBounce vs Emailable
Thirteen of fourteen models named ZeroBounce first on the direct prompt; zero named Emailable. ZeroBounce was named by fourteen of the fourteen models and Emailable by thirteen and ZeroBounce carries 63 labels and Emailable 25, so the shares are not directly comparable.
Named in four categories this edition.
Montebello, United States, founded 2017. Named in one category 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 email verification page.
By framing
ZeroBounceFirst choices, of fourteen modelsEmailable
Across every category in the November 2026 Edition, ZeroBounce and Emailable were named in the same answer sixty-six times, of the 273 answers naming ZeroBounce and the 75 naming Emailable. In those answers Emailable took the first choice five times and ZeroBounce thirty-one.
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 4.20 | | | | | | |
| 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 | | | | |
ZeroBounce Emailable first choice named as an alternative argued againstblank: not namedEach cell is one answer, ZeroBounce on the left and Emailable on the right.The direct prompt
ZeroBounce first, Emailable an alternative
13 of 14 modelsEmailable was named in the answer but not as the choice, or not at all.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
ZeroBounce30%#1 of 11Emailable6%#5 of 11ZeroBounce47%#1 of 11Emailable4%#6 of 11ZeroBounce69%#1 of 9Emailable0%#7 of 9What the models said about ZeroBounce
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Five of six in this category shown.
“Competing platforms, including ZeroBounce, NeverBounce, Kickbox, and Bouncer, charge $0.008 per verification or higher.” Claude Haiku 4.5 · budget prompt · soft negative
“More expensive per-credit than the budget leaders; only worthwhile if you need the extra features” DeepSeek V4 Flash · budget prompt · soft negative
“Choose ZeroBounce if you want an all-in-one deliverability suite with top-tier security and spam-trap detection.” Gemini 3.5 Flash · comparative prompt · first choice
“For most mid-market B2B companies, ZeroBounce offers the best balance of accuracy, features, and pricing.” MiniMax M2.5 · direct prompt · first choice
“ZeroBounce is widely considered the best email verification service for a mid-market B2B company.” Qwen 3.7 Flash · direct prompt · first choice
What the models said about Emailable
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Five of six in this category shown.
“Very low Trustpilot score (~1.9/5)... Avoid for reliability.” Grok 4.20 · negative prompt · hard negative
“Kickbox or Emailable, but they generally cost more than the budget-focused options” Perplexity Sonar · budget prompt · soft negative
“Emailable is highlighted as the best budget-friendly email verification service for companies with a limited budget” Mistral Small · budget prompt · first choice
“Best Overall Accuracy: Emailable (99%) or ZeroBounce (99%)” Kimi K2 · comparative prompt · first choice
“Emailable or EmailListVerify stand out as the best options” Grok 4.20 · budget 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.