# MillionVerifier vs DeBounce: which do AI models recommend for email verification, October 2026

GTM AI Recommendation Index, October 2026 Edition, Email verification. Zero of fourteen models named MillionVerifier first on the direct prompt; zero named DeBounce. Page: https://gtm-ai-index.com/gtm-data/email-verification/millionverifier-vs-debounce/

| | First-choice share | Rank | Negative rate | Labels | Models naming it |
|---|---|---|---|---|---|
| MillionVerifier | 9% | #3 of 10 | 30% | 20 | 12 of 14 |
| DeBounce | 4% | #6 of 10 | 15% | 20 | 11 of 14 |

## The direct prompt, model by model

- DeepSeek V4 Flash: neither first, one named (first choices: ZeroBounce) (alternatives: Bouncer, MillionVerifier, NeverBounce)
- GLM 4.7 FlashX: neither first, one named (first choices: ZeroBounce) (alternatives: Bouncer, DeBounce, Emailable, NeverBounce)
- Claude Haiku 4.5: neither named (first choices: Snov.io) (alternatives: Clearout, Kickbox, ZeroBounce)
- GPT-5.4 mini: neither named (first choices: ZeroBounce) (alternatives: Bouncer, Kickbox)
- Gemini 3.5 Flash: neither named (first choices: Bouncer) (alternatives: Allegrow, Findymail, Scrubby, ZeroBounce)
- Perplexity Sonar: neither named (first choices: Bouncer) (alternatives: Prospeo, ZeroBounce)
- Grok 4.1 Fast: neither named (first choices: ZeroBounce) (alternatives: Clearout, Hunter Email Verifier, Kickbox, NeverBounce)
- Mistral Small: neither named (first choices: NeverBounce, ZeroBounce) (alternatives: Prospeo, Snov.io)
- Llama 4 Maverick: neither named (first choices: ZeroBounce) (alternatives: Clearout, Emailable, Hunter Email Verifier)
- Qwen 3.7 Flash: neither named (first choices: ZeroBounce) (alternatives: Clearout, NeverBounce)
- Kimi K2: neither named (first choices: ZeroBounce) (alternatives: Emailable, Hunter Email Verifier, NeverBounce)
- MiniMax M2.5: neither named (first choices: ZeroBounce) (alternatives: Bouncer, Hunter Email Verifier, NeverBounce)
- GPT-6 Luna: neither named (first choices: ZeroBounce) (alternatives: Bouncer, BriteVerify)
- Muse Glimmer 30B: neither named (first choices: ZeroBounce) (alternatives: Hunter Email Verifier, NeverBounce, ZoomInfo)

## What the models said about MillionVerifier

- "MillionVerifier is the one most often singled out with documented false positives and billing complaints — proceed with caution there." (DeepSeek V4 Flash, negative prompt, hard negative)
- "MillionVerifier and EmailListVerify offer the lowest cost per 10k emails but lack advanced deliverability features" (Muse Glimmer 30B, budget prompt, soft negative)
- "Budget/low-cost options like EmailListVerify, MillionVerifier, and DeBounce - Approach with caution" (Grok 4.1 Fast, negative prompt, soft negative)
- "Choose MillionVerifier if you have a very large list (e.g., 10k+) to clean at once and want the lowest bulk price." (Qwen 3.7 Flash, budget prompt, first choice)
- "MillionVerifier – Best Overall Value ... If you need the absolute lowest cost: Go with MillionVerifier" (DeepSeek V4 Flash, budget prompt, first choice)
- "Start with MillionVerifier – 100 free credits to test, then pay-as-you-go with no expiration" (Kimi K2, budget prompt, first choice)

## What the models said about DeBounce

- "Budget/low-cost options like EmailListVerify, MillionVerifier, and DeBounce - Approach with caution" (Grok 4.1 Fast, negative prompt, soft negative)
- "Services with Hidden "Credit Multipliers" (e.g., DeBounce)" (Gemini 3.5 Flash, negative prompt, soft negative)
- "Cheapest; solid budget pick but lower accuracy on edges." (Grok 4.1 Fast, comparative prompt, soft negative)
- "Use established API providers like ZeroBounce, Debounce, or Abstract API." (Qwen 3.7 Flash, negative prompt, first choice)
- "Absolute cheapest one-off clean: DeBounce or BounceCheck at ~$20/10k one-time" (Muse Glimmer 30B, budget prompt, first choice)
- "DeBounce and MillionVerifier are generally considered the best options" (Qwen 3.7 Flash, budget prompt, first choice)

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. Comparisons are drawn for the top eight products in each category. Published under CC BY 4.0; the output is the models' output, and nothing here is a recommendation by the index.