Mail-Tester vs Microsoft SNDS
Zero of fourteen models named Mail-Tester first on the direct prompt; zero named Microsoft SNDS. Mail-Tester was named by eleven of the fourteen models and Microsoft SNDS by ten and Mail-Tester carries 20 labels and Microsoft SNDS 15, so the shares are not directly comparable.
Named in one category this edition.
Microsoft SNDS
accepted challengerBy Microsoft, Vancouver, Canada, founded 1975. 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 deliverability and testing tools page.
By framing
Mail-TesterFirst choices, of fourteen modelsMicrosoft SNDSAcross every category in the October 2026 Edition, Mail-Tester and Microsoft SNDS were named in the same answer nineteen times, of the 52 answers naming Mail-Tester and the 41 naming Microsoft SNDS. In those answers Microsoft SNDS took the first choice two times and Mail-Tester two.
Every model, every framing
| Model | DirectMS | ParaphraseMS | ComparativeMS | Budget-constrainedMS | Scale-constrainedMS | NegativeMS |
|---|---|---|---|---|---|---|
| Claude Haiku 4.5 | | |||||
| GPT-5.4 mini | ||||||
| Gemini 3.5 Flash | | | MS | |||
| Perplexity Sonar | MS | |||||
| Grok 4.1 Fast | | MS | ||||
| Mistral Small | MS | |||||
| DeepSeek V4 Flash | MS | MS | ||||
| Llama 4 Maverick | | |||||
| Qwen 3.7 Flash | MS | |||||
| Kimi K2 | | | ||||
| GLM 4.7 FlashX | MS | | ||||
| MiniMax M2.5 | | |||||
| GPT-6 Luna | | |||||
| Muse Glimmer 30B | MS | | |
Mail-TesterMS Microsoft SNDS first choice named as an alternative argued againstblank: not namedEach cell is one answer, Mail-Tester on the left and Microsoft SNDS on the right.The direct prompt
Neither was named
14 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
Mail-Tester5%#5 of 15Mail-Tester5%#5 of 12Mail-Tester0%#– of 14What the models said about Mail-Tester
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of eight in this category shown.
“Mail-Tester scores against a single seed address, so it can't tell you where your email lands across a multi-ISP seed network” Claude Haiku 4.5 · negative prompt · hard negative
“These are inaccurate and misleading... do not base business decisions on them.” DeepSeek V4 Flash · negative prompt · hard negative
“Avoid: Relying solely on these web-based scores. They are useful for a quick syntax check but should not be your primary deliverability testing tool.” GLM 4.7 FlashX · negative prompt · soft negative
“Mail-Tester for occasional pre-send checks of a message and its sending setup. It allows up to 3 free tests per day.” GPT-6 Luna · budget prompt · first choice
“The best email deliverability tool for a company with a limited budget is Mail-Tester or Unspam for pre-send testing” Llama 4 Maverick · budget prompt · first choice
“Start with free tools → Google Postmaster Tools + MXToolbox + Mail-Tester free tier” Kimi K2 · budget prompt · first choice
What the models said about Microsoft SNDS
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Three of four in this category shown.
“Set up Google Postmaster Tools (free) and Microsoft SNDS (free). These are the only tools that provide direct, unvarnished reputation data” Gemini 3.5 Flash · negative prompt · first choice
“Best free option: Stack Google Postmaster Tools, Microsoft SNDS, Yahoo Sender Hub, MXToolbox, Mail Tester, AboutMyEmail, and Sender Hub.” GLM 4.7 FlashX · budget prompt · first choice
“free monitoring stack with Google Postmaster Tools, Microsoft SNDS, MXToolbox, and Yahoo Sender Hub” Perplexity Sonar · 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.