GTM AI Index
Index Marketing Direct mail › Stannp vs PostGrid
Print · September 2026 Edition

Stannp vs PostGrid

Zero of twelve models named Stannp first on the direct prompt; zero named PostGrid. Stannp was named by nine of the twelve models and PostGrid by twelve and Stannp carries 21 labels and PostGrid 40, so the shares are not directly comparable.

Stannp

accepted challenger

Named in one category this edition.

PostGrid

criticized challenger

Named in one category this edition.

First-choice share7%7%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate0%25%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#3#4A position in a field of 11; printed, not drawn.
Labels2140A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, Stannp reading right to left. Rank and label count are printed, not drawn.Postalytics was named alongside these two in ten of the twelve direct answers. Postalytics vs Stannp · Postalytics vs PostGrid · Lob vs Stannp

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 print page.

By framing

How many of the twelve models made each the first choice, per way of asking, and how many argued against it.
StannpFirst choices, of twelve modelsPostGrid
Direct00
Paraphrase02
Comparative13
Budget-constrained302 against PostGrid
Scale-constrained01
Negative208 against PostGrid
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, Stannp and PostGrid were named in the same answer thirty-one times, of the 51 answers naming Stannp and the 110 naming PostGrid. In those answers PostGrid took the first choice three times and Stannp seven.

Every model, every framing

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

The direct prompt

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

Neither was the first choice, one was named

5 of 12 modelsThe answer put something else first and named one of the two as an alternative.
Claude Haiku 4.5PFL alternatives: PostGrid, Sendoso
Grok 4.1 FastPostalytics alternatives: Lob, PostGrid, Sendoso
Mistral SmallPostalytics alternatives: Lob, PostGrid, Sendoso
GLM 4.7 FlashXPostalytics alternatives: Lob, PostGrid, Postal, Reachdesk
MiniMax M2.5Postalytics alternatives: Lob, Postal, Sendoso, Stannp

Neither was named

7 of 12 modelsThe answer made no first choice from these two in this category.
GPT-5.4 miniSendoso alternatives: PFL
Gemini 3.5 FlashPostalytics, Reachdesk alternatives: Alyce, Lob, Postal
Perplexity SonarPostalytics alternatives: DirectMail.io, Lob, Sendoso
DeepSeek V4 FlashPostalytics alternatives: Lob, PFL, Reachdesk, Sendoso
Llama 4 MaverickPostalytics alternatives: Magileads
Qwen 3.7 FlashPostalytics alternatives: Click2Mail, LetterStream, Sendoso
Kimi K2Postalytics alternatives: Lob, PFL, Sendoso

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
Stannp leads by six points.
Stannp8%#4 of 9
PostGrid2%#6 of 9
The full small business standing →
Mid-marketThe figures above
Level: the same share of first choices.
Stannp7%#3 of 11
PostGrid7%#4 of 11
The full mid-market standing →
Enterprise
The order flips: PostGrid leads at enterprise.
PostGrid9%#4 of 9
Stannp0%#– of 9
The full enterprise standing →

What the models said about Stannp

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

“Start with Click2Mail (no monthly fees) or Stannp ($0-$12/month) to test direct mail without commitment.” Kimi K2 · budget prompt · first choice
“Safer Alternatives to Consider ... Stannp | Very low | 4.8/5 G2 rating, affordable pricing” Kimi K2 · negative prompt · first choice
“Stannp (4.8/5 on G2) – good address verification, tracking, and support” DeepSeek V4 Flash · negative prompt · first choice

What the models said about PostGrid

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

“Platforms to Avoid on a Tight Budget ... Postgrid — Cheaper API alternative ($0–99/mo), but pricing is often quote-based” DeepSeek V4 Flash · budget prompt · hard negative
“Avoid Lob ($260-$550/month) and PostGrid unless you need API-first development capabilities” Kimi K2 · budget prompt · hard negative
“Platforms to Avoid or Be Cautious About ... 1. Postgrid - Poor Customer Support” GLM 4.7 FlashX · negative prompt · hard negative
“PostGrid is best for revenue ops teams needing API-driven direct mail triggered by CRM events (rated 9.3/10 overall)” MiniMax M2.5 · comparative prompt · first choice
“Choose PostGrid or Lob if you want API-first, developer-controlled automation” Perplexity Sonar · comparative prompt · first choice
“I'd recommend starting with PostGrid due to its: Strong B2B focus” Mistral Small · paraphrase 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.