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

Stannp vs PFL

Zero of twelve models named Stannp first on the direct prompt; one named PFL. Stannp was named by nine of the twelve models and PFL by ten and Stannp carries 21 labels and PFL 23, so the shares are not directly comparable.

Stannp

accepted challenger

Named in one category this edition.

PFL

criticized challenger

Named in one category this edition.

First-choice share7%4%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate0%26%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#3#7A position in a field of 11; printed, not drawn.
Labels2123A 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 PFL · 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 modelsPFL
Direct011 against PFL
Paraphrase012 against PFL
Comparative10
Budget-constrained30
Scale-constrained00
Negative203 against PFL
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 PFL were named in the same answer seventeen times, of the 51 answers naming Stannp and the 63 naming PFL. In those answers PFL took the first choice one time and Stannp three.

Every model, every framing

The seventy-two answers behind the chart above, one cell each: where Stannp and PFL stood in it.
ModelDirectPFParaphrasePFComparativePFBudget-constrainedPFScale-constrainedPFNegativePF
Claude Haiku 4.5PFPF
GPT-5.4 miniPF
Gemini 3.5 Flash
Perplexity SonarPFPF
Grok 4.1 FastPFPF
Mistral SmallPF
DeepSeek V4 FlashPFPFPFPFPF
Llama 4 Maverick
Qwen 3.7 FlashPFPF
Kimi K2PFPFPF
GLM 4.7 FlashX
MiniMax M2.5
StannpPF PFL first choice named as an alternative argued againstblank: not namedEach cell is one answer, Stannp on the left and PFL on the right.

The direct prompt

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

PFL first, Stannp not the choice

1 of 12 modelsStannp was named in the answer but not as the choice, or not at all.
Claude Haiku 4.5PFL alternatives: PostGrid, Sendoso

Neither was the first choice, one was named

4 of 12 modelsThe answer put something else first and named one of the two as an alternative.
GPT-5.4 miniSendoso alternatives: PFL
DeepSeek V4 FlashPostalytics alternatives: Lob, PFL, Reachdesk, Sendoso
Kimi K2Postalytics alternatives: Lob, PFL, Sendoso
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.
Gemini 3.5 FlashPostalytics, Reachdesk alternatives: Alyce, Lob, Postal
Perplexity SonarPostalytics alternatives: DirectMail.io, Lob, Sendoso
Grok 4.1 FastPostalytics alternatives: Lob, PostGrid, Sendoso
Mistral SmallPostalytics alternatives: Lob, PostGrid, Sendoso
Llama 4 MaverickPostalytics alternatives: Magileads
Qwen 3.7 FlashPostalytics alternatives: Click2Mail, LetterStream, Sendoso
GLM 4.7 FlashXPostalytics alternatives: Lob, PostGrid, Postal, Reachdesk

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 eight points.
Stannp8%#4 of 9
PFL0%#– of 9
The full small business standing →
Mid-marketThe figures above
Stannp leads by two points.
Stannp7%#3 of 11
PFL4%#7 of 11
The full mid-market standing →
Enterprise
The order flips: PFL leads at enterprise.
PFL16%#2 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 PFL

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

“Takes significant time to launch campaigns... Pricing can be prohibitive for smaller teams” Kimi K2 · negative prompt · soft negative
“Primary Concerns: Operational Transparency & Speed ... "quote-only" pricing structures” Qwen 3.7 Flash · negative prompt · soft negative
“heavier setup and higher cost — generally more enterprise-oriented than "mid-sized."” DeepSeek V4 Flash · paraphrase prompt · soft negative
“PFL commands roughly 75% market share ... PFL suits mid-market and enterprise teams that prioritize print quality and deep, reliable integrations” Claude Haiku 4.5 · direct prompt · first choice
“Best Overall Recommendation: PFL” Claude Haiku 4.5 · paraphrase prompt · first choice
“Runner-up: PFL if you need more sophisticated B2B orchestration and multi-channel campaigns.” Mistral Small · paraphrase 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.