GTM AI Index
Index Vendors › Reddit · September 2026 Edition
3 categories · Named, not ranked

Reddit

10Judge labels
0First choices
6Negative labels
7 of 12Models named it
3Categories
September 2026 Edition. Every number here is derived from the raw labels under vendor table v2026-09-16.3, every buyer segment counted.
Standing
3 labels, too few to rank
A product needs 10 labels in a category before a share or quadrant is stated. Reddit was named 3 times in Community and 2 other categories, where Higher Logic Vanilla led with 23%. The labels and the evidence are below, counted exactly.
By buyer segmentRead the same way at every buyer size.
In community · each standing computed within its segment · bars are 0 to 100 · the accent bar is the product's own best reading

Standing by category

Every category where a model named Reddit for a mid-market B2B company. Share is first choices across the direct, paraphrase, budget and scale prompts; rank is within every product named in that category.
CategoryFunctionShareRankNegative rateLabelsQuadrant
Community platformsCustomer0%47 of 740%1under 10 labels · led by Higher Logic Vanilla at 23%
Content marketing platformsMarketing0%125 of 159100%1under 10 labels · led by HubSpot Content Hub at 30%
Video advertisingMarketing0%106 of 121100%1under 10 labels · led by StackAdapt at 24%

Movement

This is the first edition on this tier, so no move can be computed for Reddit yet. The next is due October 1, 2026. From the next edition this section shows, per buyer segment, whether its share moved by more than the measured noise floor.

By model

How each model treated Reddit across every prompt where it was named for a mid-market B2B company. Twelve models, six prompts per category.
ModelFirst choiceAlternativeMentionNegativeLabels
Claude Haiku 4.500000
GPT-5.4 mini00000
Gemini 3.5 Flash00011
Perplexity Sonar00000
Grok 4.1 Fast00101
Mistral Small00000
DeepSeek V4 Flash00000
Llama 4 Maverick00000
Qwen 3.7 Flash00011
Kimi K200000
GLM 4.7 FlashX00000
MiniMax M2.500000

By framing

Which of the six questions produced the naming. By model says how often; this says asked what. The first-choice count on the right carries the marks of the models that produced it.
FramingLabels by classFirst choices
Direct0 labelsNone
Paraphrase0 labelsNone
Comparative0 labelsNone
Budget-constrained2 labelsNone
Scale-constrained0 labelsNone
Negative8 labelsNone
First choiceAlternativeMentionNegative10 labels in all, every segment counted; 0 of the 0 first choices count toward share, since the comparative and negative framings do not. The bar is one segment per label class, to scale within the framing.

What the models said for it

Verbatim evidence the judge attached to positive labels.

No positive label carried a quote.

And against it

Verbatim evidence attached to negative labels. A warning on a product with few labels is a warning; on a product with many, it is one voice among them.

“Reddit (High Risk of Backlash)... its user base is famously hostile to overt marketing” Gemini 3.5 Flash · Content marketing · negative prompt · soft negative
“Niche Success But High Barriers” Qwen 3.7 Flash · Video ads · negative prompt · soft negative

Named alongside

The products named in the same answers as Reddit, over the 10 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and Reddit was named but was not.
ProductSame answerTook the first choice insteadHead to head
Discord4 of 100Not in the top three
Facebook Groups4 of 100Not in the top three
Slack4 of 100Not in the top three
Discourse3 of 101Not in the top three
Circle3 of 100Not in the top three
Meta Ads3 of 100Not in the top three
Mighty Networks3 of 100Not in the top three
Bettermode2 of 102Not in the top three
YouTube Ads2 of 101Not in the top three
AdRoll2 of 100Not in the top three
A head-to-head page exists where both products are in a category's top three. The other rows are the same fact without a page behind them, so they link to the product instead.

What carried it into the answer

The sites and pages cited by the answers that named Reddit. A fact about retrieval, not a lever on the model.

Citations exist only for the models that return a source list, four of the twelve in this edition, so these counts come from 4 of the 10 answers that named Reddit and are not a share of its labels.

Domains cited

businessofapps.com2
fastercapital.com2
medium.com2
adcreate.com1
adroll.com1
adwave.com1
aisaspa.com1
astretchout.com1
blog.hubspot.com1
businessresearchinsights.com1

Thirteen of the thirteen domain citations in answers naming Reddit came from somebody else's page.

Pages cited

Pages are listed as the models cited them.

Names read as Reddit

What the judge wrote, as written, with how often. The vendor table decides that these count as Reddit; a claim can dispute any of them.
Reddit (subreddit) 1

The company

Reddit.
Website
reddit.com
Headquarters
San Francisco, United States
Founded
2005

From Wikidata, fetched September 14, 2026. These describe the company, not the product's standing, and a claimed page can dispute any of them. · Wikidata

Is this your product?

Claim this page

Claiming is free and changes nothing in the data. A claimed page shows a verified contact who is told when each edition publishes and when Reddit's standing changes by more than the noise floor; the right to propose corrections to the vendor table, meaning names the judge wrote that should or should not read as Reddit, applied by version and listed in the change log; and a one-line description supplied by the vendor and marked as such.

It does not get any change to labels, shares or verdicts, any preview, or any say over which quotes appear. A verification link goes to your work email; an address at reddit.com is approved on the spot, any other address is reviewed by hand.

Your name and company appear on the claimed page, or the company alone if you ask below. A title and a LinkedIn address appear there too if you give them, and are left off if you do not. Your email address is never published.