GTM AI Index
Index Vendors › Masset · September 2026 Edition
1 category · Ranked

Masset

31Judge labels
9First choices
1Negative labels
10 of 12Models named it
1Category
September 2026 Edition. Every number here is derived from the raw labels under vendor table v2026-09-16.3, every buyer segment counted.
Best standing
4% in DAM for mid-market buyers
Rank 5 of 68 in the mid-market standing
1 of 12 models made it the first choice on the direct prompt; 0% of its 6 labels there were negative.
By buyer segmentRead the same way at every buyer size.
In dam · 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 Masset 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
Digital asset managementMarketing4%5 of 680%6under 10 labels · led by Canto at 34%

Movement

This is the first edition on this tier, so no move can be computed for Masset 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 Masset across every prompt where it was named for a mid-market B2B company. Twelve models, six prompts per category.
ModelFirst choiceAlternativeMentionNegativeLabels
Claude Haiku 4.501001
GPT-5.4 mini00000
Gemini 3.5 Flash11002
Perplexity Sonar00000
Grok 4.1 Fast00000
Mistral Small01001
DeepSeek V4 Flash00000
Llama 4 Maverick10001
Qwen 3.7 Flash00000
Kimi K201001
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
Direct8 labels3
Paraphrase10 labels3
Comparative4 labelsNone
Budget-constrained7 labels3
Scale-constrained2 labelsNone
Negative0 labelsNone
First choiceAlternativeMentionNegative31 labels in all, every segment counted; 9 of the 9 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.

“Masset is an AI-ready DAM built for the decks, case studies, and spec sheets B2B teams actually use. It is the best home for business content” Llama 4 Maverick · DAM · paraphrase prompt · first choice
“Top Pick: Masset ... Masset is built specifically for "business content"” Gemini 3.5 Flash · DAM · direct prompt · first choice
“Best for SaaS, Tech, & Professional Services (Business-Content Heavy)” Gemini 3.5 Flash · DAM · paraphrase prompt · alternative
“AI-ready for business content (decks, case studies, spec sheets)” Kimi K2 · DAM · comparative prompt · alternative

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.

No model argued against it.

Named alongside

The products named in the same answers as Masset, over the 31 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and Masset was named but was not.
ProductSame answerTook the first choice insteadHead to head
Canto18 of 318Not in the top three
Aprimo11 of 315Not in the top three
Bynder11 of 314Not in the top three
Brandfolder11 of 311Not in the top three
Filecamp10 of 312Not in the top three
Acquia DAM9 of 311Not in the top three
Seismic9 of 311Not in the top three
MindTickle8 of 310Not in the top three
Highspot7 of 312Not in the top three
HubSpot Sales Hub6 of 315Not 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 Masset. 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 5 of the 31 answers that named Masset and are not a share of its labels.

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 Masset'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 Masset, 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 masset.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.