GTM AI Index
Index Vendors › Qvidian · September 2026 Edition
2 categories · Named, not ranked

Qvidian

16Judge labels
1First choices
8Negative labels
8 of 12Models named it
2Categories
September 2026 Edition. Every number here is derived from the raw labels under vendor table v2026-09-16.3, every buyer segment counted.
Standing
4 labels, too few to rank
A product needs 10 labels in a category before a share or quadrant is stated. Qvidian was named 4 times in Proposals and 1 other category, where PandaDoc led with 49%. The labels and the evidence are below, counted exactly.
By buyer segmentRead the same way at every buyer size.
In proposals · 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 Qvidian 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
Proposal softwareRevenue operations0%63 of 7933%3under 10 labels · led by PandaDoc at 49%
Content marketing platformsMarketing0%148 of 159100%1under 10 labels · led by HubSpot Content Hub at 30%

Movement

This is the first edition on this tier, so no move can be computed for Qvidian 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 Qvidian 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 Flash00101
Perplexity Sonar00000
Grok 4.1 Fast00011
Mistral Small00000
DeepSeek V4 Flash00101
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
Direct3 labels1
Paraphrase0 labelsNone
Comparative3 labelsNone
Budget-constrained1 labelNone
Scale-constrained2 labelsNone
Negative7 labelsNone
First choiceAlternativeMentionNegative16 labels in all, every segment counted; 1 of the 1 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.

“Enterprise-Heavy (Avoid for Most Mid-Market): Kapost/Upland (~$3.5k+/mo, B2B ops but too pricey/implementation-heavy)” Grok 4.1 Fast · Content marketing · direct prompt · hard negative
“Enterprise Overkill (Avoid for Small Teams)” Qwen 3.7 Flash · Proposals · negative prompt · soft negative

Named alongside

The products named in the same answers as Qvidian, over the 16 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and Qvidian was named but was not.
ProductSame answerTook the first choice insteadHead to head
Loopio13 of 161Not in the top three
Responsive12 of 164Not in the top three
PandaDoc11 of 162Not in the top three
Proposify8 of 160Not in the top three
Qwilr7 of 161Not in the top three
Better Proposals6 of 163Not in the top three
Prospero3 of 161Not in the top three
Bonsai3 of 160Not in the top three
Canva3 of 160Not in the top three
Nusii3 of 160Not 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 Qvidian. 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 2 of the 16 answers that named Qvidian and are not a share of its labels.

Names read as Qvidian

What the judge wrote, as written, with how often. The vendor table decides that these count as Qvidian; a claim can dispute any of them.
Kapost/Upland 1
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 Qvidian'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 Qvidian, 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 qvidian.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.