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Index › Products › Miro · October 2026 Edition
1 category · Named, not ranked

Miro

15Judge labels
0First choices
7Negative labels
6 / 14Models named it
1Category
October 2026 Edition. Every number here is derived from the raw labels under vendor table v2026-10.8, 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. Miro was named 3 times in EA tools, where SAP LeanIX led with 25%. The labels and the evidence are below, counted exactly.
By buyer segmentRead the same way at every buyer size.
In ea tools · 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 Miro 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 rateLabelsQuadrantSince September 2026
Enterprise architecture toolsIT operations and endpoint0%107 of 11367%3under 10 labels · led by SAP LeanIX at 25%

Movement

This is the first edition on this tier, so no move can be computed for Miro yet. From the next edition this section shows, per buyer segment and per category, whether its share moved by more than the measured noise floor.

By model

How each model treated Miro across every prompt where it was named for a mid-market B2B company. Fourteen models, six prompts per category.
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ModelFirst choiceAlternativeMentionNegativeLabels
Claude Haiku 4.500000
GPT-5.4 mini00000
Gemini 3.5 Flash00022
Perplexity Sonar00000
Grok 4.1 Fast00000
Mistral Small00000
DeepSeek V4 Flash00000
Llama 4 Maverick00000
Qwen 3.7 Flash00101
Kimi K200000
GLM 4.7 FlashX00000
MiniMax M2.500000
GPT-6 Luna00000
Muse Glimmer 30B00000

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 labelsNone
Paraphrase0 labelsNone
Comparative2 labelsNone
Budget-constrained1 labelNone
Scale-constrained3 labelsNone
Negative6 labelsNone
First choiceAlternativeMentionNegative15 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.

“they are *not* enterprise architecture tools because they lack a centralized, relational object repository” Gemini 3.5 Flash · EA tools · negative prompt · hard negative
“*Drawing tools* (like Lucidchart, Miro, or Visio) are purely visual.” Gemini 3.5 Flash · EA tools · scale prompt · soft negative

Named alongside

The products named in the same answers as Miro, over the 15 answers that named it. Took the first choice instead counts the answers where the other product was the first choice and Miro was named but was not.
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ProductSame answerTook the first choice insteadHead to head
Lucidchart12 of 150Not among the top eight
Archi9 of 155Not among the top eight
LeanIX8 of 152Not among the top eight
Ardoq8 of 150Not among the top eight
Bizzdesign Horizzon7 of 150Not among the top eight
IcePanel5 of 152Not among the top eight
MEGA HOPEX5 of 150Not among the top eight
SAP LeanIX5 of 150Not among the top eight
Structurizr5 of 150Not among the top eight
Excel3 of 150Not among the top eight
A head-to-head page exists where both products are among a category's top eight. 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 Miro. A fact about retrieval, not a lever on the model.

Citations exist only for the models that return a source list, five of the fourteen in this edition, so these counts come from 11 of the 15 answers that named Miro and are not a share of its labels.

Search and answers

Where Miro stands in Google search beside where it stands in the models' answers.
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In search

Google, US estimates
Searches for its name, Google
135,000 a month (“miro”)
AI search demand for its name, est.
3,760 a month
Its own site
No site of its own on file, so no site figures

In answers

This edition
Share of first choices
0%
rank 107 of 113 in EA tools
Segment leader
25%
SAP LeanIX
First choices
0 across its categories
Named in
15 answers
Its own site cited
No site on file to match

Search figures are US estimates from DataForSEO, read September 28, 2026; AI search demand is its modeled, directional estimate, not a count of queries to any assistant. The answers are this edition's. Two measurements side by side: neither is read as the cause of the other.

Names read as Miro

What the judge wrote, as written, with how often. The vendor table decides that these count as Miro; a claim can dispute any of them.
Miro + Plugin 1

Follow Miro

An email the morning each edition publishes: where this product moved, where it held, and by how much against the noise floor. One address, confirmed by a click; a stop link in every email.

Already following? Everything you follow, with a stop for each.

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 Miro'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 Miro, applied by version and listed in the change log; and a one-line description supplied by the vendor and marked as such.

What a new claim receivesHide what a new claim receives

A new claim receives the current edition's vendor brief for Miro by email, built from the raw record of the edition. It shows:

  • where Miro is named, by buyer and by framing, and which cells hold its first choices;
  • the claims the models make when they name it, ranked, with the strongest and the weakest quoted;
  • its vocabulary against the segment leader's, and the pages the models cited;
  • who was chosen in the answers that did not name Miro, and every reason the record gives;
  • a battlecard for each top rival: the head-to-head split, why they win, and the reservation quoted against them;
  • one page of published figures cleared to show a buyer.

A verification link goes to your work email; an address at the vendor's own domain is approved on the spot, any other is reviewed by hand. Your email is never published. Claiming gives no say over labels, shares, verdicts or which quotes appear.