Index › IT › Products › Mage · November 2026 Edition
3 categories · Named, not ranked

Mage

Mage is a workflow orchestration tool for building data pipelines, including ETL, through a notebook-style visual interface · mage.ai ↗

–Too few to rank
5/14Models named it
0First choices
3Warnings
November 2026 Edition · all company sizes counted.
Ranked inWorkflow orchestration #26 mid-marketData security posture management #91ML platforms #120
What AI models recommend

Named, too few times to rank.

A product needs 10 labels in a category before a share is stated. Mage has 6.

Why models recommend it

“Choose Mage if you want a visual, less code-heavy experience for data pipelines.”GLM 4.7 FlashX · Comparative question · alternative
“The Lightweight Choice: Mage”Qwen 3.7 Flash · Paraphrase question · alternative

What gives them pause

“Vulnerabilities were broken down for projects including Weave, ZenML, Deep Lake, Vanna.AI, and Mage AI”Muse Glimmer 30B · Negative question · warning
“Niche (e.g., Slack/Zendesk-focused or AI-only) and may not cover end-to-end needs.”Grok 4.20 · Paraphrase question · warning
“great for quick prototyping but less robust for production at mid-scale”Grok 4.20 · Paraphrase question · warning

Also on the shortlist

The products named in the same answers as Mage, over the 9 answers that named it, and how often each was the first choice instead.

A side-by-side page exists where both products are among a category's top eight.

At a glance

Stated on Mage's own site, not checked by Gane.

For
data teams
Price stated
Starter: $29 / month + $0.50 per CPU-hour; Team: $100 / month + $0.50 per CPU-hour; Enterprise: Contact sales; Additional AI usage is $0.12 per credit.
Starting price
29
Free plan or trial
Start building free
Certifications
SOC 2 Type II
Visit mage.ai ↗

How this is measured

Fourteen AI models from 12 labs are asked the same buying questions six ways, for three company sizes. Standings refresh every edition.

Gane sells AI visibility software. No company can pay to change a result.

Read the method →

Sources returned with these answers

The sites and pages the answers that named Mage came back with. A fact about retrieval, not a cause of the answer.

Fourteen of the fourteen models returned a source list in this edition: five return the pages they cited and nine the search results they consulted. These counts come from 8 of the 9 answers that named Mage and are not a share of its labels.

By model

How each model answered on Mage across every prompt where it was named for a mid-market B2B company. Fourteen models, six prompts per category.
ModelFirst choiceAlternativeMentionWarningLabels
Claude Haiku 4.500000
GPT-5.4 mini00000
Gemini 3.5 Flash00000
Perplexity Sonar00000
Grok 4.2000123
Mistral Small00000
DeepSeek V4 Flash00000
Llama 4 Maverick00000
Qwen 3.7 Flash01001
Kimi K200000
GLM 4.7 FlashX01001
MiniMax M2.500000
GPT-6 Luna00000
Muse Glimmer 30B00011

What it publishes

Addresses on mage.ai
819
subdomains included
Content
321
counted in the table below
Documentation
358
Product · Integration
70 · 0
KindPagesLast 90 days2025-10 to 2026-09LatestCategories named
Blog15712026-09-01ETL, AI coding
Report or ebook100undated
Glossary or explainer55undated
Comparison802026-05-06
Case study102025-05-22
How it is countedHide how it is counted

Every page mage.ai exposes, subdomains included. Kind is read from the address and title. The last 90 days, the latest date and the twelve months count pages by when they were published, from the site's feeds, a date in the address, or the page's own publication date, read from up to a hundred of its most recently changed pages; a page that says only when it last changed is counted in its kind but not in when, so the recent counts are a floor, and a kind none of whose pages gives a publication date reads undated. Read September 29, 2026.