MathJax 2.7.5 icon

Websites using MathJax 2.7.5

MathJax is a cross-browser JavaScript library that displays mathematical notation in web browsers, using MathML, LaTeX and ASCIIMathML markup.

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2.6k live MathJax 2.7.5 sites, ready to export.

That's how many MathJax 2.7.5 websites are in VersionDB right now, each with its full tech stack, contact details, and social profiles.

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Every MathJax 2.7.5 website we detected in the United States.

Only sites where a personal, company-hosted email was found.

Sites with at least one personnel LinkedIn profile.

Start with the highest-traffic end of the dataset.

Limit results to MathJax 2.7.5 websites on .com domains.

Only sites where an organisation phone number was found.

Create your own

How many websites use MathJax 2.7.5?

We found MathJax 2.7.5 on 2,667 websites in our September 2026 crawl, across 66 countries.

Which countries use MathJax 2.7.5 the most?

By number of websites, the top countries are United States (15%, 400 sites), Japan (7%, 174 sites), China (4%, 105 sites), Germany (3%, 78 sites) and Russia (3%, 69 sites). Together they account for 31% of the 2,667 MathJax 2.7.5 sites we track. 59% of the sites are in English, and .io is the most used domain ending, on 33% of them.

Where are MathJax 2.7.5 websites hosted?

The networks carrying the most MathJax 2.7.5 sites are Fastly, Inc. (1,232 sites), Amazon.com, Inc. (258 sites) and Cloudflare, Inc. (192 sites).

What technologies are used with MathJax 2.7.5?

Across the 2,667 MathJax 2.7.5 sites we track, the technologies most often found alongside it are Cloudflare (96%, 2,551 sites), cdnjs (95%, 2,528 sites), jQuery (73%, 1,949 sites), Varnish (51%, 1,356 sites) and GitHub Pages (50%, 1,346 sites).

Deep Dive

Breakdown of MathJax 2.7.5 websites

What else they run, plus their language, hosting network, domain extension and country.

FAQ

Answers drawn from our latest crawl of MathJax 2.7.5 websites. Anything else, email us and we will look it up.

Through our own crawl, which checks each site's HTML, scripts and headers rather than relying on self-reported data.