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Usage share of web browsers
Usage share of web browsers
Usage share of web browsers
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Usage share of web browsers in April 2025 according to StatCounter
Yearly usage share of web browsers from 2009 to 2025 according to StatCounter

The usage share of web browsers is the portion, often expressed as a percentage, of visitors to a group of web sites that use a particular web browser.

Accuracy

[edit]

Measuring browser usage in the number of requests (page hits) made by each user agent can be misleading.

Overestimation

[edit]

Not all requests are generated by a user, as a user agent can make requests at regular time intervals without user input. In this case, the user's activity might be overestimated. Some examples:

  • Certain anti-virus products fake their user agent string to appear to be popular browsers. This is done to trick attack sites that might display clean content to the scanner, but not to the browser. The Register reported in June 2008 that traffic from AVG Linkscanner, using an IE6 user agent string, outstripped human link clicks by nearly 10 to 1.[1]
  • A user who revisits a site shortly after changing or upgrading browsers may be double-counted under some methods; overall numbers at the time of a new version's release may be skewed.[2]
  • Occasionally websites are written in such a way that they effectively block certain browsers. One common reason for this is that the website has been tested to work with only a limited number of browsers, and so the site owners enforce that only tested browsers are allowed to view the content, while all other browsers are sent a "failure" message, and instruction to use another browser.[3] Many of the untested browsers may still be otherwise capable of rendering the content. Sophisticated users who are aware of this may then "spoof" the user agent string in order to gain access to the site.
  • Firefox, Chrome, Safari, and Opera will, under some circumstances, fetch resources before they need to render them, so that the resources can be used faster if they are needed. This technique, prerendering or pre-loading, may inflate the statistics for the browsers using it because of pre-loading of resources which are not used in the end.[4]

Underestimation

[edit]

It is also possible to underestimate the usage share by using the number of requests, for example:

  • Firefox 1.5 (and other Gecko-based browsers) and later versions use fast Document Object Model (DOM) caching. JavaScript is executed on page load only from net or disk cache, but not if it is loaded from DOM cache. This can affect JavaScript-based tracking of browser statistics.[5]
  • While most browsers generate additional page hits by refreshing web pages when the user navigates back through page history, some browsers (such as Opera) reuse cached content without resending requests to the server.[6][7]
  • Generally, the more faithfully a browser implements HTTP's cache specifications, the more it will be under-reported relative to browsers that implement those specifications poorly.[7]
  • Browser users may run site, cookie and JavaScript blockers which cause those users to be under-counted. For example, common AdBlock blocklists such as EasyBlock include sites such as StatCounter in their privacy lists, and NoScript blocks all JavaScript by default. The Firefox Add-ons website reports 15.0 million users of AdBlock variants and 2.2 million users of NoScript.
  • Users behind a caching proxy (e.g. Squid) may have repeat requests for certain pages served to the browser from the cache, rather than retrieving it again via the Internet.

User agent spoofing

[edit]

Websites often include code to detect the browser version to adjust the page design sent according to the user agent string received. This may mean that less popular browsers are not sent complex content (even though they might be able to deal with it correctly) or, in extreme cases, refused all content.[8] Thus, various browsers have a feature to cloak or spoof their identification to force certain server-side content.

  • Default user agent strings of most browsers have pieces of strings from one or more other browsers, so that if the browser is unknown to a website, it can be identified as one of those. For example, Safari has not only "Mozilla/5.0", but also "KHTML" (from which Safari's WebKit was forked) and "Gecko" (the engine of Firefox).
  • Some Linux browsers such as GNOME Web identify themselves as Safari in order to aid compatibility.[9][10]

Differences in measurement

[edit]

Net Applications, a web analytics firm, in their NetMarketShare report, uses unique visitors to measure web usage.[11] The effect is that users visiting a site ten times will only be counted once by these sources, while they are counted ten times by statistics companies that measure page hits. The statistics released by the company routinely place operating systems sold by Microsoft (Windows) and Apple (Mac OS X) with a high market share in the desktop computer category (through 2013). Vincent Vizzaccaro (EVP – Marketing and Strategic Alliances, Net Applications, 2002–present) has stated that Microsoft and Apple are among the company's clients.[12] The company has also admitted that their statistics are skewed.[13]

Net Applications uses country-level weighting as well.[14] The goal of weighting countries based on their usage is to mitigate selection area based sampling bias. This bias is caused by the differences in the percentage of tracked hits in the sample, and the percentage of global usage tracked by third party sources. This difference is caused by the heavier levels of market usage.[15]

Statistics from the United States government's Digital Analytics Program (DAP) do not represent world-wide usage patterns. DAP uses raw data from a unified Google Analytics account.

Summary tables

[edit]

The following tables summarize the usage share of all browsers for the indicated months.

Usage share of all browsers
Browser NetMarketShare[16]
October 2024 		StatCounter[17]
August 2025 		Wikimedia[18]
May 2025 		Cloudflare[19] May 2025
Chrome 66.64% 69.26% 56.2% 68%
Safari 13.92% 14.98% 24.1% 20%
Edge 4.55% 4.99% 5.11% 5.7%
Firefox 2.18% 2.26% 5.83% 3.6%
Samsung Internet 3.04% 1.97% 1.9% 1.8%
Opera 3.02% 1.85% 0.92% 1.5%
Others — 4.69% — —
Usage share of desktop browsers
Browser W3Counter[20]
October 2024		 NetMarketShare[21]
October 2024		 StatCounter[22]
October 2024		 Wikimedia[23]
October 2024
Chrome 68.6% 79.44% 65.24% 56.1%
Safari 15.2% 3.31% 9.06% 9.4%
Edge 3.7% 12.19% 13.56% 11.6%
Firefox 2.8% 3.27% 6.39% 15.3%
Opera 1.1% 0.67% 3.2% 2.4%
Others — — 2.55% —
Usage share of mobile browsers
Browser NetMarketShare[24]
October 2024 		StatCounter[25]
October 2024		 Wikimedia[26]
October 2024
Chrome 55.78% 68% 51.4%
Safari 33.11% 23.01% 31.9%
Samsung Internet 2.70% 3.62% 3.5%
UC 0.13% 1.37% 0.1%
Opera 0.49% 1.64% 0.6%
Firefox 0.37% 0.51% 1.6%
Others — 0.68% —
Usage share of tablet browsers
Browser NetMarketShare[27]

October 2024

Statcounter[28]

October 2024

Chrome 14.90% 50.56%
Safari 84.83% 33.4%
AOSP — 13.3%
Edge — 0.95%
Opera — 0.78%
Others — 1.02%

Crossover to smartphones having majority share

[edit]
See also: Usage share of operating systems § Crossover to smartphones having majority share

According to StatCounter web use statistics (a proxy for all use), in the week from 7–13 November 2016, "mobile" (meaning smartphones) alone (without tablets) overtook desktop for the first time and by the end of the year smartphones were in the majority. Since 27 October, the desktop has not shown a majority, even on weekdays.

Previously, according to StatCounter press release, the world has become desktop-minority;[29] as of October 2016, there was about 49% of desktop usage for that month. The two biggest continents, Asia and Africa, have been mobile-majority for a while, and Australia is by now desktop-minority too.[30][31] A few countries in Europe and South America have also followed this trend of being mobile-majority.

In March 2015, for the first time in the US the number of mobile-only adult internet users exceeded the number of desktop-only internet users with 11.6% of the digital population only using mobile compared to 10.6% only using desktop; this also means the majority, 78%, use both desktop and mobile to access the internet.[32]

Older reports (2000–2019)

[edit]

StatCounter (Jan 2009 to October 2019)

[edit]
Usage share of web browsers according to StatCounter from 2008-07 to 2019-05

StatCounter statistics are directly derived from hits (not unique visitors) from 3 million sites using StatCounter totaling more than 15 billion hits per month.[33] No weightings are used.

Global Desktop stats from StatCounter (Top 5 browsers)
Date
 Chrome

 Firefox

 Safari

 Internet
Explorer
 Edge
Legacy
 Other

 Mobile

October 2019 68.91% 9.25% 8.68% 4.45% 4.51% 4.20% 54.07%
September 2019 69.08% 9.54% 7.41% 4.99% 4.71% 4.27% 53.75%
August 2019 71.15% 9.52% 5.80% 4.40% 4.71% 4.43% 53.66%
July 2019 71.05% 9.52% 5.41% 5.00% 4.60% 4.41% 53.08%
June 2019 70.71% 9.76% 5.64% 5.03% 4.50% 4.36% 52.69%
May 2019 69.09% 10.01% 7.25% 5.14% 4.32% 4.21% 49.40%
April 2019 69.55% 9.78% 6.91% 5.16% 4.37% 4.23% 50.27%
March 2019 69.52% 9.58% 6.46% 5.44% 4.56% 4.44% 51.01%
February 2019 71.58% 8.72% 5.77% 5.34% 4.34% 4.24% 49.87%
January 2019 70.88% 9.50% 5.15% 5.74% 4.41% 4.32% 51.09%
December 2018 70.95% 10.05% 5.06% 5.40% 4.17% 4.38% 50.97%
November 2018 72.38% 9.10% 5.06% 5.38% 4.00% 4.07% 45.91%
October 2018 69.64% 10.14% 5.61% 6.01% 4.21% 4.38% 50.22%
September 2018 67.88% 10.94% 5.58% 6.45% 4.36% 4.78% 53.95%
August 2018 67.66% 10.96% 5.13% 6.97% 4.24% 5.03% 54.80%
July 2018 67.60% 11.23% 5.01% 6.97% 4.19% 5.00% 55.12%
June 2018 66.87% 11.44% 5.38% 7.13% 4.16% 5.02% 54.62%
May 2018 66.93% 11.55% 5.48% 6.97% 4.15% 4.92% 54.11%
April 2018 66.17% 11.78% 5.48% 7.17% 4.26% 5.14% 53.42%
March 2018 66.93% 11.60% 5.37% 7.02% 4.18% 4.90% 53.80%
February 2018 67.49% 11.54% 5.42% 6.91% 4.04% 4.60% 54.02%
January 2018 65.98% 11.87% 5.87% 7.28% 4.11% 4.88% 54.20%
December 2017 64.72% 12.21% 6.29% 7.71% 4.18% 4.88% 54.81%
November 2017 64.02% 12.55% 6.08% 8.47% 4.29% 4.59% 52.27%
October 2017 63.60% 13.04% 5.89% 8.34% 4.43% 4.69% 53.19%
September 2017 63.98% 13.60% 5.46% 8.21% 4.30% 4.46% 54.71%
August 2017 63.58% 13.73% 5.51% 8.61% 3.95% 4.61% 55.18%
July 2017 63.48% 13.82% 5.04% 9.03% 3.95% 4.68% 56.70%
June 2017 63.23% 13.98% 5.15% 9.28% 3.89% 4.47% 55.69%
May 2017 63.36% 14.17% 5.25% 9.20% 3.74% 4.28% 54.25%
April 2017 63.45% 14.53% 5.20% 9.00% 3.71% 4.11% 54.58%
March 2017 62.81% 14.97% 5.28% 9.39% 3.64% 3.92% 53.36%
February 2017 62.95% 14.81% 5.34% 9.62% 3.68% 3.60% 52.37%
January 2017 62.09% 14.85% 5.28% 10.49% 3.58% 3.71% 52.28%
July 2016 62.38% 15.43% 4.59% 10.67% 3.04% 3.85% 47.18%
Date
 Chrome

 Internet
Explorer
 Firefox

 Safari

 Opera

 Other

 Mobile

January 2016 57.75% 16.00% 15.95% 4.60% 2.03% 3.68% 41.04%
July 2015 55.39% 18.86% 17.24% 4.70% 1.91% 1.90% 39.46%
January 2015 51.72% 21.16% 18.70% 4.94% 1.67% 1.81% 33.24%
July 2014 48.69% 22.52% 19.25% 4.89% 1.45% 2.19% 29.48%
January 2014 46.60% 24.65% 20.39% 5.09% 1.32% 1.96% 23.77%
July 2013 45.40% 26.50% 21.31% 4.80% 1.11% 1.32% 17.35%
January 2013 38.08% 32.25% 22.47% 5.12% 1.22% 0.86% 14.13%
July 2012 33.81% 32.04% 23.73% 7.12% 1.72% 1.58% 11.09%
January 2012 28.40% 37.45% 24.78% 6.62% 1.95% 0.79% 8.49%
July 2011 22.14% 42.45% 27.95% 5.14% 1.66% 0.63% 7.02%
January 2011 15.68% 46.00% 30.68% 5.09% 2.00% 0.55% 4.30%
July 2010 9.88% 52.68% 30.69% 4.09% 1.91% 0.74% 2.86%
January 2010 6.04% 55.25% 31.64% 3.76% 2.00% 1.31% 1.56%
July 2009 3.01% 60.11% 30.50% 3.02% 2.64% 0.72% 1.05%
January 2009 1.38% 65.41% 27.03% 2.57% 2.92% 0.70% 0.67%

W3Counter (May 2007 to December 2022)

[edit]

This site counts the last 15,000 page views from each of approximately 80,000 websites. This limits the influence of sites with more than 15,000 monthly visitors on the usage statistics. W3Counter is not affiliated with the World Wide Web Consortium (W3C).

Global Web Stats from W3Counter
Date Google Chrome Safari Internet Explorer & Edge Firefox Opera
December 2022 71.2% 15.1% 3.7% 3.0% 1.3%
November 2022 67.9% 17.2% 4.2% 3.3% 1.5%
October 2022 66.7% 17.7% 4.4% 3.2% 1.5%
September 2022 69.2% 15.6% 4.2% 3.4% 1.2%
August 2022 69.9% 15.7% 3.7% 3.5% 1.1%
July 2022 68.7% 16.9% 3.4% 3.6% 1.3%
June 2022 68.3% 16.3% 3.3% 3.8% 1.3%
May 2022 71.6% 15.2% 3.8% 2.6% 1.1%
April 2022 70.2% 15.4% 4.8% 2.8% 1.1%
March 2022 64.9% 15.4% 6.3% 4.1% 2.5%
February 2022 67.9% 16.2% 5.5% 3.2% 1.4%
January 2022 64.4% 17.0% 6.1% 4.0% 1.4%
December 2021 66.0% 16.9% 5.2% 3.2% 1.5%
November 2021 66.6% 16.4% 5.2% 3.2% 1.3%
October 2021 65.4% 16.5% 5.9% 3.6% 1.2%
September 2021 63.3% 17.7% 5.4% 5.8% 1.3%
August 2021 62.9% 17.7% 4.9% 4.8% 1.1%
July 2021 65.7% 16.6% 4.7% 2.9% 1.1%
June 2021 65.3% 16.7% 5.2% 3.3% 1.4%
May 2021 65.2% 16.6% 4.9% 3.2% 1.4%
April 2021 65.3% 16.7% 5.7% 4.1% 1.6%
March 2021 65.2% 17.5% 5.6% 4.4% 1.6%
February 2021 65.3% 17.1% 5.6% 4.3% 1.5%
January 2021 65.3% 17.0% 5.6% 4.1% 1.5%
December 2020 65.3% 16.7% 5.5% 4.4% 1.5%
November 2020 66.1% 17.1% 5.3% 4.5% 1.5%
October 2020 63.8% 17.9% 5.6% 4.6% 1.6%
September 2020 62.6% 18.0% 6.3% 4.8% 1.6%
August 2020 61.8% 17.3% 7.1% 4.8% 1.5%
July 2020 61.0% 16.1% 8.9% 5.0% 1.6%
June 2020 63.0% 14.4% 8.0% 5.1% 1.8%
May 2020 63.7% 13.6% 6.3% 4.5% 2.1%
April 2020 62.4% 12.2% 7.0% 4.6% 2.5%
March 2020 59.3% 12.3% 9.1% 4.5% 3.0%
February 2020 58.1% 13.0% 12.9% 5.4% 2.7%
January 2020 58.2% 17.7% 7.1% 5.5% 2.6%
December 2019 56.1% 18.1% 7.5% 5.5% 3.7%
November 2019 59.2% 14.6% 9.6% 6.1% 3.5%
October 2019 57.0% 13.4% 9.4% 6.9% 3.3%
September 2019 58.7% 12.5% 8.1% 6.3% 3.0%
August 2019 56.8% 12.3% 7.8% 5.3% 2.1%
July 2019 55.4% 12.5% 8.6% 6.5% 2.8%
June 2019 56.8% 13.3% 8.1% 6.8% 2.4%
May 2019 57.4% 13.5% 6.8% 6.8% 2.4%
April 2019 60.1% 12.7% 6.8% 6.1% 2.8%
March 2019 65.4% 13.6% 6.2% 6.3% 3.0%
February 2019 63.9% 14.1% 7.1% 6.5% 3.1%
January 2019 64.5% 14.3% 7.0% 6.3% 3.0%
December 2018 64.4% 14.6% 7.2% 6.3% 3.0%
November 2018 64.7% 14.2% 7.4% 6.7% 3.0%
October 2018 61.7% 13.1% 6.6% 6.5% 2.8%
September 2018 62.2% 13.4% 6.3% 7.1% 3.0%
August 2018 60.3% 13.1% 6.7% 7.2% 3.1%
July 2018 57.8% 14.0% 5.9% 6.0% 3.7%
June 2018 55.2% 13.5% 6.1% 5.4% 3.2%
May 2018 56.6% 14.7% 7.1% 6.5% 3.5%
April 2018 58.8% 14.6% 6.9% 6.4% 3.5%
March 2018 60.6% 15.4% 7.6% 7.2% 2.9%
February 2018 59.9% 15.7% 7.3% 8.5% 3.4%
January 2018 58.4% 15.3% 7.8% 9.1% 3.9%
December 2017 58.8% 14.5% 8.0% 9.3% 4.0%
November 2017 59.2% 14.3% 8.1% 9.3% 4.0%
October 2017 58.8% 13.4% 9.8% 9.1% 3.2%
September 2017 57.0% 13.2% 11.2% 9.1% 3.2%
August 2017 56.8% 14.9% 9.1% 8.1% 5.0%
July 2017 64.0% 13.6% 8.0% 6.8% 3.2%
June 2017 62.4% 13.5% 8.9% 7.8% 3.2%
May 2017 58.1% 14.9% 9.7% 9.0% 3.0%
April 2017 61.2% 15.9% 8.2% 6.3% 2.9%
March 2017 58.9% 15.2% 7.2% 7.2% 3.8%
February 2017 57.2% 13.2% 8.5% 9.0% 5.0%
January 2017 58.4% 13.3% 8.1% 9.5% 4.4%
July 2016 59.5% 13.1% 10.2% 10.1% 2.6%
January 2016 47.3% 20.7% 12.3% 11.4% 3.2%
July 2015 46.5% 16.5% 13.6% 13.3% 3.9%
January 2015 43.2% 15.2% 17.3% 15.3% 3.1%
July 2014 38.7% 15.4% 21.3% 15.3% 3.1%
January 2014 34.3% 17.9% 20.4% 18.4% 2.7%
July 2013 33.4% 15.2% 23.0% 19.1% 2.4%
January 2013 30.1% 14.8% 27.6% 20.1% 2.3%
July 2012 28.5% 13.4% 28.7% 23.2% 2.2%
January 2012 25.3% 6.7% 31.8% 25.5% 2.5%
July 2011 20.2% 6.6% 36.6% 28.5% 2.4%
January 2011 14.6% 6.0% 41.1% 31.9% 2.1%
July 2010 10.6% 2.1% 48.3% 34.1% 2.3%
January 2010 6.4% 5.5% 50.6% 32.9% 2.2%
July 2009 3.4% 4.8% 54.4% 32.4% 1.8%
January 2009 0.2% 2.8% 60.2% 32.1% 2.0%
July 2008 2.5% 62.3% 30.4% 2.1%
January 2008 2.8% 63.1% 29.1% 2.0%
July 2007 2.2% 66.9% 25.1% 1.8%
May 2007 2.4% 67.7% 25.0% 1.8%
Date Google Chrome Safari Internet Explorer Firefox Opera

Net Applications (May 2016 to November 2019)

[edit]

Net Applications bases its usage share on statistics from 40,000 websites having around 160 million unique visitors per month. The mean site has 1300 unique visitors per day.

Global usage share of desktop browsers data from: Net Applications
Period
 Chrome

 Firefox

 Internet
Explorer
 Edge
Legacy
 Safari

 Sogou
Explorer
 QQ

 Opera

 Yandex

 UC

November 2019 67.15% 8.15% 6.81% 5.97% 5.29% 1.78% 1.66% 1.28% 0.81% 0.40%
October 2019 67.38% 8.62% 6.47% 6.10% 4.82% 1.83% 1.66% 1.32% 0.84% 0.31%
September 2019 68.33% 8.68% 6.30% 5.93% 4.26% 1.59% 1.45% 1.42% 0.98% 0.34%
August 2019 68.60% 8.43% 7.50% 6.34% 3.85% 1.72% 1.58% 1.39% 0.86% 0.26%
July 2019 67.22% 8.34% 7.44% 5.80% 3.40% 1.70% 1.52% 1.43% 0.88% 0.34%
June 2019 66.29% 8.86% 7.30% 6.03% 3.32% 1.35% 1.30% 1.54% 0.87% 0.32%
May 2019 67.90% 9.46% 7.70% 5.36% 3.30% 1.47% 1.33% 1.52% 0.95% 0.39%
April 2019 65.64% 10.23% 8.44% 5.53% 3.58% 1.63% 1.40% 1.57% 0.89% 0.37%
March 2019 67.88% 9.27% 7.34% 5.20% 3.69% 1.50% 1.33% 1.65% 0.97% 0.44%
February 2019 66.89% 9.39% 8.23% 4.79% 3.56% 1.49% 1.60% 1.63% 0.83% 0.46%
January 2019 67.29% 9.92% 7.94% 4.61% 4.00% 1.24% 1.31% 1.60% 0.80% 0.44%
December 2018 67.18% 9.58% 8.31% 4.09% 3.71% 1.69% 1.71% 1.68% 0.68% 0.51%
November 2018 65.57% 8.96% 9.64% 4.22% 3.74% 1.73% 1.68% 1.56% 0.67% 0.55%
October 2018 66.43% 9.25% 9.48% 4.28% 3.74% 1.43% 1.53% 1.55% 0.63% 0.49%
September 2018 66.28% 9.62% 9.94% 4.08% 3.59% 1.23% 1.20% 1.61% 0.59% 0.60%
August 2018 65.21% 9.76% 10.86% 4.30% 3.65% 1.15% 1.14% 1.66% 0.64% 0.52%
July 2018 64.67% 9.68% 11.15% 4.21% 3.49% 1.49% 1.55% 1.58% 0.46% 0.60%
June 2018 62.77% 10.12% 12.22% 4.25% 3.70% 1.45% 1.49% 1.58% 0.56% 0.59%
May 2018 62.85% 9.92% 11.82% 4.26% 3.71% 1.47% 1.55% 1.67% 0.58% 0.75%
April 2018 61.77% 10.52% 12.20% 4.46% 3.94% 1.60% 1.72% 1.50% 0.72% 0.80%
March 2018 61.77% 10.52% 12.20% 4.46% 3.94% 1.49% 1.38% 1.45% 0.65% 0.66%
February 2018 61.55% 11.15% 11.66% 4.44% 4.39% 1.32% 1.21% 1.73% 0.72% 0.63%
January 2018 61.41% 10.85% 11.84% 4.67% 4.18% 1.64% 1.20% 1.60% 0.62% 0.71%
December 2017 60.57% 11.02% 12.36% 4.61% 4.00% 1.79% 1.47% 1.56% 0.58% 0.76%
November 2017 60.61% 11.42% 12.04% 4.21% 3.85% 1.84% 1.53% 1.51% 0.77% 0.78%
October 2017 59.99% 11.71% 12.25% 4.06% 3.78% 1.92% 1.80% 1.41% 0.55% 0.70%
September 2017 60.67% 13.26% 11.80% 3.71% 3.54% 1.70% 1.28% 1.38% 0.55% 0.66%
August 2017 61.05% 12.26% 12.07% 3.67% 3.14% 1.74% 1.70% 1.52% 0.59% 0.74%
July 2017 59.65% 12.59% 12.96% 3.78% 3.22% 1.72% 1.64% 1.58% 0.61% 0.82%
June 2017 60.08% 12.53% 12.75% 3.80% 3.24% 1.66% 1.40% 1.55% 0.66% 0.97%
May 2017 58.92% 12.90% 12.91% 3.97% 3.38% 1.81% 1.32% 1.56% 0.91% 0.78%
April 2017 55.95% 13.13% 14.41% 3.97% 3.35% 1.86% 1.98% 1.77% 1.29% 0.72%
March 2017 55.81% 15.50% 14.61% 3.63% 3.26% 1.69% 0.96% 1.93% 0.38% 0.78%
February 2017 59.17% 14.88% 11.82% 3.22% 3.13% 1.32% 0.84% 1.59% 0.52% 0.61%
January 2017 56.65% 15.56% 14.93% 3.32% 3.43% 1.33% 0.85% 1.41% 0.36% 0.52%
July 2016 55.50% 15.27% 14.79% 2.97% 4.57% 1.34% 0.79% 1.61% 0.86% 0.32%
May 2016 56.20% 14.79% 14.89% 2.31% 4.67% 1.05% 0.60% 2.95% 0.50% 0.31%

Wikimedia (April 2009 to March 2015)

[edit]
Usage in Wikimedia during 2012

Wikimedia traffic analysis reports are based on server logs of about 4 billion page requests per month, based on the user agent information that accompanied the requests.[34] These server logs cover requests to all the Wikimedia Foundation projects, including Wikipedia, Wikimedia Commons, Wiktionary, Wikibooks, Wikiquote, Wikisource, Wikinews, Wikiversity and others.[35]

Note: Wikimedia has recently[when?] had a large percentage of unrecognised browsers, previously counted as Firefox, that are now assumed to be Internet Explorer 11 fixed in the February 2014 and later numbers. And February 2014 numbers include mobile for Internet Explorer and Firefox (not included in Android). Chrome did not include the mobile numbers at that time while Android does since there was an "Android browser" that was the default browser at that time.

Usage share data from Wikimedia visitor log analysis report: All Requests
Period Chrome
 Firefox
 Internet
Explorer 		Safari Opera Android
 Mobile
Total
Desktop Mobile Total Desktop Mobile Total
March 2015 29.61% 14.23% 10.86% 2.97% 16.68% 19.65% 0.65% 1.41% 2.06% 17.45% 38.37%
February 2014 Archived 18 March 2014 at the Wayback Machine 27.94% 12.00% 17.01% 3.83% 17.97% 21.80% 1.50% 1.27% 2.77% 12.59% 35.03%
January 2014 27.32% 18.15% 11.78% 3.88% 19.41% 23.29% 1.51% 1.32% 2.83% 12.89% 35.01%
December 2013 30.70% 17.90% 11.48% 3.45% 18.03% 21.48% 1.54% 1.32% 2.86% 11.52% 32.20%
November 2013 35.04% 17.37% 13.80% 2.52% 15.17% 17.69% 1.49% 1.16% 2.65% 9.45% 26.99%
October 2013 33.93% 16.12% 15.46% 2.36% 14.34% 16.70% 1.53% 1.17% 2.70% 9.00% 26.32%
August 2013 31.07% 17.17% 15.98% 2.69% 15.92% 18.61% 1.87% 1.14% 3.01% 9.18% 28.25%
July 2013 32.33% 16.90% 15.65% 2.63% 15.66% 18.29% 2.06% 1.18% 3.24% 8.56% 27.38%
June 2013 35.16% 17.83% 15.93% 2.37% 13.13% 15.50% 2.18% 1.10% 3.28% 6.45% 22.32%
May 2013 35.23% 17.79% 16.99% 2.19% 12.63% 14.82% 2.41% 1.14% 3.55% 6.32% 21.83%
April 2013 34.16% 18.16% 16.95% 2.31% 13.61% 15.92% 2.42% 1.18% 3.60% 6.55% 23.13%
March 2013 33.22% 16.28% 17.03% 4.34% 13.59% 17.93% 2.55% 1.18% 3.73% 6.51% 23.13%
February 2013 32.21% 16.80% 18.27% 4.56% 13.06% 17.62% 2.57% 1.21% 3.78% 6.25% 22.44%
January 2013 31.34% 17.61% 18.68% 4.64% 12.66% 17.30% 2.72% 1.16% 3.88% 6.01% 21.71%
July 2012 Archived 21 August 2012 at the Wayback Machine 27.20% 19.23% 23.70% 4.88% 10.60% 15.48% 3.00% 1.50% 4.50% 4.55% 18.19%
January 2012 Archived 23 July 2012 at the Wayback Machine 22.20% 22.30% 29.51% 5.87% 7.58% 13.45% 3.94% 1.21% 5.15% 3.21% 13.40%
July 2011[dead link] 16.81% 24.98% 36.78% 5.44% 5.31% 10.75% 3.32% 0.90% 4.22% 1.71% 9.80%
January 2011 Archived 28 February 2011 at the Wayback Machine 11.75% 28.71% 41.56% 5.53% 3.73% 9.26% 3.55% 0.70% 4.25% 0.90% 6.90%
Usage share data from Wikimedia visitor log analysis report
Period
 Internet
Explorer
 Firefox

 Chrome

 Safari

 Opera

 Other
Mozilla
 Mobile

December 2010 Archived 16 January 2011 at the Wayback Machine 42.12% 28.82% 11.18% 5.70% 3.67% 0.52% 6.4%
July 2010 Archived 11 August 2011 at the Wayback Machine 47.74% 30.43% 7.52% 5.18% 2.89% 0.53% 4.5%
January 2010 Archived 11 March 2011 at the Wayback Machine 51.01% 30.85% 4.81% 5.13% 3.18% 0.56% 3.1%
July 2009 Archived 11 August 2011 at the Wayback Machine 54.55% 31.52% 2.77% 4.51% 2.38% 0.70% 2.4%
April 2009 Archived 10 August 2011 at the Wayback Machine 57.37% 30.71% 1.93% 3.86% 2.57% 0.68% 1.9%

Clicky (September 2009 to August 2013)

[edit]
Global usage share data from GetClicky.com
Period
 Internet
Explorer
 Chrome

 Firefox

 Safari

 Opera

 Other Mozilla

August 2013 28.76% 39.48% 20.86% 9.55% 1.04% 0.31%
July 2013 28.64% 39.44% 21.27% 9.19% 1.14% 0.31%
June 2013 29.08% 38.92% 21.22% 9.28% 1.17% 0.32%
May 2013 29.14% 38.39% 21.19% 9.86% 1.13% 0.29%
April 2013 30.57% 37.12% 21.36% 9.48% 1.22% 0.27%
March 2013 31.92% 35.83% 21.29% 9.52% 1.21% 0.24%
February 2013 33.10% 34.57% 21.40% 9.51% 1.21% 0.20%
January 2013 35.67% 32.79% 20.79% 9.41% 1.16% 0.19%
July 2012 35.77% 29.87% 23.61% 9.18% 1.43% 0.13%
January 2012 38.59% 25.75% 24.74% 9.55% 1.28% 0.09%
July 2011 42.06% 20.25% 27.35% 9.07% 1.20% 0.07%
January 2011 46.00% 15.25% 28.74% 8.62% 1.27% 0.12%
July 2010 49.26% 10.53% 30.88% 7.89% 1.26% 0.18%
January 2010 50.73% 6.85% 32.89% 7.79% 1.51% 0.23%
September 2009 54.58% 4.25% 31.96% 7.44% 1.34% 0.43%

StatOwl.com (September 2008 to November 2012)

[edit]
US usage share data from StatOwl.com Archived 16 March 2016 at the Wayback Machine [36]
Period
 Internet
Explorer
 Firefox,
Other Mozilla
 Chrome

 Safari

 Opera

 Gecko

 Netscape
Navigator
November 2012 Archived 13 January 2015 at the Wayback Machine [37] 43.38% 19.42% 24.91% 9.27% 0.75% 0.84%
October 2012 Archived 13 January 2015 at the Wayback Machine [38] 44.40% 19.62% 24.09% 9.42% 0.68% 0.55%
September 2012 Archived 13 January 2015 at the Wayback Machine [39] 45.03% 19.26% 23.31% 9.84% 0.65% 0.78%
August 2012 Archived 13 January 2015 at the Wayback Machine [40] 45.87% 19.49% 22.53% 10.14% 0.59% 0.43%
July 2012 Archived 2 April 2016 at the Wayback Machine [41] 46.95% 19.03% 22.31% 9.96% 0.52% 0.36%
June 2012 Archived 4 April 2016 at the Wayback Machine [42] 46.69% 19.42% 21.76% 9.80% 0.55% 0.30%
May 2012 Archived 13 January 2015 at the Wayback Machine [43] 46.47% 20.47% 20.88% 10.04% 0.55% 0.30%
April 2012 Archived 6 April 2016 at the Wayback Machine [44] 48.28% 19.73% 19.39% 10.51% 0.44% 0.27%
March 2012 Archived 3 April 2016 at the Wayback Machine [45] 49.18% 19.46% 18.10% 11.14% 0.38% 0.29%
February 2012 Archived 4 April 2016 at the Wayback Machine [46] 50.98% 19.00% 17.05% 11.16% 0.33% 0.22%
January 2012 Archived 4 April 2016 at the Wayback Machine [47] 51.81% 18.98% 16.77% 10.93% 0.38% 0.15%
December 2011 Archived 13 January 2015 at the Wayback Machine [48] 51.42% 19.73% 16.78% 10.69% 0.39% 0.16%
November 2011 Archived 5 April 2016 at the Wayback Machine [49] 51.17% 20.15% 16.13% 11.29% 0.38% 0.16%
October 2011 Archived 3 April 2016 at the Wayback Machine [50] 52.59% 20.06% 15.01% 11.13% 0.36% 0.17%
September 2011 Archived 3 April 2016 at the Wayback Machine [51] 53.79% 20.18% 13.79% 10.81% 0.37% 0.21%
August 2011 Archived 5 April 2016 at the Wayback Machine [52] 53.81% 20.61% 13.64% 10.75% 0.39% 0.15%
July 2011 Archived 3 April 2016 at the Wayback Machine [53] 55.26% 20.29% 12.58% 10.68% 0.37% 0.13%
June 2011 Archived 5 April 2016 at the Wayback Machine [54] 56.23% 20.85% 12.04% 9.77% 0.46%
May 2011 Archived 4 April 2016 at the Wayback Machine [55] 57.48% 20.43% 11.06% 9.88% 0.49%
April 2011 Archived 2 April 2016 at the Wayback Machine [56] 57.08% 21.40% 10.85% 9.47% 0.53%
March 2011 Archived 2 April 2016 at the Wayback Machine [57] 60.27% 19.57% 9.60% 9.62% 0.42%
February 2011 Archived 4 April 2016 at the Wayback Machine [58] 60.92% 19.21% 9.13% 9.59% 0.40% 0.42%
January 2011 Archived 4 April 2016 at the Wayback Machine [59] 61.28% 19.57% 8.80% 9.40% 0.39% 0.31%
December 2010 Archived 13 January 2015 at the Wayback Machine [60] 60.98% 20.14% 8.61% 9.33% 0.40% 0.24%
November 2010 Archived 13 January 2015 at the Wayback Machine [61] 62.13% 19.69% 7.46% 9.42% 0.37% 0.18%
October 2010 Archived 11 March 2016 at the Wayback Machine [62] 62.54% 19.76% 7.17% 9.03% 0.36% 0.15%
September 2010 Archived 13 March 2016 at the Wayback Machine [63] 62.68% 20.51% 6.99% 8.83% 0.36% 0.15%
August 2010 Archived 13 March 2016 at the Wayback Machine [64] 62.66% 20.94% 6.83% 8.83% 0.35% 0.14%
July 2010 Archived 13 March 2016 at the Wayback Machine [65] 61.73% 21.66% 6.95% 8.94% 0.36% 0.11%
June 2010 Archived 13 March 2016 at the Wayback Machine [66] 63.37% 21.26% 6.24% 8.52% 0.33%
May 2010 Archived 12 March 2016 at the Wayback Machine [67] 64.17% 21.12% 5.59% 8.31% 0.37%
April 2010 Archived 13 March 2016 at the Wayback Machine [68] 64.55% 21.35% 5.23% 8.12% 0.40%
March 2010 Archived 13 March 2016 at the Wayback Machine [69] 66.34% 19.90% 4.39% 8.59% 0.31%
February 2010 Archived 12 March 2016 at the Wayback Machine [70] 66.99% 19.48% 3.98% 9.00% 0.24% 0.06%
January 2010 Archived 13 March 2016 at the Wayback Machine [71] 66.33% 20.31% 3.87% 8.94% 0.26% 0.06%
December 2009 Archived 13 January 2015 at the Wayback Machine [72] 66.12% 20.82% 3.51% 8.73% 0.30% 0.07%
November 2009 Archived 13 March 2016 at the Wayback Machine [73] 67.74% 20.15% 2.88% 8.56% 0.28% 0.10%
October 2009 Archived 13 January 2015 at the Wayback Machine [74] 68.38% 20.32% 2.56% 8.09% 0.27% 0.14%
September 2009 Archived 11 March 2016 at the Wayback Machine [75] 67.25% 21.12% 2.41% 8.46% 0.28% 0.21%
August 2009 Archived 12 March 2016 at the Wayback Machine [76] 68.37% 21.32% 2.21% 7.29% 0.28% 0.23%
July 2009 Archived 11 March 2016 at the Wayback Machine [77] 69.29% 21.06% 2.05% 6.77% 0.30% 0.24%
June 2009 Archived 12 March 2016 at the Wayback Machine [78] 71.44% 19.48% 1.93% 6.30% 0.33% 0.22%
May 2009 Archived 13 March 2016 at the Wayback Machine [79] 71.35% 20.26% 1.64% 5.95% 0.31% 0.21%
April 2009 Archived 13 March 2016 at the Wayback Machine [80] 71.38% 20.46% 1.43% 5.80% 0.31% 0.19%
March 2009 Archived 13 March 2016 at the Wayback Machine [81] 72.03% 20.00% 1.19% 5.91% 0.30% 0.10%
February 2009 Archived 13 March 2016 at the Wayback Machine [82] 74.04% 18.64% 0.97% 5.57% 0.27% 0.10%
January 2009 Archived 12 March 2016 at the Wayback Machine [83] 73.05% 19.39% 0.96% 5.72% 0.29% 0.12%
December 2008 Archived 13 January 2015 at the Wayback Machine [84] 70.89% 20.87% 0.95% 6.32% 0.33% 0.13%
November 2008 Archived 13 January 2015 at the Wayback Machine [85] 72.07% 19.78% 0.68% 6.57% 0.29% 0.13%
October 2008 Archived 13 January 2015 at the Wayback Machine [86] 73.45% 18.88% 0.57% 6.22% 0.26% 0.16%
September 2008 Archived 13 March 2016 at the Wayback Machine [87] 74.53% 18.14% 0.52% 5.98% 0.22% 0.17%

92% of sites monitored by StatOwl serve predominantly United States market.[88]

AT Internet Institute (Europe, July 2007 to June 2010)

[edit]

AT Internet Institute was formerly known as XiTi.

Method: Only counts visits to local sites in 23 European countries and then averages the percentages for those 23 European countries independent of population size.

Europe usage share data from AT Internet Institute
Date Internet Explorer Netscape Firefox Opera Safari Chrome Source
June 2010 53.8% 30.6% 2.4% 6.8% 5.7% 2010-6
March 2010 57.1% 29.6% 2.2% 5.2% 5.3% 2010-3
September 2009 62.0% 28.4% 2.2% 4.3% 2.8% 2009–11
April 2009 63.6% 0.6% 28.4% 2.2% 3.4% 1.7% 2009-5
March 2009 64.6% 0.6% 27.8% 2.2% 3.3% 1.4%
February 2009 65.6% 0.5% 27.4% 2.1% 3.0% 1.3%
January 2009 58.1% 0.6% 32.5% 4.1% 3.0% 1.5% 2009-1
December 2008 58.5% 0.6% 32.3% 4.5% 2.7% 1.3%
November 2008 59.5% 0.6% 31.1% 5.1% 2.5% 1.1% 2008-12-22
October 2008 59.2% 0.6% 31.1% 5.4% 2.4% 1.1%
September 2008 60.2% 0.4% 31.2% 4.8% 2.4% 1.0% 2008-10-10
August 2008 59.4% 0.3% 33.0% 4.5% 2.6%
July 2008 60.4% 0.3% 32.2% 4.5% 2.4%
June 2008 60.5% 0.3% 31.4% 5.1% 2.5%
May 2008 61.7% 0.4% 30.7% 4.7% 2.4%
April 2008 64.5% 0.5% 28.9% 3.6% 2.4%
March 2008 65.0% 0.5% 28.8% 3.3% 2.3% 2008-04-30
February 2008 65.6% 0.5% 28.5% 3.2% 2.2%
January 2008 66.1% 0.5% 28.0% 3.2% 2.1%
December 2007 66.1% 0.5% 28.0% 3.3% 2.0%
November 2007 66.9% 0.5% 27.3% 3.2% 1.9%
October 2007 67.5% 0.4% 27.0% 3.1% 1.8%
September 2007 66.6% 0.3% 27.7% 3.4% 1.8% 2007-10-30
2–8 July 2007 66.5% 0.3% 27.8% 3.5% 1.7% 2007-07-18

TheCounter.com (2000 to 2009)

[edit]

TheCounter.com, a defunct web counter service, identified sixteen versions of six browsers (Internet Explorer, Firefox, Safari, Opera, Netscape, and Konqueror). Other browsers are categorised as either "Netscape compatible" (including Google Chrome, which may also be categorized as "Safari" because of its "Webkit" subtag) or "unknown". Internet Explorer 8 is identified as Internet Explorer 7. Monthly data includes all hits from 2008-02-01 until the end of the month concerned. More than the exact browser type, this data identifies the underlying rendering engine used by various browsers, and the table below aggregates them in the same column.

Global usage share data from TheCounter.com (global statistics)
Period
 Internet
Explorer
 Netscape,
Other Mozilla,
Firefox 		Safari

 Opera

 Netscape
Navigator
 Sources
2009 Q4 66.42% 21.13% 10.05% 1.00% 0.05% Oct, Nov, Dec
2009 Q3 69.07% 20.59% 8.10% 0.89% 0.06% Jul, Aug, Sep
2009 Q2 70.31% 20.12% 6.44% 0.94% 0.06% Apr, May, Jun
2009 Q1 71.25% 20.01% 5.47% 0.92% 0.08% Jan, Feb, Mar
2008 Q4 74.24% 18.66% 4.52% 0.89% 0.07% Oct, Nov, Dec
2008 Q3 76.33% 17.97% 3.76% 0.84% 0.07% Jul, Aug, Sep
2008 Q2 78.30% 16.36% 3.41% 0.81% 0.06% Apr, May, Jun
2008 Q1 78.80% 15.87% 3.32% 0.79% 0.06% Jan, Feb, Mar
2007 Q4 81.14% 13.81% 3.21% 0.67% 0.06% Oct, Nov, Dec
2007 Q3 81.63% 13.49% 3.00% 0.66% 0.06% Jul, Aug, Sep
2007 Q2 82.97% 12.41% 2.87% 0.64% 0.06% Apr, May, Jun
2007 Q1 83.69% 11.57% 2.92% 0.57% 0.06% Jan, Feb, Mar
2006 Q4 84.11% 11.13% 2.80% 0.60% 0.05% Nov, Dec Archived 9 December 2006 at the Wayback Machine [89]
2006 Q3 84.48% 10.56% 2.27% 0.73% 0.06% Jul Archived 1 November 2011 at the Wayback Machine [90]
2006 Q2 86.32% 9.03% 1.89% 0.70% 0.05% Apr Archived 1 November 2011 at the Wayback Machine [91]
2006 Q1 90.01% 6.77% 1.40% 0.58% 0.05% Jan Archived 1 November 2011 at the Wayback Machine [92]
2005 Q4 87.25% 8.60% 1.83% 0.71% 0.07% Oct Archived 1 November 2011 at the Wayback Machine [93]
2005 Q3 87.58% 8.42% 1.60% 0.67% 0.07% Jul Archived 1 November 2011 at the Wayback Machine [94]
2005 Q2 90.90% 6.02% 0.99% 0.51% 0.09% Apr Archived 13 August 2008 at the Wayback Machine [95]
2005 Q1 90.77% 5.73% 1.00% 0.54% 0.11% Jan Archived 1 November 2011 at the Wayback Machine [96]
2004 Q4 90.98% 5.10% 0.77% 0.68% 0.18% Oct Archived 1 November 2011 at the Wayback Machine [97]
2004 Q3 92.70% 3.57% 0.73% 0.65% 0.20% Jul Archived 1 November 2011 at the Wayback Machine [98]
2004 Q2 95.04% 2.37% 0.67% 0.51% 0.32% Apr Archived 1 November 2011 at the Wayback Machine [99]
2004 Q1 94.28% 2.70% 0.52% 0.36% Jan Archived 6 October 2011 at the Wayback Machine [100]
2003 Q4 Oct, Nov, Dec
2003 Q3 Jul, Aug, Sep
2003 Q2 94.43% 2.22% 0.66% 1.45% Apr, May, Jun
2003 Q1 94.18% 2.15% 0.65% 1.77% Jan, Feb, Mar
2002 Q4 93.94% 1.67% 0.83% 2.31% Oct, Nov, Dec
2002 Q3 93.32% 1.36% 0.94% 3.04% Jul, Aug, Sep
2002 Q2 92.47% 1.13% 0.82% 4.13% Apr, May, Jun
2002 Q1 92.40% 0.93% 0.52% 4.67% Jan, Feb, Mar
2001 Q4 90.83% 0.71% 0.36% 5.23% Oct, Nov, Dec
2001 Q3 88.43% 0.26% 0.31% 6.49% Jul, Aug, Sep
2001 Q2 87.99% 0.27% 0.28% 7.46% Apr, May, Jun
2001 Q1 86.80% 0.30% 0.22% 9.84% Jan, Feb, Mar
2000 Q4 83.95% 0.14% 0.14% 12.61% Oct, Nov, Dec
2000 Q3 82.76% 0.04% 0.14% 14.35% Jul, Aug, Sep
2000 Q2 80.30% 0.02% 0.12% 17.54% Apr, May, Jun
2000 Q1 79.09% 0.00% 0.13% 19.25% Jan, Feb, Mar
Period
 Internet
Explorer
 Netscape,
Other Mozilla,
Firefox 		Safari

 Opera

 Netscape
Navigator
 Sources

OneStat.com (April 2002 to March 2009)

[edit]
Global usage share data from OneStat.com Archived 2 May 2021 at the Wayback Machine [101] (press releases)
Period
 Internet
Explorer
 Other Mozilla,
Firefox
 Safari

 Chrome

 Opera

 Netscape

 Netscape
Navigator
March 2009 Archived 25 February 2021 at the Wayback Machine [102] 79.79% 15.59% 2.65% 0.86% 0.54% 0.31%
November 2008 Archived 26 February 2021 at the Wayback Machine [103] 81.36% 14.67% 2.42% 0.54% 0.55% 0.32%
February 2008 Archived 24 February 2021 at the Wayback Machine [104] 83.27% 13.76% 2.18% 0.55% 0.14%
June 2007 Archived 26 February 2021 at the Wayback Machine [105] 84.66% 12.72% 1.79% 0.61% 0.11%
January 2007 Archived 27 February 2021 at the Wayback Machine [106] 85.81% 11.69% 1.64% 0.58% 0.13%
November 2006 Archived 25 February 2021 at the Wayback Machine [107] 85.24% 12.15% 1.61% 0.69% 0.11%
October 2006 Archived 4 March 2021 at the Wayback Machine [108] 85.85% 11.49% 1.61% 0.69% 0.12%
July 2006 Archived 27 April 2021 at the Wayback Machine [109] 83.05% 12.93% 1.84% 1.00% 0.16%
May 2006 Archived 25 February 2021 at the Wayback Machine [110] 85.17% 11.79% 2.02% 0.79% 0.15%
January 2006 Archived 25 February 2021 at the Wayback Machine [111] 85.82% 11.23% 1.88% 0.77% 0.16%
November 2005 Archived 14 April 2021 at the Wayback Machine [112] 85.45% 11.51% 1.75% 0.77% 0.26%
April 2005 Archived 26 January 2021 at the Wayback Machine [113] 86.63% 8.69% 1.26% 1.03% 1.08%
February 2005 Archived 24 February 2021 at the Wayback Machine [114] 87.28% 8.45% 1.21% 1.09% 1.11%
November 2004 Archived 25 February 2021 at the Wayback Machine [115] 88.90% 7.35% 0.91% 1.33%
May 2004 Archived 27 February 2021 at the Wayback Machine [116] 93.9% 2.1% 0.71% 1.02%
January 2004 Archived 12 February 2021 at the Wayback Machine [117] 94.8% 1.8% 0.48% 0.8%
July 2003 Archived 11 February 2021 at the Wayback Machine [118] 95.4% 1.6% 0.25% 0.6% 1.9% 0.6%
February 2003 Archived 25 February 2021 at the Wayback Machine [119] 95.2% 1.2% 0.11% 0.7% 1.9% 1.0%
December 2002 Archived 25 February 2021 at the Wayback Machine [120] 95.0% 1.1% 0.8% 1.9% 1.1%
September 2002 Archived 25 February 2021 at the Wayback Machine [121] 94.9% 0.8% 0.9% 1.8% 1.2%
June 2002 Archived 11 April 2021 at the Wayback Machine [122] 95.3% 0.4% 0.7% 1.5% 1.9%
April 2002 Archived 24 February 2021 at the Wayback Machine [123] 96.6% 0.5% 0.7% 2.1%
US usage share data from OneStat.com Archived 2 May 2021 at the Wayback Machine [101] (press releases)
Period
 Internet
Explorer
 Other Mozilla,
Firefox
 Safari

 Chrome

 Opera

 Netscape

March 2009 Archived 25 February 2021 at the Wayback Machine [124] 72.69% 20.40% 4.53% 1.05% 0.49% 0.38%
November 2008 Archived 26 February 2021 at the Wayback Machine [103] 75.54% 18.74% 3.95% 0.62% 0.39% 0.50%
June 2007 Archived 26 February 2021 at the Wayback Machine [105] 75.69% 19.65% 3.77% 0.61% 0.17%
January 2007 Archived 26 February 2021 at the Wayback Machine [105] 78.13% 16.11% 3.68% 0.73% 0.18%
Canadian usage share data from OneStat.com Archived 2 May 2021 at the Wayback Machine [101] (press releases)
Period
 Internet
Explorer
 Other Mozilla,
Firefox
 Safari

 Chrome

 Opera

 Netscape

March 2009 Archived 25 February 2021 at the Wayback Machine [124] 65.55% 23.09% 7.36% 1.32% 0.75% 0.56%
November 2008 Archived 26 February 2021 at the Wayback Machine [103] 69.67% 20.38% 7.56% 0.92% 0.76% 0.56%
June 2007 Archived 26 February 2021 at the Wayback Machine [105] 75.76% 16.47% 5.72% 0.69% 0.13%
January 2007 Archived 26 February 2021 at the Wayback Machine [105] 79.00% 14.13% 4.70% 0.71% 0.14%
UK usage share data from OneStat.com Archived 2 May 2021 at the Wayback Machine [101] (press releases)
Period
 Internet
Explorer
 Other Mozilla,
Firefox
 Safari

 Chrome

 Opera

 Netscape

March 2009 Archived 25 February 2021 at the Wayback Machine [124] 80.91% 15.16% 1.94% 0.85% 0.60% 0.36%
November 2008 Archived 26 February 2021 at the Wayback Machine Archived 26 February 2021 at the Wayback Machine [103] 83.77% 11.45% 1.76% 0.43% 0.60% 0.34%
June 2007 Archived 26 February 2021 at the Wayback Machine [105] 86.00% 11.22% 1.61% 0.53% 0.10%
January 2007 Archived 26 February 2021 at the Wayback Machine [105] 86.72% 10.86% 1.78% 0.49% 0.10%
Australian usage share data from OneStat.com Archived 2 May 2021 at the Wayback Machine [101] (press releases)
Period
 Internet
Explorer
 Other Mozilla,
Firefox
 Safari

 Chrome

 Opera

 Netscape

June 2007 Archived 26 February 2021 at the Wayback Machine [105] 66.42% 26.32% 1.86% 4.05% 0.24%
January 2007 Archived 26 February 2021 at the Wayback Machine Archived 26 February 2021 at the Wayback Machine [105] 65.71% 26.68% 1.77% 4.28% 0.24%
French usage share data from OneStat.com Archived 2 May 2021 at the Wayback Machine Archived 2 May 2021 at the Wayback Machine [101] (press releases)
Period
 Internet
Explorer
 Other Mozilla,
Firefox
 Safari

 Chrome

 Opera

 Netscape

March 2009 Archived 25 February 2021 at the Wayback Machine Archived 25 February 2021 at the Wayback Machine [124] 71.57% 23.48% 2.90% 0.86% 0.54% 0.46%
November 2008 Archived 26 February 2021 at the Wayback Machine [103] 71.50% 23.45% 3.23% 0.59% 0.56% 0.51%

ADTECH (Europe, 2004 to 2009)

[edit]
Europe usage share data from ADTECH Archived 18 July 2005 at the Wayback Machine [125]'s press releases; this is an ad serving company
Period
 Internet
Explorer
 Firefox

 Safari

 Chrome

 Opera

 Other Mozilla

 Netscape

Q4 2009 Archived 25 November 2010 at the Wayback Machine [126] 63.6% 26.7% 3.6% 2.8% 1.7% 0.7%
Q1 2009 Archived 17 August 2009 at the Wayback Machine [127] 67.7% 25.3% 2.6% 1.0% 1.4% 1.1%
Q1 2008 Archived 5 March 2009 at the Wayback Machine [128] 76.2% 18.1% 1.7% 1.0% 2.6%
Q4 2007 Archived 3 March 2009 at the Wayback Machine [129] 76.0% 18.0% 1.6% 1.0% 2.9%
July 2007 Archived 21 November 2018 at the Wayback Machine [130] 77.5% 15.5% 1.6% 0.9% 3.9%
February 2007 Archived 15 December 2018 at the Wayback Machine [131] 77.34% 14.34% 1.63% 0.85% 5.11%
February–April 2006 Archived 21 November 2018 at the Wayback Machine [132] 83.36% 12.38% 1.67% 0.77% 0.82% 0.38%
September 2005 Archived 21 November 2018 at the Wayback Machine [133] 83.31% 12.41% 1.40% 0.90% 1.06% 0.61%
June 2005 Archived 21 November 2018 at the Wayback Machine [134] 85.10% 10.11% 1.34% 1.21% 1.05% 0.60%
March 2005 Archived 15 December 2018 at the Wayback Machine [135] 86.73% 8.96% 1.12% 1.14% 0.71%
February 2005 Archived 15 December 2018 at the Wayback Machine [135] 87.57% 7.85% 1.05% 1.26% 0.76%
January 2005 Archived 15 December 2018 at the Wayback Machine [135] 87.13% 7.43% 1.70% 1.33% 0.85%
November 2004 Archived 21 November 2018 at the Wayback Machine [136] 89.47% 5.51% 1.01% 2.50% 0.92%
September 2004 Archived 21 November 2018 at the Wayback Machine [137] 92.63% 2.91% 1.00% 2.10% 0.82%
August 2004 Archived 21 November 2018 at the Wayback Machine [136] 93.08% 2.15% 0.89% 2.18% 0.95%
July 2004 Archived 21 November 2018 at the Wayback Machine [137] 93.08% 1.64% 0.99% 2.62% 0.97%
January–April 2004 Archived 6 August 2004 at the Wayback Machine [138] 94.72% 0.73% 2.50% 1.49%

WebSideStory (US, February 1999 to June 2006)

[edit]
US usage share data from: WebSideStory
Date Internet Explorer Netscape, Other Mozilla Firefox Source
June 2006 86.64% 9.95% 19 July 2006
5 January 2006 87.63% 8.88% 12 January 2006
4 November 2005 88.16% 1.61% 8.13% 10 November 2005
23 September 2005 88.46% 1.69% 7.86% 27 September 2005
29 April 2005 88.86% 2.23% 6.75% 10 May 2005
18 February 2005 89.85% 2.47% 5.69% 28 February 2005
14 January 2005 90.28% 2.64% 4.95%
3 December 2004 91.80% 2.83% 4.06%
5 November 2004 92.89% 2.95% 3.03%
8 October 2004 93.21% 3.05% 2.66% 13 December 2004
4 June 2004 95.48% 3.53%
26 August 2002 95.97% 3.39% 28 August 2002
25 October 2001 89.03% 10.47% 31 October 2001
25 April 2001 86.61% 13.10% 1 May 2001
21 February 2001 87.71% 12.01% 22 February 2001
18 June 2000 86.08% 13.90%
2 August 1999 75.31% 24.68% 9 August 1999
6 April 1999 68.75% 29.46% 7 April 1999
1 March 1999 66.90% 31.21% 2 March 1999
8 February 1999 64.60% 33.43% 22 February 2001

Older reports (pre-2000)

[edit]
Market share for several browsers between 1995 and 2010, illustrating the First Browser War (NN vs IE). Firefox was originally named "Phoenix", a name which implied that it would rise like a Phoenix after Netscape was killed off by Microsoft.


GVU WWW user survey (January 1994 to October 1998)

Usage share data from: GVU WWW user survey
Date Mosaic Netscape Navigator Internet Explorer Source
October 1998 64% 32.2% Primary Browser in 12 Months
April 1998 70% 22.7% Browser Expected to Use in 12 Months
October 1997 59.67% 15.13% Browser Expected to Use in 12 Months
April 1997 81.13% 12.13% Browser Expected to Use in 12 Months
October 1996 80.45% 12.18% Browser Expected to Use in 12 Months
April 1996 89.36% 3.76% Browser Expected to Use in 12 Months
April 1995 9% 54% Hal Berghel's Cybernautica – "A Web Monopoly"
October 1994 68% 18% Result Graph – Browser
January 1994 97% General Results Graphs


EWS Web Server at UIUC (1996 Q2 to 1998)

Usage share data from: EWS Web Server at UIUC Archived 8 March 2012 at the Wayback Machine
Date Mosaic Internet Explorer Netscape Navigator Source
1998 Q4 50.43% 46.87% Oct 1998, Nov 1998, Dec 1998
1998 Q3 47.90% 48.97% Jul 1998, Aug 1998, Sep 1998
1998 Q2 43.17% 53.57% Apr 1998, May 1998, Jun 1998
1998 Q1 39.67% 57.63% Jan 1998, Feb 1998, Mar 1998
1997 Q4 35.53% 62.23% Oct 1997, Nov 1997, Dec 1997
1997 Q3 32.40% 64.93% Jul 1997, Aug 1997, Sep 1997
1997 Q2 0.37% 27.67% 69.77% Apr 1997, May 1997, Jun 1997
1997 Q1 0.60% 22.87% 74.33% Jan 1997, Feb 1997, Mar 1997
1996 Q4 1.20% 19.07% 77.13% Oct 1996, Nov 1996, Dec 1996
1996 Q3 2.47% 13.97% 80.37% Jul 1996, Aug 1996, Sep 1996
1996 Q2 6.93% 9.60% 82.77% Apr 1996, May 1996, Jun 1996


ZD Market Intelligence (US, January 1997 to January 1998)

Usage share data from: ZD Market Intelligence
Date Internet Explorer Netscape Navigator Source
January 1998 39% 54% Behind the numbers: Browser market share
January 1997 21% 63%


Zona Research (US, Jan 1997 to Jan 1998)

Usage share data from: Zona Research
Date Internet Explorer Netscape Navigator Source
July 1998 45% 54% Behind the numbers: Browser market share
September 1997 36% 62%
January 1997 28% 70%


AdKnowledge (January 1998 to June 1998)

Usage share data from: AdKnowledge
Date Internet Explorer Netscape Navigator Source
June 1998 46% 52% Behind the numbers: Browser market share
March 1998 42% 57%
January 1998 36% 61%


Dataquest (1995 to 1997)

Usage share data from: Dataquest
Date Internet Explorer Netscape Navigator Source
1997 39.4% 57.6% Browser wars: High price, huge rewards
1996 20% 73%
1995 2.9% 80.1%


International Data Corporation (US, 1996 to 1997)

Usage share data from: International Data Corporation
Date Internet Explorer Netscape Navigator Source
1997 23% 51% Behind the numbers: Browser market share
1996 16% 55%

See also

[edit]

References

[edit]
[edit]
Revisions and contributorsEdit on WikipediaRead on Wikipedia

Usage share of web browsers

View on Grokipedia
from Grokipedia
The usage share of web browsers refers to the percentage of or page views generated by users of a particular browser, calculated from large-scale sampling of activity across millions of websites. This metric provides insights into browser popularity, influencing standards, security priorities, and market competition among developers like , Apple, , and . As of January 2026, Google Chrome commands the largest global share at 71.37%, driven by its integration with Android devices and cross-platform availability, while Apple's Safari holds 14.75%, primarily among iOS and macOS users. Microsoft Edge follows with 4.65%, benefiting from default installation on Windows systems, Mozilla Firefox at 2.23%, appealing to privacy-focused users. Other browsers include Opera at 1.88% and Samsung Internet at 1.83%. Google Chrome remains the dominant browser, with shares varying significantly by region—for instance, Chrome exceeds 90% in markets like India. Historically, browser usage has undergone dramatic shifts since the mid-1990s, beginning with the "" between , which peaked at over 90% in 1995, and Microsoft's , which surged to dominance by 2003 amid antitrust scrutiny. The launch of in 2004 revived competition, capturing up to 30% share by 2009 through open-source innovation, but Google's Chrome, introduced in 2008, rapidly overtook rivals with superior speed and ecosystem integration, reaching over 45% by 2015 and 50% by 2016, solidifying its lead thereafter. The proliferation of mobile internet since 2010 has further boosted Chrome and , as desktop shares for and declined sharply. Usage shares are primarily measured through analytics panels like StatCounter, which aggregates data from over 5 billion monthly page views across more than 1.5 million global websites, weighting results toward rather than unique visitors. Alternative sources, such as W3Counter and Net Applications, employ similar page-view tracking but yield varying figures due to differences in sample size, geographic coverage, and methodology—for example, W3Counter reported Chrome at 75.1% as of January 2026. These discrepancies highlight the challenges in capturing a fully representative snapshot of the 5 billion-plus internet users worldwide.

Methodologies and Accuracy

Data Collection Methods

Server log analysis represents the most common method for collecting data on web browser usage shares, as it leverages records automatically generated by web servers during user interactions. When a user visits a , the server receives an HTTP request that includes a string—a text field identifying the browser, operating system, and device details. tools parse these logs to aggregate browser types across millions of requests, providing a broad sample of real-time without requiring additional user-side installation. This approach is widely used by services monitoring large-scale , offering insights into global and regional patterns based on actual page loads. Panel-based measurement complements server logs by recruiting representative groups of users to install tracking software that monitors their habits in detail. Firms such as assemble panels through opt-in recruitment via affiliate programs and third-party applications, where participants download a meter that passively records all activity, including browser usage across sessions. This method captures comprehensive user behavior, such as time spent and sites visited, and projects the data to broader populations using demographic weighting and surveys to estimate market shares. However, user agent spoofing can pose a detection challenge in both server log and panel analyses, as some users or bots alter strings to mimic other browsers. Toolbar or browser extension data collection involves users voluntarily installing add-ons that report browsing data back to the provider. Historical examples include the Alexa Toolbar, which gathered anonymized usage statistics from millions of users to compute traffic rankings and infer browser distributions based on the proportion of toolbar-equipped visitors. These tools provide granular, opt-in data but are limited by self-selection bias toward tech-savvy users. Search engine referral data offers another estimation avenue by analyzing traffic sources from query logs, where referrers indicate the originating browser via user agent information. Providers like Google or Bing can derive browser shares from aggregated referral patterns, supplementing direct measurements with insights into search-driven visits. This method is particularly useful for identifying trends in mobile versus desktop usage. Specific implementations, such as StatCounter's approach, exemplify hybrid techniques by embedding tags on over 1.5 million websites to sample page views and parse user agents in real time. This results in billions of monthly observations, focusing on page view volume to reflect usage intensity rather than unique visitors alone.

Accuracy Challenges

Measuring the usage share of web browsers is complicated by sampling biases, where often favors certain demographics, regions, or device types over others, leading to unrepresentative global estimates. For instance, many analytics panels draw from websites popular in high-income countries, resulting in underrepresentation of mobile-heavy regions like parts of and Africa, where browser preferences may differ significantly from desktop-dominated Western markets. Similarly, device-type biases occur because some tracking methods perform better on desktops than on mobiles or tablets, skewing shares toward browsers optimized for larger screens. Passive measurement techniques, which dominate browser share data through server logs or client-side JavaScript trackers, introduce inaccuracies compared to active methods like user surveys, as they fail to capture sessions in privacy-focused modes or when blocking tools are active. Incognito or modes disable persistent , undercounting unique users by treating repeat visits as new sessions and evading long-term tracking. Ad blockers exacerbate this by preventing analytics scripts from loading, potentially excluding a significant portion of from measurements depending on the audience, as they filter out both ads and embedded trackers. Temporal factors, such as seasonal fluctuations in usage, further challenge the reliability of monthly averages used in browser share reports. Web traffic often surges during holidays or events like Black Friday, with increased mobile browsing in summer or e-commerce peaks in winter, causing short-term spikes that can distort averages if not seasonally adjusted; for example, e-commerce traffic can increase by 40-60% during major shopping events. To derive overall shares, providers extrapolate from sampled page views or visits to estimate total internet traffic, introducing error margins that vary by sample size and methodology; StatCounter relies on its large sample of over 5 billion monthly page views for accuracy. These extrapolations assume uniform behavior across unsampled populations, but variances in regional internet penetration can amplify inaccuracies. A key source of discrepancy lies in the choice of metrics—page view counts (e.g., ) emphasize frequent users and heavy-traffic sites, inflating shares for popular browsers, while unique visitor or session-based metrics (e.g., former Net Applications) prioritize distinct individuals, potentially underrepresenting browsers used sporadically. This metric divergence can lead to share differences of 5-10 percentage points for the same browser across providers.

Overestimation Factors

Bot and automated traffic represent a major source of overestimation in web browser usage shares, as these non-human activities often emulate the user agents of common browsers to evade detection or blend with legitimate traffic. According to Imperva's 2025 Bad Bot Report, automated bots accounted for 51% of all web traffic in 2024, with bad bots comprising 37% and good bots 14%. Many bots default to user agents of dominant browsers like Chrome, artificially boosting their reported shares in analytics that fail to filter non-human activity. In enterprise settings, this effect was particularly pronounced for Internet Explorer during its peak, where default installations led to automated scripts and internal tools generating substantial traffic under IE's user agent, distorting global estimates. Sample site biases further contribute to overestimation by skewing data toward browsers favored by specific demographics on sites with heavy implementation. For instance, technology-focused websites, where enjoys higher adoption among developers and early adopters, often host disproportionate numbers of tracking tags, leading to inflated Chrome shares in aggregated reports from sources like panels. This bias arises because such sites attract users already predisposed to Chrome, amplifying its visibility in samples that underrepresent broader populations, such as non-tech users on general content platforms. Multiple device counting without effective deduplication exacerbates overestimation, especially for shared accounts or households where the same users access sites across devices using the same browser. Analytics relying on or IP addresses may count each device visit separately, overcounting usage for browsers like Chrome that are pre-installed on both desktop and mobile ecosystems. A study on unique visitor metrics found that cookie-based tracking can overstate user counts by 2 to 4 times due to multi-device , a principle that extends to browser share calculations without cross-device user identification. A notable example of overestimation occurred in the early 2010s with , where corporate logs captured extensive automated and internal traffic from as the mandated enterprise browser, leading some reports to portray higher global adoption than actual consumer usage reflected. Studies have indicated that traffic can inflate browser share reports in affected datasets, particularly when filtering mechanisms overlook benign automated sources like crawlers.

Underestimation Factors

Privacy-focused browsers and extensions often contribute to underestimation of usage shares in measurements that depend on third-party trackers or analytics scripts. For instance, 's Enhanced Tracking Protection, enabled by default since 2019, blocks known tracking content from companies like and , which can prevent sessions from being fully recorded in tools such as or server logs that rely on these scripts. This results in fewer detected visits from privacy-conscious users, leading to deflated estimates for browsers like and , whose Intelligent Tracking Prevention similarly limits cross-site tracking. Regional under-sampling exacerbates underestimation for browsers tied to specific ecosystems, such as in Android-dominant markets like . Where penetration is low—around 20-25% in many Asian countries—panel-based or log-based metrics may inadequately capture Safari usage due to limited device diversity in sampled populations or lower representation of Apple hardware in global panels. For example, StatCounter data shows Safari holding 7.52% share in for the period October 2024 to October 2025. Access to offline or cached content further contributes to undercounting, as these interactions do not trigger server requests and thus evade log-based . When users view previously loaded pages from browser cache or service workers enable offline functionality, no new traffic is recorded, distorting usage shares toward browsers or users with higher online activity. This bias is particularly acute for mobile browsers, where intermittent connectivity leads to more caching, and standard web metrics miss repeat visits in such scenarios. The Tor Browser exemplifies severe underestimation due to its core anonymization mechanisms, which route traffic through multiple relays and resist standard fingerprinting or logging. Conventional metrics like those from StatCounter or rarely detect Tor usage, as exit nodes mask s and IPs, evading aggregation in global datasets; Tor Metrics itself estimates around 2.5-3 million daily users as of 2025 but notes that external underreport this due to the network's design. Relatedly, user agent spoofing in privacy tools can compound this evasion, though it primarily affects identification rather than overall volume. In panel-based surveys, opt-out rates for data collection further deflate shares for browsers like , where users frequently disable to preserve . Historical data from the late indicated high opt-out rates exceeding 70% in some user cohorts, limiting representative sampling.

User Agent Spoofing

strings, included in HTTP request headers, serve as identifiers that inform web servers about the client's browser type, version, operating system, and device characteristics, enabling tailored content delivery and compatibility adjustments. These strings can be deliberately altered or forged, a practice known as spoofing, to misrepresent the client's and potentially evade detection or access restrictions. Spoofing occurs through various methods, including built-in browser behaviors for compatibility, such as on devices, which leverages Apple's engine and transmits a string mimicking to ensure seamless integration with ecosystem standards. Additional types involve third-party browser extensions like User-Agent Switcher, which allow users to manually select and apply predefined or custom strings for different browsers or devices, and developer tools in browsers like Chrome DevTools, where overriding the user agent facilitates testing across simulated environments. Detection of spoofing relies on to identify inconsistencies between the reported and actual browser behaviors, such as a string claiming Safari origins paired with Chrome-specific rendering traits or unsupported features. Complementary techniques include JavaScript-based fingerprinting, which gathers supplementary attributes like canvas rendering, capabilities, and hardware concurrency to cross-verify the declared identity against observable traits, revealing mismatches indicative of forgery. This practice distorts browser usage share measurements by inflating or deflating reported adoption rates, as spoofed traffic misattributes visits to incorrect browsers or devices, leading to unreliable analytics on market distribution. For instance, spoofing has been used to bypass site restrictions, complicating accurate share calculations from log-based data sources. The prevalence of spoofing rose notably after 2015, coinciding with accelerated growth, as users increasingly employed it to bypass site-imposed restrictions, such as desktop-only access policies or suboptimal mobile-optimized layouts that limited functionality. Modern developments include User-Agent Client Hints, a privacy-focused alternative introduced by major browsers in the early , which reduces reliance on full strings and aims to mitigate spoofing risks while preserving compatibility.

Variations in Measurement

Methodological Differences

Major analytics services employ distinct methodologies to estimate web browser usage shares, leading to variations in reported figures due to differences in data collection, sampling, and processing. StatCounter relies on JavaScript-based sampling, where its tracking code is voluntarily installed on millions of websites worldwide to capture page view data rather than unique visitors, allowing it to account for browsing frequency and using a geographically diverse sample without weighting for global statistics. In contrast, Net Applications, whose browser tracking reports (NetMarketShare) were discontinued in 2020, utilized a panel-based opt-in approach, collecting data from the browsers of site visitors to its exclusive on-demand network of approximately 40,000 partner websites, focusing on daily unique visitors to prioritize individual user sessions over page impressions. Other services further diversify these approaches through specialized data sources. W3Counter aggregates statistics from a global panel of websites that opt into its free service, drawing on logs from tens of thousands of participating sites to generate estimates based on observed visitor behaviors without requiring broad implementation. Similarly, combines direct first-party from millions of shared website datasets with AI-inferred modeling derived from web crawlers that index public patterns, enabling it to extrapolate browser usage from a multidimensional blend of observed and predicted engagement metrics. Radar, meanwhile, leverages real-time edge network data from the billions of requests processed for its protected sites, parsing user-agent strings to identify browsers and operating systems directly from incoming , which provides a server-side perspective on usage without relying on client-side scripts. Statista takes an aggregative stance by compiling and weighting data from multiple primary sources, such as StatCounter and SimilarWeb, to produce synthesized estimates that balance discrepancies across methodologies and aim for broader representativeness through algorithmic adjustments for regional and device variances. These differences extend to core definitions, particularly in identifying unique visitors; for instance, services like Net Applications historically emphasized cookie-based or IP-address tracking to deduplicate sessions per user, whereas page-view-focused tools like StatCounter avoid such metrics to mitigate issues like cookie blocking or shared IPs. Sampling bias, such as underrepresentation of certain regions or device types, can influence all these methods, underscoring the need for methodological transparency in interpreting usage shares.

Impacts on Reported Shares

Methodological variations in and analysis lead to significant divergences in reported browser usage shares across different services, often resulting in differences of several points for major browsers. A prominent case study involves Google's Chrome, whose share has historically been reported 5-10% higher in log-based analyses like those from StatCounter compared to panel-based from Net Applications, primarily due to differences in user demographics and sampling biases. StatCounter's global, pageview-weighted approach captures more usage from emerging markets and heavy users where Chrome dominates, particularly on mobile devices, while Net Applications' focus on unique users from a more U.S.-centric panel underrepresents Chrome's penetration in international and high-volume traffic scenarios. Firefox experiences consistent underreporting in mobile-focused samples, where its market presence is minimal compared to desktop environments, leading services emphasizing mobile to depict Firefox's overall share as lower than in balanced or desktop-heavy datasets. This discrepancy arises because Firefox's mobile adoption remains below 1% globally, skewing results in samples dominated by Android and ecosystems favoring Chrome and . In the , debates over (IE) versus Chrome highlighted these impacts, with log data from StatCounter indicating a more rapid decline for IE—reaching below 50% share by 2010—while from Net Applications portrayed a slower erosion, maintaining IE above 50% into 2012 and fueling arguments over leadership in the browser market. spoofing further contributes to these variances by allowing browsers to misreport their identity, complicating accurate attribution in log analyses. Since the 2020 discontinuation of Net Applications' browser tracking, methodological improvements and hybrid approaches have narrowed some discrepancies, but notable variations persist as of January 2026—for example, StatCounter reports Chrome at 71.37%, while W3Counter reports 75.1%. Reconciliation efforts, such as creating averaged indices from multiple sources, have gained traction to provide more reliable estimates, mitigating biases from any single .

Current Usage Shares (2020–2026)

Global Summary

From 2020 to 2026, the global web browser market has been dominated by , which has consistently held the largest usage share across all devices, driven by its widespread adoption on mobile platforms. As of January 2026, commands 71.37% of the worldwide market, followed by Apple Safari at 14.75%, at 4.65%, Mozilla Firefox at 2.23%, at 1.88%, and at 1.83%, with remaining browsers accounting for approximately 3.3%. These figures reflect aggregated data from over 5 billion monthly page views, capturing usage across desktop, mobile, and tablet environments. Chrome's market share has shown steady growth over this period, rising from 63.38% in to 64.70% in 2023 and reaching 71.37% as of January 2026, primarily attributable to its default integration with Android operating systems, which power the majority of global smartphones. This expansion has contributed to decreasing market fragmentation, with the top three browsers—Chrome, , and Edge—collectively holding over 90% of the share in 2026, up from approximately 87% in . Data from sources like StatCounter and aggregates from highlight minor variances due to methodological differences in tracking, such as page view sampling versus detection, but confirm Chrome's overarching dominance in this timeframe. Overall, these trends underscore a consolidating ecosystem where a few major browsers serve the vast majority of users worldwide.

Desktop Browser Shares

In the desktop browser market as of January 2026, holds a dominant position with 76.39% usage share, followed by at 9.14%, Apple Safari at 5.29%, Firefox at 4.05%, and at 2.21%. These figures reflect data from analytics providers focusing on desktop environments, where Chrome's integration with search and extensions continues to drive its lead. From 2020 to 2026, notable trends include Edge's steady growth from 3% to 9.14% share, attributed primarily to its default inclusion and updates within Windows ecosystems, enhancing user retention and adoption. In contrast, has declined from 8% to 4.05%, influenced by competition from Chromium-based alternatives and reduced marketing visibility. Safari's share remains stable around 5.29%, bolstered by macOS loyalty, while holds a niche at 2.21% through customization features. Regional variations highlight localized preferences: enjoys higher adoption in , with shares between 8% and 10%, due to privacy-focused user bases and historical . In the United States, Edge reaches about 12%, benefiting from strong Windows prevalence and enterprise deployments.
Browser2026 Global Desktop ShareKey Trend (2020–2026)
Chrome76.39%Stable dominance
Edge9.14%Growth from 3% via Windows integration
4.05%Decline from 8%
5.29%Steady on macOS
2.21%Niche stability
Overall, desktop browsing's proportion of total has fallen from 55% in 2020 to 45% in 2025, as mobile usage expands, though desktop remains critical for productivity tasks.

Mobile Browser Shares

In the period from 2020 to 2026, s have increasingly dominated , with Google Chrome establishing a commanding lead globally due to its pre-installation as the default on Android devices, which hold the majority of the mobile OS market. As of January 2026, Chrome commanded 67.28% of the global , reflecting growth from around 60% in 2020 as Android's ecosystem expanded in emerging markets. Apple's maintained a consistent share of 23.23% throughout this timeframe, bolstered by its lock-in as the default and primary browser on devices, where users face restrictions on easily switching alternatives. On Android platforms specifically, Chrome's dominance remained strong, underscoring the platform's role in driving overall trends. captured 3.61% globally, primarily among device users, while other browsers like and accounted for the remaining shares. A notable challenge in measuring mobile shares arises from the prevalence of in-app browsers, such as those embedded in apps like , which handled an estimated 31% of sessions in 2025 and can inflate or distort reported usage for standalone browsers. These in-app experiences often mimic full browsers but bypass traditional metrics, complicating accurate attribution. Data from sources like and highlight these dynamics, emphasizing the need for methodologies that differentiate app-integrated browsing. By 2023, mobile devices accounted for over 60% of global website traffic, surpassing desktop for the first time and prompting browsers to adapt with enhanced mobile-first features like accelerated rendering and privacy tools. This shift has amplified mobile's role in the broader crossover to device-agnostic browsing patterns.

Crossover to Mobile Dominance

The crossover to mobile dominance in web browsing occurred in late 2016, when mobile and tablet traffic first surpassed desktop, reaching 51.3% of global web activity compared to desktop's 48.7%. By the end of 2023, mobile devices accounted for approximately 58% of web traffic, rising to 64.35% by mid-2025. This progression reflects a steady erosion of desktop's former lead, with mobile shares climbing from just under 50% in early 2016 to over 60% within a decade. The implications for browser usage have been profound, as mobile's ascent has disproportionately favored Chrome and Safari, the pre-installed defaults on Android and iOS devices that command the vast majority of smartphones. Chrome, in particular, has seen its global share bolstered by Android's widespread adoption in emerging markets, while Safari benefits from iOS's strong position in developed regions. Conversely, browsers like Firefox, which maintain stronger footholds on desktop but limited presence on mobile, have experienced relative declines in overall usage share as desktop traffic diminishes to around 36% globally. Driving this shift are factors such as explosive smartphone penetration in developing economies; in , for example, mobile devices generate over 80% of by 2025, fueled by affordable devices and expanding / networks. The post-2020 era witnessed accelerated growth in mobile dominance, with the largest single-year jump occurring in 2020 amid the , which heightened overall reliance while reinforcing on-the-go browsing habits. This trend is often visualized in line charts from analytics platforms like Statcounter, where mobile and desktop share curves intersect around 2016 before mobile pulls decisively ahead.

Historical Usage Shares

In the mid-1990s, the web browser market was dominated by , which captured approximately 90% of the usage share by 1995 following its release in late 1994. This rapid ascent was fueled by the browser's innovative features, such as support for extensions and , which enabled richer web experiences at a time when the was expanding from academic and enterprise use to broader commercial adoption. The launch of marked the beginning of the first "" in 1995, as it challenged the status quo and drew intense competition from emerging players. Netscape's high-profile (IPO) on August 9, 1995, further amplified its influence, valuing the company at over $2 billion on its first trading day and signaling the commercial potential of internet technologies. However, Microsoft's entry with (IE) in 1995 began to erode this dominance. By January 1998, Netscape's share had declined to about 54%, as IE gained traction through aggressive marketing and integration strategies. The rivalry intensified with the release of in 1998, which bundled IE 4.0 as a core component, making it the default browser for millions of new Windows users and prompting antitrust scrutiny from the U.S. Department of Justice. By 1999, had surged to around 70% , according to data from firm TheCounter.com, while fell to 25%. Similar trends were reported by WebSideStory, which noted Netscape at 32% for 1999 overall, dropping further to 13.9% by mid-2000 as reached 86%. These shifts reflected Microsoft's leveraging of its operating system monopoly to distribute freely, contrasting with Netscape's licensing model. Measurements during this era were inherently limited by the nascent infrastructure, relying on basic server log analysis from a global user base of under 300 million in 1999, primarily on desktop computers with no significant mobile access.

2000–2010 Developments

During the early , maintained a dominant position in the market, reaching a peak usage share of approximately 95% by 2003, largely due to its tight integration with the Windows operating system and the legacy of the ' resolution in Microsoft's favor. This monopoly was reinforced by enterprise deployments, where server logs sometimes overestimated IE's share due to widespread corporate use of Windows environments, though consumer trends began to show early signs of diversification. Data from TheCounter.com, which tracked global statistics from 2000 to 2009 based on website traffic, illustrated IE's steady hold above 90% through the mid-decade, with minor competitors like and early variants comprising the remainder. The release of 1.0 in November 2004 marked a pivotal shift, reigniting competition by offering an open-source alternative focused on speed, security, and extensibility, which appealed to users frustrated with IE's stagnation. This event spurred the browser market toward innovation, as 's adoption grew rapidly; by 2009, it had achieved a usage share of around 25%, according to Net Applications' global metrics, challenging IE's dominance and promoting standards compliance. Reports from OneStat.com, covering 2002 to 2009, corroborated this rise, showing Mozilla-based browsers climbing from under 5% in 2003 to over 20% by late 2008, driven by marketing and features like tabbed browsing. Google's launch of Chrome in September 2008 introduced further disruption, starting with less than 1% market share but emphasizing performance through its V8 JavaScript engine and minimalist design. By the end of 2010, Chrome had surged to approximately 11% globally, according to StatCounter data, benefiting from aggressive updates and integration with Google's ecosystem, which accelerated the fragmentation of the market. ADTECH Europe's analytics from 2004 to 2009 highlighted regional variations, with IE declining from 92% to 75% in Europe alone, as Firefox and emerging browsers like Safari gained traction among broadband users embracing Web 2.0 applications. Overall, the period transitioned from IE's near-total monopoly to a more competitive landscape, with IE's share eroding to about 60% by 2010 amid antitrust scrutiny and user demands for alternatives, as evidenced by aggregated traffic data from multiple trackers. Mobile browsing remained negligible, accounting for less than 5% of total web traffic through 2010, as smartphone adoption was still nascent and desktop remained the primary access method. This era's developments laid the groundwork for a multi-browser ecosystem, prioritizing user choice and rapid iteration over single-vendor control.

2011–2020 Shifts

During the period from to , the web browser market underwent profound transformations driven by the proliferation of mobile devices and the aggressive expansion of . In , held a dominant position with approximately 35.5% global according to StatCounter data, while Chrome stood at 25.1%, at 23.3%, and at around 8%. By contrast, Net Applications reported a higher share for at over 51% in December , reflecting methodological differences that weighted desktop usage more heavily. Chrome's growth accelerated rapidly, fueled by its integration with Google's ecosystem and superior performance, reaching 63.4% by per StatCounter, while and its successor Edge combined fell to under 5%. remained relatively stable, fluctuating between 3.8% and 4.4% over the decade according to the same source, and expanded to 19.3% by , largely due to Apple's mandates requiring all browsers to use the engine, effectively channeling mobile traffic through Safari's rendering core. A key trend was the crossover to mobile dominance, with mobile browsing surpassing 50% of global by 2017, as reported by based on industry analytics. This shift amplified Chrome's ascent on Android devices and bolstered on , while diminishing the relevance of desktop-centric browsers like . The launch of with in July 2015 initially captured only about 2% of overall browser traffic, hampered by user loyalty to established alternatives. Significant events accelerated these changes, including Microsoft's announcement in 2015 that support for older versions (IE 8, 9, and 10) would end on January 12, 2016, prompting migrations away from legacy Microsoft browsers and further eroding their market position to below 10% by in most metrics. Discrepancies across sources persisted; for instance, Net Applications continued to report higher shares for —around 8-10%—into late , compared to StatCounter's lower figures of under 5%, attributable to differences in , such as Net Applications' emphasis on unique visitors versus StatCounter's page view sampling. W3Counter data from 2011 showed at 32.2%, Chrome at 24.6%, and at 26.3%, aligning more closely with StatCounter trends, while Wikimedia's server log analyses from 2009-2015 indicated similar patterns, with at roughly 30-40% declining steadily. These shifts underscored Chrome's consolidation as the leading browser by 2020, capturing over two-thirds of the market in aggregate reports.

Key Sources and Data Comparisons

Cross-period analyses of browser usage shares reveal notable consistencies in certain trends across independent data providers during the late 2000s. For instance, StatOwl's archived U.S.-focused data from September 2008 to November 2012 and Clicky's global estimates from September 2009 to August 2013 both indicate reaching a peak of approximately 32% around November 2010, reflecting its surge in adoption before the rise of Chrome. These alignments underscore 's brief dominance in that era, despite varying panel sizes and geographic scopes. In contrast, AT Internet's Europe-specific reports from 2007 to 2010, which emphasized ad impression data, showed holding 53.8% in June 2010—higher than global averages of around 50% from broader traffic metrics—highlighting regional preferences for Microsoft's browser in enterprise-heavy markets. Pre-2000 data from WebSideStory, centered on U.S. traffic from February 1999 onward, captured 's rapid ascent to over 70% by mid-2000, driven by bundling with Windows, while ADTECH's European ad network data in the (2004–2009) reported more fragmented shares, with at 60–70% but stronger showings for (around 5–10%) compared to U.S. figures under 2%. In the , Wikimedia's traffic statistics diverged from general web estimates, overrepresenting at 6–8% versus 3–4% globally, due to the site's appeal to tech-savvy users less reliant on default browsers like Chrome or . Discontinued sources like StatOwl provide valuable archived insights into these shifts, accessible via web preservation tools, enabling retrospective validation against active trackers. Longitudinal discrepancies persisted notably between providers, such as Net Applications (now discontinued) reporting higher shares—over 50% until 2019—compared to StatCounter's earlier depiction of decline below 40% by 2012, stemming from Net Applications' emphasis on unique daily users across fewer sites versus StatCounter's pageview-based sampling from millions of domains that favored active web users. By the 2020s, however, major trackers like StatCounter and exhibited greater alignment, with Chrome's global share reported at 73% and 64% respectively in late 2025, converging within 9 percentage points amid standardized methodologies and broader mobile inclusion— a marked improvement from prior variances exceeding 20%.
Period/Source PairKey Consistency/DivergenceExample Metric (IE Share)
StatOwl (2008–2012) vs. Clicky (2009–2013)Similar Firefox peaksFirefox ~32% (2010)
AT Internet (2007–2010, ) vs. GlobalRegional IE overrepresentation53.8% Europe vs. ~50% global (2010)
WebSideStory (pre-2000, ) vs. ADTECH (2000s, )Higher in EuropeIE 70%+ US vs. 60–70% Europe
Wikimedia (2010s) vs. General WebElevated Firefox on 6–8% vs. 3–4%
Applications vs. StatCounter (to 2019)Delayed IE decline in Net>50% vs. <40% (2012)
StatCounter vs. (2020s)Closer Chrome alignment73% vs. 64% (2025)

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