User agent detail

Mozilla/5.0 (Linux i686; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/30.0.1599.114 Safari/537.36 SRAF/3.0 HbbTV/1.1.1 (+DRM+TRICKMODE; SERAPHIC; TV101; sw-v1.0; hw-v1.0) CE-HTML/1.0 FXM-U2FsdGVkX1+tH+IvjK4AyJIfuJUAyORg8ptl86EQiyLy7LytAiEgU3mKjwgF90uz-END
GeneralDeviceBot
ProviderBrowserEngineOSBrandModelTypeIs mobileIs touchIs botNameTypeParse timeActions
Test suite
WhichBrowser
v2.0.18
vendor/whichbrowser/parser/tests/data/television/other.yaml
Seraphic Sraf 3.0Blink televisionclosecloseclose0 Detail
Providers
BrowscapFull
6014
Chrome 30.0Blink Linux Desktop0.032 Detail
BrowscapLite
6014
Chrome closeLinux closecloseDesktopcloseclosecloseclose0.005 Detail
BrowscapPhp
6014
Chrome 30.0closeLinux closecloseDesktopclose0.039 Detail
DonatjUAParser
v0.5.1
Chrome 30.0.1599.114closeclosecloseclosecloseclosecloseclosecloseclose0 Detail
JenssegersAgent
v2.3.3
Chrome 30.0.1599.114closeLinux closecloseclosecloseclose0.001 Detail
NeutrinoApiCom

Chrome 30.0.1599.114closeLinux desktop-browsercloseclose0.26302 Detail
PiwikDeviceDetector
3.6.1
Chrome 30.0Blink GNU/Linux tv0.003 Detail
SinergiBrowserDetector
6.0.1
Chrome 30.0.1599.114closeLinux closecloseclosecloseclose0 Detail
UAParser
v3.4.5
HbbTV 1.1.1closeLinux SERAPHICTV101closeclosecloseclose0.003 Detail
UserAgentApiCom

Chrome 30.0.1599.114WebKit 537.36closeclosecloseDesktopclosecloseclose0.15601 Detail
UserAgentStringCom

Chrome 30.0.1599.114closeLinux closecloseclosecloseclose0.097 Detail
WhatIsMyBrowserCom

Chrome 30.0.1599.114WebKit 537.36Linux closeclosecloseclosecloseclose0.38602 Detail
WhichBrowser
v2.0.18
Seraphic Sraf 3.0Blink televisioncloseclose0.006 Detail
Woothee
v1.2.0
Chrome 30.0.1599.114closeclosecloseclosepcclosecloseclose0 Detail
Wurfl
1.7.1.0
Chrome 30.0.1599.114closeLinux i686 SmartTVSmart-TVcloseclose0.016 Detail
Zsxsoft
1.3
Google Chrome 30.0.1599.114closeGNU/Linux closeclosecloseclosecloseclose0 Detail

About this comparison

The primary goal of this project is simple
I wanted to know which user agent parser is the most accurate in each part - device detection, bot detection and so on...

The secondary goal is to provide a source for all user agent parsers to improve their detection based on this results.

You can also improve this further, by suggesting ideas at ThaDafinser/UserAgentParserComparison

The comparison is based on the abstraction by ThaDafinser/UserAgentParser
Comparison created 2016-05-10 07:53:10 | by ThaDafinser