User agent detail

BlackBerry9800/6.0.0.600 Profile/MIDP-2.1 Configuration/CLDC-1.1 VendorID/102
GeneralDeviceBot
ProviderBrowserEngineOSBrandModelTypeIs mobileIs touchIs botNameTypeParse timeActions
Source result (test suite)
whichbrowser/parser
/tests/data/mobile/os-blackberry.yaml
BlackBerry Browser BlackBerry OS 6.0 RIMBlackBerry Torch 9800mobile:smartyes Detail
Providers
BrowscapPhp
6012
BlackBerry 6.0WebKit RIM OS 6.0RIMTorchMobile Phoneyesyes0.006 Detail
DonatjUAParser
v0.5.0
BlackBerry9800 6.0.0.600closeclosecloseclosecloseclosecloseclosecloseclose0 Detail
NeutrinoApiCom
BlackBerry Browser closeRIM OS RIMBlackBerry 9800mobile-browseryescloseclose0.17898 Detail
PiwikDeviceDetector
3.5.2
BlackBerry Browser BlackBerry OS 6.0RIMBlackBerry 9800smartphoneyes0.004 Detail
SinergiBrowserDetector
6.0.0
BlackBerry 6.0.0.600closeBlackBerry closecloseyesclosecloseclose0 Detail
UAParser
v3.4.5
BlackBerry 9800closeBlackBerry OS 6.0.0BlackBerry9800closeclosecloseclose0.008 Detail
UserAgentStringCom
BlackBerry closeBlackBerryOS 6.0.0closecloseclosecloseclose0.05899 Detail
WhatIsMyBrowserCom
Blackberry Browser 6.0.0.600 BlackBerry OS BlackBerryBlackBerry 9800closeclosecloseclosecloseclose0.48195 Detail
WhichBrowser
2.0.10
BlackBerry Browser BlackBerry OS 6.0RIMBlackBerry Torch 9800mobile:smartyescloseclose0.003 Detail
Woothee
v1.2.0
closeclosecloseclosesmartphoneclosecloseclose0.001 Detail
Wurfl
1.6.4
BlackBerry Browser 6.4closeBlackBerry 6.4RIMBlackBerry 9800Feature Phoneyesyescloseclose0.013 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 2016-02-13 13:34:45 | by ThaDafinser