OnePlus Bullets Wireless Z2 ANC Bluetooth in Ear Earphones with Mic, 45dB Hybrid ANC, Bombastic Bass – 12.4 mm Drivers, 10 Mins Charge – 20 Hrs Music, 28 Hrs Battery (Black)
Price: ₹2,449 - ₹2,298.00
(as of Jul 18, 2024 00:56:07 UTC – Details)
From the manufacturer
[ANC]: 45dB Hybrid Active Noise Cancellation combines both FeedForward and FeedBack microphones to maximize frequency range of noise that can be reduced, performing up to 45dB.; [Enhanced Sound Experience]: A large 12.4mm dynamic driver can bring deeper bass and powerful beats. The titanium coating dome can better provide rich audio details at each frequency, so that people can clearly feel every audio beat.
[3-mic AI Call Noise Cancellation]: The advanced 3mics AI call captures and amplifies human voice befittingly when calling by strengthened AI algorithm on software and 3 mics system on hardware. It can recognize high-resolution voice and dynamically filter noise in different environments. The voice of the caller is clear, and can be heard clearly in the noisy environment.
[Battery Life]:The flagship-level battery life delivers up to 28 hours of non-stop music on a single charge with ANC Off. [IP55 rating]: The IP55-rated internals and design ensure your OnePlus Bullets Wireless Z2 ANC stay all-weather ready.
[Quick Switch]: Quick Switch lets you switch between two paired devices, such as your phone and laptop. Users can go from listening to music on your phone to enjoying a movie on your laptop in seconds. [Bluetooth and Low Latency ]: Supports Bluetooth 5.2 and 94ms low-latency dual transmission technology, Whether watching videos online or gaming with friends, the sound is always stable and clear, deliver users a smoother gaming experience.
Model: Bwz-2 Anc; Control Type: Voice Control
Customers say
Customers like the sound quality and bass of the headphones. They say it has a fair and soft bass. However, some customers have reported issues with the performance and connectivity. Opinions are mixed on value, battery life, and comfort.
AI-generated from the text of customer reviews