Xiaomi Introduces The New Redmi Note 12 Series

There has been unprecedented success for the Xiaomi Redmi Note series, there are also plans been put in place to launch the new Redmi Note 12 series.Xiaomi Redmi Note 12 Series

A new upgraded technology was also introduced in the new Redmi Note 12 Series which is the fast charging. The highest model of the Redmi Note 12 series will have a fast charging rate of 210W.

Features Of The New Redmi Note 12 Series Xiaomi Redmi Note 12 series

Redmi Note 12 Pro has 2 various types of designs which is the: Shallow Dream Galaxy design and Time Blue design. When compared to the previous series,The company has used a lighter colored design.

Xiaomi newly released Redmi Note 12 series will be powered by a MediaTek processor just as the Redmi Note 11 series.

MediaTek Dimensity 1080 is the processor that will be used on the Redmi Note 12 Pro series. This particular processor is manufactured by TSMC. It has Arm Cortex-78 and Cortex-55 cores. Arm Cortex-A78 runs at up to 2.6GHz and this chipset also supports 5G. Redmi Note 12 Pro and Pro+ will also feature MediaTek Dimensity 1080 but it is not clear enough if the Redmi Note 12 will have it. We assume it will be powered by Dimensity 1080 too.

Also read: Top Xiaomi Smartphones To Buy In 2022

And also Sony’s IMX 766 camera sensor will also be on the Redmi Note 12 series. It is a bad camera sensor that was utilised on Xiaomi 12 and Nothing Phone 1 before. It has a 1/1.56″ of sensor size and a built in optical image stabilization. some people say the Pro series might have a 200MP sensor.

Xiaomi has reported that upgrades have been made to the camera software. Redmi Note 12 series will have an improved night mode and it will also reduce the noise on photos more effectively.

Redmi Note 12 will have the capacity to charge at 67 Watt, Redmi Note 12 Pro will be at 120 Watt, and Redmi Note 12 Pro+ will be at 210 Watt.

Some Xiaomi phones have been able to charge at 120W, but the Redmi Note 12 Pro+ will charge at a fast rate of 210W, which is the first model to achieve this.

 

 

 

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