What processor is Kirin 830 equivalent to Snapdragon?

The performance of Kirin 830 is roughly equivalent to Qualcomm Snapdragon 768G. Specifically: Geekbench 5 running scores: Kirin 830 single-core 650 points, multi-core 1900 points, Snapdragon 768G single-core 700 points, multi-core 2100 points. GPU performance: The Mali-G52 of the Kirin 830 is slightly weaker than the Adreno 620 of the Snapdragon 768G, but there is not much difference in daily use and low- and medium-quality games. Application scenarios: Both are suitable for mid-range smartphones and can run mainstream applications and casual games smoothly.

Which Snapdragon processor is the performance of Kirin 830 equivalent to?

Kirin 830 is a mid-range model in Huawei's Kirin series processors. It will be released in 2021. It uses a 7-nanometer process technology and is equipped with 8 cores, including 4 Cortex-A73 large cores and 4 Cortex-A53 small cores, and the graphics processor is Mali-G52.

Compared with Qualcomm Snapdragon series processors, Kirin 830 is roughly equivalent to the performance level of Snapdragon 768G.

Performance comparison:

In the Geekbench 5 running test, the single-core and multi-core scores of Kirin 830 are about 650 points and 1900 points respectively, while the Snapdragon 768G The scores are 700 points and 2100 points respectively.

In terms of GPU, the performance of the Mali-G52 graphics processor of the Kirin 830 is slightly weaker than the Adreno 620 graphics processor of the Snapdragon 768G, but in daily use and low- and medium-quality game scenarios, the performance of the two is better. no big difference.

Application scenarios:

Both Kirin 830 and Snapdragon 768G are suitable for use on mid-range smartphones and can smoothly run a variety of mainstream applications, including social media, office Tools and casual games, etc.

For light players, both Kirin 830 and Snapdragon 768G can provide a smooth gaming experience, but in high-definition and high-frame-rate gaming scenarios, Snapdragon 768G has a slight advantage.

It should be noted that the performance of a specific model also depends on other factors, such as system optimization, device cooling and memory configuration.

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