Google Tensor SoC Beats Snapdragon 888, Exynos 2100, Kirin 9000 in GPU Benchmark Tests: Report


The Google Pixel 6 and Google Pixel 6 Pro were launched last week and a recent report suggests that the Google-designed Tensor SoC that powers both the smartphones, Qualcomm Snapdragon 888, Samsung Exynos 2100 and HiSilicon in GPU benchmarks. Beats Kirin 9000 chipset. These benchmarks — conducted on 3DMark Wildlife, Wildlife Extreme and Wildlife Stress — were posted by a user on Reddit. The Tensor chipset of the Google Pixel 6 seems to beat the other flagship Android chipsets by a decent score in each of the three tests. It should be noted that these results do not indicate real world performance.

According to Reddit user Greg (u/grt3), he received google pixel 6 quick and Asked If users want to know anything on the social media platform. After a user asked about the GPU performance of the Google Tensor SoC, Greg tested the smartphone on 3DMark Wildlife, Wildlife Extreme and Wildlife Stress tests.

Google’s Tensor SoC is said to have scored 6,666 points scoring 2,028 at 39 frames per second in the Wildlife test and 12.8 frames per second in the Wildlife Extreme test. Whereas in the wildlife stress test lasting 20 minutes, it had a best loop score of 2,129 and a low loop score of 1,193 with 56 percent stability.

Tipster Golden Reviewer (@Golden_Reviewer) share an image of Samsung Galaxy S21 Ultra And this Huawei Mate 40 Pro, showing Wildlife Extreme Score. The overall score of the Galaxy smartphone with Snapdragon 888 chipset was 1,494 points at 8.90 frames per second. The Exynos 2100 chipset variant, on the other hand, scored 1,793 points at 10.70 frames per second. The Huawei smartphone with Kirin 9000 SoC scored 2,004 with 12 frames per second.

These results indicate that the Google Tensor SoC may be the best Android smartphone SoC in the market in terms of graphical performance, but this information should be taken with a pinch of salt as not many reviewers have benchmarked the new one. launched Pixel 6 series or Tensor SoC.