Google Tensor Chip Core Code Name Revealed, Similar to Samsung Exynos 2100

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Yukesh Prabhu
Yukesh Prabhu
A dedicated student of Journalism with high aspiration in Reporting and content writing. A keen communicator and researcher with an expertise in content curation.

Google recently launched the Pixel 6/Pro Mobile phones, power-packed with google’s home-brewed Tensor chip, which Google has promised to offer blazingly fast performance and secured experience to users; officials and tech tipsters previously said that this SoC was developed in collaboration with Google and Samsung, predominantly fabricated using Samsung’s 5nm process.

According to Anandtech, in foreign lands, users of the Google Pixel 6 series have located the core code name of the Tensor chip, which is quite similar to the Samsung Exynos 2100 chip. In addition,  Anandtech informed that Google Tensor’s kernel code name is S5E9845, while in the flip, Samsung Exynos 2100 is S5E9840.

While seeing the Code name, we could judge at the same time. The code name is akin to Samsung Exynos 2100. This implicit, as might be expected, that the Tensor chip couldn’t be the one with highly self-developed chips in the Google home. Partly, it can be based on Samsung Exynos SoC. The performance of the Tensor chip is indubitably higher than Exynos 2100; judging from current exposure scores, Google has not officially disclosed the core performance of the chip and code name as well.

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In addition, Twitter user @andreif7 also leaked a screenshot displaying the codename of the Tensor chip in the Android system as “Exynos.” 

Furthermore, some foreign developers have found the detailed specifications of Google’s Tensor SoC in the Pixel 6 Pro system, but it has not been confirmed officially. 

• 2x ARM Cortex-X1 large core, 2.802 GHz 

• 2x ARM Cortex-A76 large core, 2.2563 GHz 

• 4x ARM Cortex-A55 small core, 1.80 GHz 

• ARM Mali-G78 MP20 GPU, 20 cores 

Some contrast features are also developed in Google’s home-brewed Tensor chip compared with Exynos 2100, such as a dedicated processing unit for machine learning operations, image processing, etc., and also has a Tensor security core.

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