Google Tensor gets trounced by the A15 Bionic in new Machine Learning benchmark test
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Apple’s A15 Bionic chipset trounced the Google Tensor in an ML-focused benchmark test
Magic Eraser, Motion Mode, Face Unblur are examples of computational photography driven by the Tensor. And the chip also helps the Pixel offer ambient features such as the Pixel 6 series’ always-on displays and the Now Playing feature that tells you the name of a song (and the artist) that is playing in the background. The Tensor chip also allows the new Pixels to deliver the most accurate Automatic Speech Recognition (ASR) ever created by Google without consuming too much battery life.
So you would think that when it comes to Machine Learning, the Google Tensor would outperform the A15 Bionic in a benchmark test, but that is not what took place. Instead, on the Geekbench ML test, the Tensor was trounced by Apple’s A15 Bionic. The developer of the benchmark test, Primate Labs, says that it is a cross-platform test that is designed to “help you understand whether your device is ready to run the latest machine learning applications.”
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In the Geekbench ML TensorFlow Lite CPU test, the Apple A15 scored 939 compared to just 307 for the Google Tensor. The GPU test was not as lopsided, but Apple’s latest chipset still won the battle 2727 (Core ML) while the Tensor scores just 1720 (NNAPI). Overall, the A15 Bionic scored 5,934 on the Geekbenck ML test compared to 3,455 for the Tensor. So even looking at how both chipsets handle Machine Learning tasks, which is supposed to be the strength of the Tensor chip, the A15 Bionic is 71% faster.
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Besides, we won’t know what to really expect from the Pixel 6 Pro battery for more than a week since it takes a total of two weeks for the adaptive battery feature (which uses Machine Learning) to understand how you use the phone and the battery. And if you need to stretch out the battery on the Pixel 6 and Pixel 6 Pro, disabling 5G will reportedly add more battery life to the handsets.
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