Google Tensor G2 vs Apple A16 Bionic: Google has joined Apple in making chipsets for its own smartphones. The latest Google Pixel 7 Pro debuts with Google’s new Tensor G2 chipset inside but how good is this new chipset when compared with the Apple A16 Bionic chipset that Apple used in the iPhone 14 Pro?
The Apple A16 Bionic chipset is the most powerful SoC in the industry right now. It can render high graphics faster than any other chipset in a 2022 smartphone. However, the Tensor G2 chipset just showed that there is more to a chipset than just powerful CPU and GPU cores. So, in this Google Tensor G2 vs Apple A16 Bionic, we’ll highlight all the specs of these chipsets for you to understand the differences and decide which is better.
Google Tensor G2 vs Apple A16 Bionic
Process Technology & Power Management
The Google Tensor G2 and Apple A16 Bionic chipsets are both built on a 4nm process technology. Chipsets on the 4nm process are usually fast and use less power to send and received data. This is because the components of the chipsets are not far from each other and can easily and quickly communicate, hence the faster data transfer using less power.
However, according to Apple, the CPU performance of the A16 Bionic chipset is about 20% better than the competition (Tensor G2 inclusive). Apple also said that the power efficiency of the A16 Bionic is also about 10-15% better than the one in the competition. This means the A16 Bionic chipset process data faster and uses less power when doing so. This explains why the iPhone 14 Pro series have good battery life (up to 10 hours) and faster graphics rendering. See our Apple iPhone Battery Test of 2022 for more on the Apple iPhone 14 battery life.
Google Tensor G2 vs Apple A16 Bionic: CPU
The Tensor G2 features an Octa-core CPU. It has two power cores (2x Cortex-X1) with a CPU speed of 2.85GHz, two big efficiency cores (2x Cortex-A78) with a CPU speed of 2.35GHz, and four small efficiency cores (4x Cortex-A55) with a CPU speed of 1.80GHz. In comparison, the A16 Bionic features a Hexa-core (6-core CPU) while the Snapdragon 8+ Gen 1 features an Octa-core CPU (8-core CPU). The A16 Bionic has two power cores (2x Everest) with a CPU speed of 3.46GHz and four efficiency cores (4x Sawtooth) with a CPU speed of 2.00GHz.
The two power cores of the A16 Bionic chipset are faster than the two power cores of the Tensor G2. This is because the CPU cores of the Tensor G2 are two years older than those of the A16 Bionic. When it also comes to power efficiency, the efficiency cores of the A16 Bionic are newer and better than those of the Tensor G2. Note that this does not mean that the CPU cores of the Tensor G2 are not fast or not power efficient. It only means that those of the A16 Bionic chipset is better. See Geekbench tests of the Google Tensor G2 and Apple A16 Bionic chipsets in the table below.
Google Tensor G2 vs Apple A16 Bionic: GPU & AI
The Google Tensor G2 features the Mali-G710 MC10 GPU while the Apple A16 Bionic features the Apple GPU (5-core graphics). The Mali-G710 MC10 GPU is no match for the Apple GPU (5-core graphics) when it comes to graphics rendering. The Apple GPU (5-core graphics) renders graphics faster and can perform at its optimum for longer because it uses less power. But there is a twist when it comes to AI.
It seems the intention of Google with the Google Pixel 7 and Pixel 7 Pro is not just about power but also integration and automation. The Tensor G2 chipset has one of the best AI integration you can think of. Yes, the A16 bionic chipset is also very good in the AI department but it seems Google sacrificed power to enhance the AI capabilities of the Tensor G2 chip. Let’s talk about some of the AI capabilities of the Tensor G2 in its ISP below.
Google Tensor G2 vs Apple A16 Bionic: ISP
The Image Signal Processing (ISP) on the A16 Bionic is the Photonic Engine while that of the Google Tensor G2 is the Tensor Processing Unit (TPU). The TPU in the Tensor G2 is Google’s custom next-generation Tensor Processing Unit (TPU) and it brings some major improvements over its predecessor and some really impressive automation.
The new Tensor Processing Unit (TPU) supports up to a 108MP camera sensor while the Photonic Engine currently supports a 48MP camera sensor. Both ISPs allow devices to record videos in RAW format and support Dolby Vision, HDR10+, HDR10, 4K video recording, etc. With the Tensor Processing Unit (TPU), you can enjoy features such as Guided Frame, Photo Unblur, Pro Level Zoom, etc.
The Guided Frame is a new feature that allows blind people to take perfect selfie photos. Once turned on, Pixel 7 with the help of the Tensor Processing Unit (TPU) will use a voice guide to direct blind people to place the camera on the phone and take a perfect selfie photo. Photo Unblur is another impressive feature that allows users to clear out any blur from photos. The new Tensor Processing Unit (TPU) also now makes it possible for users to scan more than 100 languages and automatically translate them.
These are the few impressive new automatic features that the Tensor G2 chipset brings. Yes, it might not have those powerful Cores as the A16 Bionic, but it sure has those small important daily features that are very useful for every user.
Google Tensor G2 vs Apple A16 Bionic: Connectivity
The connectivity options available on both chipsets are very similar. Both chipsets have support for 5G connectivity but have different 5G MODEM inside. The Tensor G2 has the G5300B 5G MODEM from Samsung while the A16 Bionic has the X65 MODEM from Qualcomm.
Other connectivity options available on both chipsets are NFC, Bluetooth 5.3, GPS, Ultra Wideband (UWB) support, an online payment system, Wi-Fi 6E (Tensor G2), Wi-Fi 6 (A16 Bionic), etc. But only the Apple A16 Bionic chipset has support for the Emergency SOS via satellite (SMS sending/receiving) connectivity feature.
Google Tensor G2 vs Apple A16 Bionic: Conclusion
So, between the Google Tensor G2 and Apple A16 Bionic which is better? Well, when it comes to performance and power efficiency, the Apple A16 Bionic chipset is better than the Google Tensor G2 chipset. This is because the A16 Bionic has faster CPU cores and a more powerful GPU. But this Google Tensor G2 vs Apple A16 Bionic comparison has shown that power is not everything.
The Tensor G2 chipset might not be as powerful as the A16 Bionic chipset but it makes up for it with its extra AI features. These features are simple but very useful features for everyday users while also maintaining a decent-performing chipset.
Truth is if you’re the type of person that loves playing games and doing heavy graphics work with your phone, buying a phone powered by the Apple A16 Bionic chipset is best for you. But if you’re like me who is not a heavy gamer but someone who loves AI and automation a lot, then you’ll find the extra AI features of the Tensor G2 chipset to be very useful (just like I do).