Apple recently unveiled its latest iPhone 16 and iPhone 16 Pro series. Along them came an all-new A18 bionic processor, which powers the base iPhone 16 and 16 Plus. The chipset is based on TSMC’s second-gen 3nm technology, combining two performance and four efficiency cores, and a 16-core neural engine.
On the opposing end of Apple A18 bionic is the Google Tensor G4, which powers the most recent Pixel lineup. Based on Samsung’s 4nm technology, the Tensor G4 brings an incremental upgrade over its predecessor in performance. To find out how the chipset stacks up against A18 bionic, check out the detailed comparison below.
Note: All benchmark scores mentioned in this article were collated by our internal Core Testing Team (CTT) by testing the Google Pixel 9 (powered by the Tensor G4 SoC) and iPhone 16 Plus (armed with the Apple A18 Bionic).
A18 Bionic vs Tensor G4: Specs Comparison
| Specification | Apple A18 Bionic | Google Tensor G4 |
| Architecture | 3nm, TSMC (N3P) | 4nm, Samsung |
| Cores | 6 | 7 |
| Core configuration | 2x Performance Cores
4x Efficiency Cores |
1x Arm Cortex-X4 (3.1GHz)
3x Arm Cortex-A720 (2.6GHz) 4x Arm Cortex-A520 (1.92GHz) |
| Max Frequency | 4.04GHz | 3.1GHz |
| GPU | 5-core GPU (1398 MHz) | Arm Mali-G715 (MC7)
(940MHz) |
| NPU | 16-core | Third-gen Tensor Processing Unit |
| Memory type | LPDDR5X | LPDDR5X |
| Modem | Snapdragon X75 modem | Exynos 5400 |
| Connectivity | Wi-Fi 7, Bluetooth 5.3 and UWB | Wi-Fi 7, Bluetooth 5.3 |
If we go by the specs on paper, Apple A18 Bionic has outdone its rival Tensor G4 in almost all departments. This saga has been going on since Google introduced the Tensor chipset in its Pixel series. We ran some benchmarks to see how much the gap between the two processors has widened.
A18 Bionic vs Tensor G4: AnTuTu Scores
During our testing, the Apple A18 Bionic was shy of a few thousand from touching the 2 million mark. But unlike the A18 Bionic, the Tensor G4 barely surpassed the 1 million mark. Here is the detailed breakdown of how each chipset scored in different categories:
| Test | A18 Bionic | Tensor G4 |
| CPU | 414,760 | 212,232 |
| GPU | 597,355 | 447,897 |
| Memory | 230,593 | 176,890 |
| UX | 354,106 | 198,449 |
| Overall | 1,596,814 | 1,035,468 |
To give you a clear picture, we also conducted the same AnTuTu test on other flagship chipsets like the Snapdragon 8 Gen 3 (on the iQOO 12), Snapdragon 8 Gen 2 (on the iQOO Neo 9 Pro), and MediaTek Dimensity 9300 (on the Vivo X100). Here’s how each combatant stood up in our test:
A18 Bionic vs Tensor G4: Geekbench Scores
Besides AnTuTu Benchmark, Geekbench is another popular benchmark among Indian tech nerds. It is known for analysing the raw performance of a device’s GPU and CPU. It categorises the result into “Single-Core” and “Multi-Core.” Here’s how both chipsets fared against each other in Geekbench:
| Test | A18 Bionic | Tensor G4 |
| Single-Core | 3,100 | 1,709 |
| Multi-Core | 7,611 | 3,697 |
The result reveals that the A18 Bionic has effortlessly surpassed the Tensor G4 by a huge margin. We also ran the Geekbench test on other flagship processors to see how they match up against each other:
A18 Bionic vs Tensor G4: 3DMark Benchmark Scores
We also conducted the 3DMark Wildlife Extreme Stress test, a 20-minute test evaluating how a device performs under longer periods of heavy load. Like the previous two benchmark tests, this test was no different as the A18 Bionic came on top again with much better results. Here’s the breakdown of how each processor performed in this stress test:
| Test | A18 Bionic | Tensor G4 |
| Wildlife Extreme Stress test | 3,945 | 2,603 |
Apple A18 Bionic vs Google Tensor G4: Verdict
The Apple iPhone 16 Plus, powered by the A18 Bionic, has shone like the moon in every test we ran. Its scores in Geekbench’s single-core and multi-core show that the chipset has been designed for performance. Similarly, the way the A18 Bionic performed in the 3DMark Wildlife Extreme Stress test indicates its reliability in our daily usage.
All in all, there is no denying that the A18 Bionic-charged devices are more reliable and a better companion for productivity-oriented users.
