Google Tensor vs Apple A15 Bionic (4-GPU)

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CPU comparison with benchmarks


Google Tensor CPU1 vs CPU2 Apple A15 Bionic (4-GPU)
Google Tensor Apple A15 Bionic (4-GPU)

CPU comparison

Google Tensor or Apple A15 Bionic (4-GPU) - which processor is faster? In this comparison we look at the differences and analyze which of these two CPUs is better. We compare the technical data and benchmark results.

The Google Tensor has 8 cores with 8 threads and clocks with a maximum frequency of 2.80 GHz. Up to 12 GB of memory is supported in 2 memory channels. The Google Tensor was released in Q4/2021.

The Apple A15 Bionic (4-GPU) has 6 cores with 6 threads and clocks with a maximum frequency of 3.23 GHz. The CPU supports up to 6 GB of memory in 1 memory channels. The Apple A15 Bionic (4-GPU) was released in Q3/2021.
Google Tensor (3) Family Apple A series (22)
Google Tensor (1) CPU group Apple A15 (2)
1 Generation 15
G1 Architecture A15
Mobile Segment Mobile
-- Predecessor --
Google Tensor G2 Successor --

CPU Cores and Base Frequency

The Google Tensor has 8 CPU cores and can calculate 8 threads in parallel. The clock frequency of the Google Tensor is 2.80 GHz while the Apple A15 Bionic (4-GPU) has 6 CPU cores and 6 threads can calculate simultaneously. The clock frequency of the Apple A15 Bionic (4-GPU) is at 3.23 GHz.

Google Tensor Characteristic Apple A15 Bionic (4-GPU)
8 Cores 6
8 Threads 6
hybrid (Prime / big.LITTLE) Core architecture hybrid (big.LITTLE)
No Hyperthreading No
No Overclocking ? No
2.80 GHz
2x Cortex-X1
A-Core 3.23 GHz
2x Avalanche
2.25 GHz
2x Cortex-A76
B-Core 2.02 GHz
4x Blizzard
1.80 GHz
4x Cortex-A55
C-Core --

Artificial Intelligence and Machine Learning

Processors with the support of artificial intelligence (AI) and machine learning (ML) can process many calculations, especially audio, image and video processing, much faster than classic processors. Algorithms for ML improve their performance the more data they have collected via software. ML tasks can be processed up to 10,000 times faster than with a classic processor.

Google Tensor Characteristic Apple A15 Bionic (4-GPU)
Google Tensor AI AI hardware Apple Neural Engine
Google Edge TPU @ 1.6 TOPS AI specifications 16 Neural cores @ 15.8 TOPS

Internal Graphics

The Google Tensor or Apple A15 Bionic (4-GPU) has integrated graphics, called iGPU for short. The iGPU uses the system's main memory as graphics memory and sits on the processor's die.

ARM Mali-G78 MP20 GPU Apple A15 (4 GPU Cores)
0.76 GHz GPU frequency 1.34 GHz
-- GPU (Turbo) --
Vallhall 2 GPU Generation 12
5 nm Technology 5 nm
1 Max. displays 3
20 Compute units 16
320 Shader 512
No Hardware Raytracing No
No Frame Generation No
-- Max. GPU Memory 6 GB
12 DirectX Version --

Hardware codec support

A photo or video codec that is accelerated in hardware can greatly accelerate the working speed of a processor and extend the battery life of notebooks or smartphones when playing videos.

ARM Mali-G78 MP20 GPU Apple A15 (4 GPU Cores)
Decode / Encode Codec h265 / HEVC (8 bit) Decode / Encode
Decode / Encode Codec h265 / HEVC (10 bit) Decode / Encode
Decode / Encode Codec h264 Decode / Encode
Decode / Encode Codec VP9 Decode / Encode
Decode / Encode Codec VP8 Decode / Encode
Decode Codec AV1 No
Decode / Encode Codec AVC Decode
Decode / Encode Codec VC-1 Decode
Decode / Encode Codec JPEG Decode / Encode

Memory & PCIe

The Google Tensor can use up to 12 GB of memory in 2 memory channels. The maximum memory bandwidth is 53.0 GB/s. The Apple A15 Bionic (4-GPU) supports up to 6 GB of memory in 1 memory channels and achieves a memory bandwidth of up to 34.1 GB/s.

Google Tensor Characteristic Apple A15 Bionic (4-GPU)
LPDDR5-5500 Memory LPDDR4X-4266
12 GB Max. Memory 6 GB
2 (Dual Channel) Memory channels 1 (Single Channel)
53.0 GB/s Max. Bandwidth 34.1 GB/s
No ECC No
8.00 MB L2 Cache 16.00 MB
-- L3 Cache 32.00 MB
-- PCIe version --
-- PCIe lanes --
-- PCIe Bandwidth --

Thermal Management

The thermal design power (TDP for short) of the Google Tensor is 10 W, while the Apple A15 Bionic (4-GPU) has a TDP of 7.25 W. The TDP specifies the necessary cooling solution that is required to cool the processor sufficiently.

Google Tensor Characteristic Apple A15 Bionic (4-GPU)
10 W TDP (PL1 / PBP) 7.25 W
-- TDP (PL2) --
-- TDP up --
-- TDP down --
-- Tjunction max. --

Technical details

The Google Tensor is manufactured in 5 nm and has 8.00 MB cache. The Apple A15 Bionic (4-GPU) is manufactured in 5 nm and has a 48.00 MB cache.

Google Tensor Characteristic Apple A15 Bionic (4-GPU)
5 nm Technology 5 nm
Unknown Chip design Chiplet
Armv8-A (64 bit) Instruction set (ISA) Armv8-A (64 bit)
-- ISA extensions --
-- Socket --
None Virtualization None
No AES-NI No
Android Operating systems iOS
Q4/2021 Release date Q3/2021
-- Release price --
show more data show more data


Rate these processors

Here you can rate the Google Tensor to help other visitors make their purchasing decisions. The average rating is 4.3 stars (6 ratings). Rate now:
Here you can rate the Apple A15 Bionic (4-GPU) to help other visitors make their purchasing decisions. The average rating is 4.7 stars (6 ratings). Rate now:


Average performance in benchmarks

⌀ Single core performance in 2 CPU benchmarks
Google Tensor (64%)
Apple A15 Bionic (4-GPU) (100%)
⌀ Multi core performance in 3 CPU benchmarks
Google Tensor (71%)
Apple A15 Bionic (4-GPU) (100%)

Geekbench 5, 64bit (Single-Core)

Geekbench 5 is a cross plattform benchmark that heavily uses the systems memory. A fast memory will push the result a lot. The single-core test only uses one CPU core, the amount of cores or hyperthreading ability doesn't count.
Google Tensor Google Tensor
8C 8T @ 2.80 GHz
1043 (60%)
Apple A15 Bionic (4-GPU) Apple A15 Bionic (4-GPU)
6C 6T @ 3.23 GHz
1745 (100%)

Geekbench 5, 64bit (Multi-Core)

Geekbench 5 is a cross plattform benchmark that heavily uses the systems memory. A fast memory will push the result a lot. The multi-core test involves all CPU cores and taks a big advantage of hyperthreading.
Google Tensor Google Tensor
8C 8T @ 2.80 GHz
2915 (61%)
Apple A15 Bionic (4-GPU) Apple A15 Bionic (4-GPU)
6C 6T @ 3.23 GHz
4777 (100%)

Geekbench 6 (Single-Core)

Geekbench 6 is a benchmark for modern computers, notebooks and smartphones. What is new is an optimized utilization of newer CPU architectures, e.g. based on the big.LITTLE concept and combining CPU cores of different sizes. The single-core benchmark only evaluates the performance of the fastest CPU core, the number of CPU cores in a processor is irrelevant here.
Google Tensor Google Tensor
8C 8T @ 2.80 GHz
1494 (67%)
Apple A15 Bionic (4-GPU) Apple A15 Bionic (4-GPU)
6C 6T @ 3.23 GHz
2245 (100%)

Geekbench 6 (Multi-Core)

Geekbench 6 is a benchmark for modern computers, notebooks and smartphones. What is new is an optimized utilization of newer CPU architectures, e.g. based on the big.LITTLE concept and combining CPU cores of different sizes. The multi-core benchmark evaluates the performance of all of the processor's CPU cores. Virtual thread improvements such as AMD SMT or Intel's Hyper-Threading have a positive impact on the benchmark result.
Google Tensor Google Tensor
8C 8T @ 2.80 GHz
3639 (67%)
Apple A15 Bionic (4-GPU) Apple A15 Bionic (4-GPU)
6C 6T @ 3.23 GHz
5402 (100%)

iGPU - FP32 Performance (Single-precision GFLOPS)

The theoretical computing performance of the internal graphics unit of the processor with simple accuracy (32 bit) in GFLOPS. GFLOPS indicates how many billion floating point operations the iGPU can perform per second.
Google Tensor Google Tensor
ARM Mali-G78 MP20 @ 0.76 GHz
1943 (100%)
Apple A15 Bionic (4-GPU) Apple A15 Bionic (4-GPU)
Apple A15 (4 GPU Cores) @ 1.34 GHz
1370 (71%)

AnTuTu 9 Benchmark

The AnTuTu 9 benchmark is very well suited to measuring the performance of a smartphone. AnTuTu 9 is quite heavy on 3D graphics and can now also use the "Metal" graphics interface. In AnTuTu, memory and UX (user experience) are also tested by simulating browser and app usage. AnTuTu version 9 can compare any ARM CPU running on Android or iOS. Devices may not be directly comparable when benchmarked on different operating systems.

In the AnTuTu 9 benchmark, the single-core performance of a processor is only slightly weighted. The rating is made up of the multi-core performance of the processor, the speed of the working memory, and the performance of the internal graphics.
Google Tensor Google Tensor
8C 8T @ 2.80 GHz
691770 (86%)
Apple A15 Bionic (4-GPU) Apple A15 Bionic (4-GPU)
6C 6T @ 3.23 GHz
806250 (100%)

Performance for Artificial Intelligence (AI) and Machine Learning (ML)

Processors with the support of artificial intelligence (AI) and machine learning (ML) can process many calculations, especially audio, image and video processing, much faster than classic processors. The performance is given in the number (trillions) of arithmetic operations per second (TOPS).
Google Tensor Google Tensor
8C 8T @ 2.80 GHz
1.6 (10%)
Apple A15 Bionic (4-GPU) Apple A15 Bionic (4-GPU)
6C 6T @ 3.23 GHz
15.8 (100%)

AnTuTu 8 Benchmark

The AnTuTu 8 Benchmark measures the performance of a SoC. AnTuTu benchmarks the CPU, GPU, Memory as well as the UX (User Experience) by simulating browser and app usage. AnTuTu can benchmark any ARM CPU that runs under Android or iOS. Devices may not be directly compareable if the benchmark has been performed under different operating systems.

In the AnTuTu 8 benchmark, the single-core performance of a processor is only slightly weighted. The evaluation consists of the multi-core performance of the processor, the speed of the RAM and the performance of the internal graphics.
Google Tensor Google Tensor
8C 8T @ 2.80 GHz
612494 (100%)
Apple A15 Bionic (4-GPU) Apple A15 Bionic (4-GPU)
6C 6T @ 3.23 GHz
0 (0%)

Devices using this processor

Google Tensor Apple A15 Bionic (4-GPU)
Google Pixel 6
Google Pixel 6 Pro
Apple iPhone 13 mini
Apple iPhone 13

News and articles for the Google Tensor and the Apple A15 Bionic (4-GPU)


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