Apple A13 Bionic vs Google Tensor G2

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CPU comparison with benchmarks


Apple A13 Bionic CPU1 vs CPU2 Google Tensor G2
Apple A13 Bionic Google Tensor G2

CPU comparison

In this CPU comparison, we compare the Apple A13 Bionic and the Google Tensor G2 and use benchmarks to check which processor is faster.

We compare the Apple A13 Bionic 6 core processor released in Q3/2019 with the Google Tensor G2 which has 8 CPU cores and was introduced in Q4/2022.
Apple A series (22) Family Google Tensor (3)
Apple A13 (1) CPU group Google Tensor G2 (1)
13 Generation 2
A13 (Lightning / Thunder) Architecture G2
Mobile Segment Mobile
Apple A12 Bionic Predecessor Google Tensor
Apple A14 Bionic Successor --

CPU Cores and Base Frequency

The Apple A13 Bionic is a 6 core processor with a clock frequency of 2.65 GHz. The processor can compute 6 threads at the same time. The Google Tensor G2 clocks with 2.85 GHz, has 8 CPU cores and can calculate 8 threads in parallel.

Apple A13 Bionic Characteristic Google Tensor G2
6 Cores 8
6 Threads 8
hybrid (big.LITTLE) Core architecture hybrid (Prime / big.LITTLE)
No Hyperthreading No
No Overclocking ? No
2.65 GHz
2x Lightning
A-Core 2.85 GHz
2x Cortex-X1
1.80 GHz
4x Thunder
B-Core 2.35 GHz
2x Cortex-A78
-- C-Core 1.80 GHz
4x Cortex-A55

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.

Apple A13 Bionic Characteristic Google Tensor G2
Apple Neural Engine AI hardware Google Tensor AI
8 Neural cores @ 6 TOPS AI specifications Google Edge TPU @ 4 TOPS

Internal Graphics

Graphics (iGPU) integrated into the processor not only enable image output without having to rely on a dedicated graphics solution, but can also efficiently accelerate video playback.

Apple A13 GPU ARM Mali-G710 MP7
1.35 GHz GPU frequency 0.90 GHz
-- GPU (Turbo) --
10 GPU Generation Vallhall 3
7 nm Technology 4 nm
1 Max. displays 1
16 Compute units 7
256 Shader --
No Hardware Raytracing No
No Frame Generation No
4 GB Max. GPU Memory --
-- DirectX Version 12

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.

Apple A13 GPU ARM Mali-G710 MP7
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
No Codec AV1 Decode
Decode Codec AVC Decode / Encode
Decode Codec VC-1 Decode / Encode
Decode / Encode Codec JPEG Decode / Encode

Memory & PCIe

Up to 4 GB of memory in a maximum of 1 memory channels is supported by the Apple A13 Bionic, while the Google Tensor G2 supports a maximum of 12 GB of memory with a maximum memory bandwidth of 53.0 GB/s enabled.

Apple A13 Bionic Characteristic Google Tensor G2
LPDDR4X-4266 Memory LPDDR5-5500
4 GB Max. Memory 12 GB
1 (Single Channel) Memory channels 2 (Dual Channel)
34.1 GB/s Max. Bandwidth 53.0 GB/s
No ECC No
8.00 MB L2 Cache 8.00 MB
-- L3 Cache 4.00 MB
-- PCIe version --
-- PCIe lanes --
-- PCIe Bandwidth --

Thermal Management

The Apple A13 Bionic has a TDP of 6 W. The TDP of the Google Tensor G2 is 10 W. System integrators use the TDP of the processor as a guide when dimensioning the cooling solution.

Apple A13 Bionic Characteristic Google Tensor G2
6 W TDP (PL1 / PBP) 10 W
-- TDP (PL2) --
-- TDP up --
-- TDP down --
-- Tjunction max. --

Technical details

The Apple A13 Bionic has 8.00 MB cache and is manufactured in 7 nm. The cache of Google Tensor G2 is at 12.00 MB. The processor is manufactured in 4 nm.

Apple A13 Bionic Characteristic Google Tensor G2
7 nm Technology 4 nm
Chiplet Chip design Chiplet
Armv8-A (64 bit) Instruction set (ISA) Armv8-A (64 bit)
-- ISA extensions --
-- Socket --
None Virtualization None
No AES-NI No
iOS Operating systems Android
Q3/2019 Release date Q4/2022
-- Release price --
show more data show more data


Rate these processors

Here you can rate the Apple A13 Bionic to help other visitors make their purchasing decisions. The average rating is 3.9 stars (22 ratings). Rate now:
Here you can rate the Google Tensor G2 to help other visitors make their purchasing decisions. The average rating is 4.0 stars (13 ratings). Rate now:


Average performance in benchmarks

⌀ Single core performance in 2 CPU benchmarks
Apple A13 Bionic (100%)
Google Tensor G2 (82%)
⌀ Multi core performance in 3 CPU benchmarks
Apple A13 Bionic (94%)
Google Tensor G2 (95%)

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.
Apple A13 Bionic Apple A13 Bionic
6C 6T @ 2.65 GHz
1336 (100%)
Google Tensor G2 Google Tensor G2
8C 8T @ 2.85 GHz
1068 (80%)

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.
Apple A13 Bionic Apple A13 Bionic
6C 6T @ 2.65 GHz
3429 (100%)
Google Tensor G2 Google Tensor G2
8C 8T @ 2.85 GHz
3149 (92%)

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.
Apple A13 Bionic Apple A13 Bionic
6C 6T @ 2.65 GHz
1710 (100%)
Google Tensor G2 Google Tensor G2
8C 8T @ 2.85 GHz
1426 (83%)

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.
Apple A13 Bionic Apple A13 Bionic
6C 6T @ 2.65 GHz
3599 (100%)
Google Tensor G2 Google Tensor G2
8C 8T @ 2.85 GHz
3342 (93%)

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.
Apple A13 Bionic Apple A13 Bionic
Apple A13 @ 1.35 GHz
691 (99%)
Google Tensor G2 Google Tensor G2
ARM Mali-G710 MP7 @ 0.90 GHz
700 (100%)

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.
Apple A13 Bionic Apple A13 Bionic
6C 6T @ 2.65 GHz
648406 (82%)
Google Tensor G2 Google Tensor G2
8C 8T @ 2.85 GHz
789419 (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).
Apple A13 Bionic Apple A13 Bionic
6C 6T @ 2.65 GHz
6 (100%)
Google Tensor G2 Google Tensor G2
8C 8T @ 2.85 GHz
4 (67%)

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.
Apple A13 Bionic Apple A13 Bionic
6C 6T @ 2.65 GHz
523650 (100%)
Google Tensor G2 Google Tensor G2
8C 8T @ 2.85 GHz
0 (0%)

Estimated results for PassMark CPU Mark

Some of the CPUs listed below have been benchmarked by CPU-monkey. However the majority of CPUs have not been tested and the results have been estimated by a CPU-monkey’s secret proprietary formula. As such they do not accurately reflect the actual Passmark CPU mark values and are not endorsed by PassMark Software Pty Ltd.
Apple A13 Bionic Apple A13 Bionic
6C 6T @ 2.65 GHz
5368 (100%)
Google Tensor G2 Google Tensor G2
8C 8T @ 2.85 GHz
0 (0%)

Devices using this processor

Apple A13 Bionic Google Tensor G2
Apple iPhone 11
Apple iPhone 11 Pro
Apple iPhone 11 Pro Max
iPhone SE
Google Pixel 7
Google Pixel 7 Pro

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