Google Tensor vs Apple A10 Fusion

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CPU comparison with benchmarks


Google Tensor CPU1 vs CPU2 Apple A10 Fusion
Google Tensor Apple A10 Fusion

CPU comparison

Google Tensor or Apple A10 Fusion - 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 A10 Fusion has 4 cores with 4 threads and clocks with a maximum frequency of 2.34 GHz. The CPU supports up to 3 GB of memory in 1 memory channels. The Apple A10 Fusion was released in Q3/2016.
Google Tensor (3) Family Apple A series (22)
Google Tensor (1) CPU group Apple A10/A10X (2)
1 Generation 10
G1 Architecture A10
Mobile Segment Mobile
-- Predecessor Apple A9
Google Tensor G2 Successor Apple A11 Bionic

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 A10 Fusion has 4 CPU cores and 4 threads can calculate simultaneously. The clock frequency of the Apple A10 Fusion is at 2.34 GHz.

Google Tensor Characteristic Apple A10 Fusion
8 Cores 4
8 Threads 4
hybrid (Prime / big.LITTLE) Core architecture hybrid (big.LITTLE)
No Hyperthreading No
No Overclocking ? No
2.80 GHz
2x Cortex-X1
A-Core 2.34 GHz
2x Hurricane
2.25 GHz
2x Cortex-A76
B-Core 1.09 GHz
2x Zephyr
1.80 GHz
4x Cortex-A55
C-Core --

NPU AI performance

The performance values of the processor's AI unit. The isolated NPU performance is specified here, the total AI performance (NPU+CPU+iGPU) can be higher. Processors with support for artificial intelligence (AI) and machine learning (ML) can process many calculations, especially audio, image and video processing, much faster than classic processors.

Google Tensor Characteristic Apple A10 Fusion
Google Tensor AI AI hardware --
Google Edge TPU @ 1.6 TOPS AI specifications --
-- NPU + CPU + iGPU --

Integrated graphics (iGPU)

The Google Tensor or Apple A10 Fusion 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 A10
0.76 GHz GPU frequency 0.90 GHz
-- GPU (Turbo) --
Vallhall 2 GPU Generation 7
5 nm Technology 16 nm
1 Max. displays 1
20 Compute units 24
320 Shader 192
No Hardware Raytracing No
No Frame Generation No
-- Max. GPU Memory 4 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 A10
Decode / Encode Codec h265 / HEVC (8 bit) Decode
Decode / Encode Codec h265 / HEVC (10 bit) Decode
Decode / Encode Codec h264 Decode / Encode
Decode / Encode Codec VP9 Decode
Decode / Encode Codec VP8 Decode
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 A10 Fusion supports up to 3 GB of memory in 1 memory channels and achieves a memory bandwidth of up to 25.6 GB/s.

Google Tensor Characteristic Apple A10 Fusion
LPDDR5-5500 Memory LPDDR4-3200
12 GB Max. Memory 3 GB
2 (Dual Channel) Memory channels 1 (Single Channel)
53.0 GB/s Max. Bandwidth 25.6 GB/s
No ECC No
8.00 MB L2 Cache 3.00 MB
-- L3 Cache 4.00 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 A10 Fusion has a TDP of 5 W. The TDP specifies the necessary cooling solution that is required to cool the processor sufficiently.

Google Tensor Characteristic Apple A10 Fusion
10 W TDP (PL1 / PBP) 5 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 A10 Fusion is manufactured in 10 nm and has a 7.00 MB cache.

Google Tensor Characteristic Apple A10 Fusion
5 nm Technology 10 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 Q3/2016
-- 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 (14 ratings). Rate now:
Here you can rate the Apple A10 Fusion to help other visitors make their purchasing decisions. The average rating is 3.5 stars (16 ratings). Rate now:


Average performance in benchmarks

⌀ Single core performance in 2 CPU benchmarks
Google Tensor (100%)
Apple A10 Fusion (66%)
⌀ Multi core performance in 2 CPU benchmarks
Google Tensor (100%)
Apple A10 Fusion (41%)

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 (100%)
Apple A10 Fusion Apple A10 Fusion
4C 4T @ 2.34 GHz
776 (74%)

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 (100%)
Apple A10 Fusion Apple A10 Fusion
4C 4T @ 2.34 GHz
1422 (49%)

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 (100%)
Apple A10 Fusion Apple A10 Fusion
4C 4T @ 2.34 GHz
853 (57%)

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 (100%)
Apple A10 Fusion Apple A10 Fusion
4C 4T @ 2.34 GHz
1207 (33%)

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 A10 Fusion Apple A10 Fusion
Apple A10 @ 0.90 GHz
346 (18%)

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 A10 Fusion Apple A10 Fusion
4C 4T @ 2.34 GHz
227804 (37%)

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 (100%)
Apple A10 Fusion Apple A10 Fusion
4C 4T @ 2.34 GHz
0 (0%)

AI performance (NPU)

The performance values of the processor's AI unit. The isolated NPU performance is given here, the total AI performance (NPU+CPU+iGPU) can be higher.

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 (100%)
Apple A10 Fusion Apple A10 Fusion
4C 4T @ 2.34 GHz
0 (0%)

Devices using this processor

Google Tensor Apple A10 Fusion
Google Pixel 6
Google Pixel 6 Pro
Apple iPhone 7
Apple iPhone 7 Plus
Apple iPad (6. Gen)

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