Google Tensor G2 vs Apple M2 (8-GPU)

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CPU comparison with benchmarks


Google Tensor G2 CPU1 vs CPU2 Apple M2 (8-GPU)
Google Tensor G2 Apple M2 (8-GPU)

CPU comparison

Google Tensor G2 or Apple M2 (8-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 G2 has 8 cores with 8 threads and clocks with a maximum frequency of 2.85 GHz. Up to 12 GB of memory is supported in 2 memory channels. The Google Tensor G2 was released in Q4/2022.

The Apple M2 (8-GPU) has 8 cores with 8 threads and clocks with a maximum frequency of 3.50 GHz. The CPU supports up to 24 GB of memory in 2 memory channels. The Apple M2 (8-GPU) was released in Q2/2022.
Google Tensor (3) Family Apple M series (23)
Google Tensor G2 (1) CPU group Apple M2 (8)
2 Generation 2
G2 Architecture M2
Mobile Segment Mobile
Google Tensor Predecessor Apple M1
-- Successor Apple M3 (8-GPU)

CPU Cores and Base Frequency

The Google Tensor G2 has 8 CPU cores and can calculate 8 threads in parallel. The clock frequency of the Google Tensor G2 is 2.85 GHz while the Apple M2 (8-GPU) has 8 CPU cores and 8 threads can calculate simultaneously. The clock frequency of the Apple M2 (8-GPU) is at 0.66 GHz (3.50 GHz).

Google Tensor G2 Characteristic Apple M2 (8-GPU)
8 Cores 8
8 Threads 8
hybrid (Prime / big.LITTLE) Core architecture hybrid (big.LITTLE)
No Hyperthreading No
No Overclocking ? No
2.85 GHz
2x Cortex-X1
A-Core 0.66 GHz (3.50 GHz)
4x Avalanche
2.35 GHz
2x Cortex-A78
B-Core 0.60 GHz (2.42 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 G2 Characteristic Apple M2 (8-GPU)
Google Tensor AI AI hardware Apple Neural Engine
Google Edge TPU @ 4 TOPS AI specifications 16 Neural cores @ 15.8 TOPS

Internal Graphics

The Google Tensor G2 or Apple M2 (8-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-G710 MP7 GPU Apple M2 (8 Core)
0.90 GHz GPU frequency 0.45 GHz
-- GPU (Turbo) 1.40 GHz
Vallhall 3 GPU Generation 2
4 nm Technology 5 nm
1 Max. displays 2
7 Compute units 128
-- Shader 1024
No Hardware Raytracing No
No Frame Generation No
-- Max. GPU Memory 24 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-G710 MP7 GPU Apple M2 (8 Core)
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
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 G2 can use up to 12 GB of memory in 2 memory channels. The maximum memory bandwidth is 53.0 GB/s. The Apple M2 (8-GPU) supports up to 24 GB of memory in 2 memory channels and achieves a memory bandwidth of up to 102.4 GB/s.

Google Tensor G2 Characteristic Apple M2 (8-GPU)
LPDDR5-5500 Memory LPDDR5-6400
12 GB Max. Memory 24 GB
2 (Dual Channel) Memory channels 2 (Dual Channel)
53.0 GB/s Max. Bandwidth 102.4 GB/s
No ECC No
8.00 MB L2 Cache 20.00 MB
4.00 MB L3 Cache --
-- PCIe version 4.0
-- PCIe lanes --
-- PCIe Bandwidth --

Thermal Management

The thermal design power (TDP for short) of the Google Tensor G2 is 10 W, while the Apple M2 (8-GPU) has a TDP of 20 W. The TDP specifies the necessary cooling solution that is required to cool the processor sufficiently.

Google Tensor G2 Characteristic Apple M2 (8-GPU)
10 W TDP (PL1 / PBP) 20 W
-- TDP (PL2) --
-- TDP up 25 W
-- TDP down 10 W
-- Tjunction max. 100 °C

Technical details

The Google Tensor G2 is manufactured in 4 nm and has 12.00 MB cache. The Apple M2 (8-GPU) is manufactured in 5 nm and has a 20.00 MB cache.

Google Tensor G2 Characteristic Apple M2 (8-GPU)
4 nm Technology 5 nm
Chiplet Chip design Chiplet
Armv8-A (64 bit) Instruction set (ISA) Armv8.5-A (64 bit)
-- ISA extensions Rosetta 2 x86-Emulation
-- Socket --
None Virtualization Apple Virtualization Framework
No AES-NI Yes
Android Operating systems macOS, iPadOS
Q4/2022 Release date Q2/2022
-- Release price --
show more data show more data


Rate these processors

Here you can rate the Google Tensor G2 to help other visitors make their purchasing decisions. The average rating is 4.0 stars (12 ratings). Rate now:
Here you can rate the Apple M2 (8-GPU) to help other visitors make their purchasing decisions. The average rating is 4.9 stars (47 ratings). Rate now:


Average performance in benchmarks

⌀ Single core performance in 2 CPU benchmarks
Google Tensor G2 (56%)
Apple M2 (8-GPU) (100%)
⌀ Multi core performance in 2 CPU benchmarks
Google Tensor G2 (35%)
Apple M2 (8-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 G2 Google Tensor G2
8C 8T @ 2.85 GHz
1068 (57%)
Apple M2 (8-GPU) Apple M2 (8-GPU)
8C 8T @ 3.50 GHz
1874 (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 G2 Google Tensor G2
8C 8T @ 2.85 GHz
3149 (36%)
Apple M2 (8-GPU) Apple M2 (8-GPU)
8C 8T @ 3.50 GHz
8853 (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 G2 Google Tensor G2
8C 8T @ 2.85 GHz
1426 (55%)
Apple M2 (8-GPU) Apple M2 (8-GPU)
8C 8T @ 3.50 GHz
2596 (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 G2 Google Tensor G2
8C 8T @ 2.85 GHz
3342 (33%)
Apple M2 (8-GPU) Apple M2 (8-GPU)
8C 8T @ 3.50 GHz
10062 (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 G2 Google Tensor G2
ARM Mali-G710 MP7 @ 0.90 GHz
700 (25%)
Apple M2 (8-GPU) Apple M2 (8-GPU)
Apple M2 (8 Core) @ 1.40 GHz
2840 (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 G2 Google Tensor G2
8C 8T @ 2.85 GHz
4 (25%)
Apple M2 (8-GPU) Apple M2 (8-GPU)
8C 8T @ 0.66 GHz
15.8 (100%)

Cinebench 2024 (Single-Core)

The Cinebench 2024 benchmark is based on the Redshift rendering engine, which is also used in Maxon's 3D program Cinema 4D. The benchmark runs are each 10 minutes long to test whether the processor is limited by its heat generation.
Google Tensor G2 Google Tensor G2
8C 8T @ 2.85 GHz
0 (0%)
Apple M2 (8-GPU) Apple M2 (8-GPU)
8C 8T @ 3.50 GHz
120 (100%)

Cinebench 2024 (Multi-Core)

The Multi-Core test of the Cinebench 2024 benchmark uses all cpu cores to render using the Redshift rendering engine, which is also used in Maxons Cinema 4D. The benchmark run is 10 minutes long to test whether the processor is limited by its heat generation.
Google Tensor G2 Google Tensor G2
8C 8T @ 2.85 GHz
0 (0%)
Apple M2 (8-GPU) Apple M2 (8-GPU)
8C 8T @ 3.50 GHz
555 (100%)

Cinebench R23 (Single-Core)

Cinebench R23 is the successor of Cinebench R20 and is also based on the Cinema 4 Suite. Cinema 4 is a worldwide used software to create 3D forms. The single-core test only uses one CPU core, the amount of cores or hyperthreading ability doesn't count.
Google Tensor G2 Google Tensor G2
8C 8T @ 2.85 GHz
0 (0%)
Apple M2 (8-GPU) Apple M2 (8-GPU)
8C 8T @ 3.50 GHz
1592 (100%)

Cinebench R23 (Multi-Core)

Cinebench R23 is the successor of Cinebench R20 and is also based on the Cinema 4 Suite. Cinema 4 is a worldwide used software to create 3D forms. The multi-core test involves all CPU cores and taks a big advantage of hyperthreading.
Google Tensor G2 Google Tensor G2
8C 8T @ 2.85 GHz
0 (0%)
Apple M2 (8-GPU) Apple M2 (8-GPU)
8C 8T @ 3.50 GHz
8558 (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.
Google Tensor G2 Google Tensor G2
8C 8T @ 2.85 GHz
789419 (100%)
Apple M2 (8-GPU) Apple M2 (8-GPU)
8C 8T @ 0.66 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.
Google Tensor G2 Google Tensor G2
8C 8T @ 2.85 GHz
0 (0%)
Apple M2 (8-GPU) Apple M2 (8-GPU)
8C 8T @ 3.50 GHz
15472 (100%)

Blender 2.81 (bmw27)

Blender is a free 3D graphics software for rendering (creating) 3D bodies, which can also be textured and animated in the software. The Blender benchmark creates predefined scenes and measures the time (s) required for the entire scene. The shorter the time required, the better. We selected bmw27 as the benchmark scene.
Google Tensor G2 Google Tensor G2
8C 8T @ 2.85 GHz
0 (0%)
Apple M2 (8-GPU) Apple M2 (8-GPU)
8C 8T @ 3.50 GHz
277 (100%)

CPU performance per watt (efficiency)

Efficiency of the processor under full load in the Cinebench R23 (multi-core) benchmark. The benchmark result is divided by the average energy required (CPU package power in watts). The higher the value, the more efficient the CPU is under full load.
Google Tensor G2 Google Tensor G2
2.85 GHz
0 (0%)
Apple M2 (8-GPU) Apple M2 (8-GPU)
8,558 CB R23 MC @ 20 W
428 (100%)

Devices using this processor

Google Tensor G2 Apple M2 (8-GPU)
Google Pixel 7
Google Pixel 7 Pro
Apple MacBook Air 14 (2022)
Apple MacBook Pro 13 (2022)

News and articles for the Google Tensor G2 and the Apple M2 (8-GPU)

Most popular processors in the first half of 2022
Most popular processors in the first half of 2022
Posted by Stefan on 2022-07-05
In the past we had repeatedly written about our most popular processors. Since this format was quiet popular, I would like to continue this today and introduce you the most popular processors in the first half of 2022.

With more than 2 million page views per month, CPU-Monkey is one of the biggest comparison sites for processors and is currently available in 16 languages.
Apple M2 Pro with more CPU cores and production in 3 nm ?
Apple M2 Pro with more CPU cores and production in 3 nm ?
Posted by Stefan on 2022-06-28
After Apple surprisingly presented the normal Apple M2 processor as the first successor to the Apple M1 already in June 2022, the Apple M2 Pro and the Apple M2 Max may follow in autumn. The difference in performance compared to the basic version could be even greater this time and range from 25 to 40 percent.

In this article we describe how Apple could realize this and why the price should also go up.
Apple M2 vs Apple M1 - What are the differences?
Apple M2 vs Apple M1 - What are the differences?
Posted by Stefan on 2022-06-09
During WWDC 2022 on June 6th, 2022 Apple surprisingly presented its new Apple M2 processor. This will initially be installed in a completely revised Apple MacBook Air with 13.6 inches, a even thinner form factor and new colors. Apple also updated the already known (old) Apple MacBook Pro 13.3 with touch bar.

Many leakers had counted on Apple not presenting its new second-generation M processor until the fall. But things turned out differently. And there is very likely a reason for that: the improvements in the Apple M2 are limited compared to the predecessor.

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