Google Tensor G3 vs Apple M3 Pro (11-CPU 14-GPU)

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CPU comparison with benchmarks


Google Tensor G3 CPU1 vs CPU2 Apple M3 Pro (11-CPU 14-GPU)
Google Tensor G3 Apple M3 Pro (11-CPU 14-GPU)

CPU comparison

Google Tensor G3 or Apple M3 Pro (11-CPU 14-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 G3 has 8 cores with 8 threads and clocks with a maximum frequency of 2.91 GHz. Up to 12 GB of memory is supported in 2 memory channels. The Google Tensor G3 was released in Q3/2023.

The Apple M3 Pro (11-CPU 14-GPU) has 11 cores with 11 threads and clocks with a maximum frequency of 4.06 GHz. The CPU supports up to 36 GB of memory in 2 memory channels. The Apple M3 Pro (11-CPU 14-GPU) was released in Q4/2023.
Google Tensor (3) Family Apple M series (25)
Google Tensor G3 (1) CPU group Apple M3 (6)
3 Generation 3
G3 Architecture M3
Mobile Segment Mobile
Google Tensor Predecessor Apple M2 Pro (10-CPU 16-GPU)
-- Successor --

CPU Cores and Base Frequency

The Google Tensor G3 is a 8 core processor with a clock frequency of 2.91 GHz. The Apple M3 Pro (11-CPU 14-GPU) has 11 CPU cores with a clock frequency of 0.70 GHz (4.06 GHz).

Google Tensor G3 Characteristic Apple M3 Pro (11-CPU 14-GPU)
8 Cores 11
8 Threads 11
hybrid (Prime / big.LITTLE) Core architecture hybrid (big.LITTLE)
No Hyperthreading No
No Overclocking ? No
2.91 GHz
1x Cortex-X3
A-Core 0.70 GHz (4.06 GHz)
5x P-Core
2.37 GHz
4x Cortex-A715
B-Core 0.74 GHz (2.75 GHz)
6x E-Core
1.70 GHz
4x Cortex-A510
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 G3 Characteristic Apple M3 Pro (11-CPU 14-GPU)
Google Tensor AI AI hardware Apple Neural Engine
Google Edge TPU AI specifications 16 Neural cores @ 35 TOPS

Internal Graphics

The integrated graphics unit of a processor is not only responsible for the pure image output on the system, but can also significantly increase the efficiency of the system with the support of modern video codecs.

ARM Immortalis-G715 MP10 GPU Apple M3 Pro (14 Core)
0.89 GHz GPU frequency 0.39 GHz
-- GPU (Turbo) 1.40 GHz
Vallhall GPU Generation --
4 nm Technology 3 nm
0 Max. displays 3
10 Compute units 224
-- Shader 1792
No Hardware Raytracing Yes
No Frame Generation No
-- Max. GPU Memory 36 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 Immortalis-G715 MP10 GPU Apple M3 Pro (14 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 / Encode Codec AV1 Decode
Decode / Encode Codec AVC Decode
Decode / Encode Codec VC-1 Decode
Decode / Encode Codec JPEG Decode / Encode

Memory & PCIe

The Google Tensor G3 supports a maximum of 12 GB of memory in 2 memory channels. The Apple M3 Pro (11-CPU 14-GPU) can connect up to 36 GB of memory in 2 memory channels.

Google Tensor G3 Characteristic Apple M3 Pro (11-CPU 14-GPU)
LPDDR5-5500 Memory LPDDR5-6400
12 GB Max. Memory 36 GB
2 (Dual Channel) Memory channels 2 (Dual Channel)
53.0 GB/s Max. Bandwidth 153.6 GB/s
No ECC No
-- L2 Cache 36.00 MB
-- L3 Cache --
-- PCIe version 4.0
-- PCIe lanes --
-- PCIe Bandwidth --

Thermal Management

The TDP (Thermal Design Power) of a processor specifies the required cooling solution. The Google Tensor G3 has a TDP of 10 W, that of the Apple M3 Pro (11-CPU 14-GPU) is 35 W.

Google Tensor G3 Characteristic Apple M3 Pro (11-CPU 14-GPU)
10 W TDP (PL1 / PBP) 35 W
-- TDP (PL2) --
-- TDP up --
-- TDP down --
-- Tjunction max. 100 °C

Technical details

The Google Tensor G3 has a 0.00 MB cache, while the Apple M3 Pro (11-CPU 14-GPU) cache has a total of 36.00 MB.

Google Tensor G3 Characteristic Apple M3 Pro (11-CPU 14-GPU)
4 nm Technology 3 nm
Chiplet Chip design Chiplet
Armv9-A (64 bit) Instruction set (ISA) Armv8-A (64 bit)
-- ISA extensions Rosetta 2 x86-Emulation
-- Socket --
None Virtualization Apple Virtualization Framework
No AES-NI Yes
Android Operating systems macOS, iPadOS
Q3/2023 Release date Q4/2023
-- Release price --
show more data show more data


Rate these processors

Here you can rate the Google Tensor G3 to help other visitors make their purchasing decisions. The average rating is 3.6 stars (28 ratings). Rate now:
Here you can rate the Apple M3 Pro (11-CPU 14-GPU) to help other visitors make their purchasing decisions. The average rating is 4.9 stars (223 ratings). Rate now:


Average performance in benchmarks

⌀ Single core performance in 2 CPU benchmarks
Google Tensor G3 (56%)
Apple M3 Pro (11-CPU 14-GPU) (100%)
⌀ Multi core performance in 2 CPU benchmarks
Google Tensor G3 (30%)
Apple M3 Pro (11-CPU 14-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 G3 Google Tensor G3
8C 8T @ 2.91 GHz
1267 (55%)
Apple M3 Pro (11-CPU 14-GPU) Apple M3 Pro (11-CPU 14-GPU)
11C 11T @ 4.06 GHz
2305 (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 G3 Google Tensor G3
8C 8T @ 2.91 GHz
3631 (27%)
Apple M3 Pro (11-CPU 14-GPU) Apple M3 Pro (11-CPU 14-GPU)
11C 11T @ 3.80 GHz
13255 (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 G3 Google Tensor G3
8C 8T @ 2.91 GHz
1759 (56%)
Apple M3 Pro (11-CPU 14-GPU) Apple M3 Pro (11-CPU 14-GPU)
11C 11T @ 4.06 GHz
3125 (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 G3 Google Tensor G3
8C 8T @ 2.91 GHz
4533 (33%)
Apple M3 Pro (11-CPU 14-GPU) Apple M3 Pro (11-CPU 14-GPU)
11C 11T @ 3.80 GHz
13755 (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 G3 Google Tensor G3
ARM Immortalis-G715 MP10 @ 0.89 GHz
1 (0%)
Apple M3 Pro (11-CPU 14-GPU) Apple M3 Pro (11-CPU 14-GPU)
Apple M3 Pro (14 Core) @ 1.40 GHz
4970 (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 G3 Google Tensor G3
8C 8T @ 2.91 GHz
0 (0%)
Apple M3 Pro (11-CPU 14-GPU) Apple M3 Pro (11-CPU 14-GPU)
11C 11T @ 4.06 GHz
139 (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 G3 Google Tensor G3
8C 8T @ 2.91 GHz
0 (0%)
Apple M3 Pro (11-CPU 14-GPU) Apple M3 Pro (11-CPU 14-GPU)
11C 11T @ 4.06 GHz
847 (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 G3 Google Tensor G3
8C 8T @ 2.91 GHz
0 (0%)
Apple M3 Pro (11-CPU 14-GPU) Apple M3 Pro (11-CPU 14-GPU)
11C 11T @ 4.06 GHz
1889 (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 G3 Google Tensor G3
8C 8T @ 2.91 GHz
0 (0%)
Apple M3 Pro (11-CPU 14-GPU) Apple M3 Pro (11-CPU 14-GPU)
11C 11T @ 3.80 GHz
13289 (100%)

AnTuTu 10 Benchmark

The AnTuTu 10 benchmark is one of the best-known benchmarks for mobile processors, which is now available in version 10. There is a version for Android-based smartphones and tablets, as well as a version for Apple mobile devices, i.e. iPhones and iPads.

The Antutu 10 benchmark has 3 phases. In the first phase, the device's RAM is tested, in phase 2 the graphics are tested and in the final phase the entire device is pushed to its performance limits by rendering 3D graphics.

Antutu 10 is therefore ideal for comparing the performance of different devices.
Google Tensor G3 Google Tensor G3
8C 8T @ 2.91 GHz
1106280 (100%)
Apple M3 Pro (11-CPU 14-GPU) Apple M3 Pro (11-CPU 14-GPU)
11C 11T @ 0.70 GHz
0 (0%)

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 G3 Google Tensor G3
8C 8T @ 2.91 GHz
894587 (100%)
Apple M3 Pro (11-CPU 14-GPU) Apple M3 Pro (11-CPU 14-GPU)
11C 11T @ 0.70 GHz
0 (0%)

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 G3 Google Tensor G3
8C 8T @ 2.91 GHz
0 (0%)
Apple M3 Pro (11-CPU 14-GPU) Apple M3 Pro (11-CPU 14-GPU)
11C 11T @ 0.70 GHz
35 (100%)

Devices using this processor

Google Tensor G3 Apple M3 Pro (11-CPU 14-GPU)
Google Pixel 8
Google Pixel 8 Pro
Apple MacBook Pro 14 (2023)
Apple MacBook Pro 16 (2023)

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