Apple A17 Pro vs Google Tensor G3

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CPU comparison with benchmarks


Apple A17 Pro CPU1 vs CPU2 Google Tensor G3
Apple A17 Pro Google Tensor G3

CPU comparison

Apple A17 Pro or Google Tensor G3 - 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 Apple A17 Pro has 6 cores with 6 threads and clocks with a maximum frequency of 3.78 GHz. Up to 8 GB of memory is supported in 1 memory channels. The Apple A17 Pro was released in Q3/2023.

The Google Tensor G3 has 8 cores with 8 threads and clocks with a maximum frequency of 2.91 GHz. The CPU supports up to 12 GB of memory in 2 memory channels. The Google Tensor G3 was released in Q3/2023.
Apple A series (22) Family Google Tensor (3)
Apple A17 (1) CPU group Google Tensor G3 (1)
17 Generation 3
A17 Architecture G3
Mobile Segment Mobile
Apple A16 Bionic Predecessor Google Tensor
-- Successor --

CPU Cores and Base Frequency

The Apple A17 Pro is a 6 core processor with a clock frequency of 3.78 GHz. The Google Tensor G3 has 8 CPU cores with a clock frequency of 2.91 GHz.

Apple A17 Pro Characteristic Google Tensor G3
6 Cores 8
6 Threads 8
hybrid (big.LITTLE) Core architecture hybrid (Prime / big.LITTLE)
No Hyperthreading No
No Overclocking ? No
3.78 GHz A-Core 2.91 GHz
1x Cortex-X3
2.11 GHz B-Core 2.37 GHz
4x Cortex-A715
-- C-Core 1.70 GHz
4x Cortex-A510

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 A17 Pro Characteristic Google Tensor G3
Apple Neural Engine AI hardware Google Tensor AI
16 Neural cores @ 35 TOPS AI specifications Google Edge TPU

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.

Apple A17 Pro (6 GPU Cores) GPU ARM Immortalis-G715 MP10
1.40 GHz GPU frequency 0.89 GHz
-- GPU (Turbo) --
-- GPU Generation Vallhall
3 nm Technology 4 nm
3 Max. displays 0
24 Compute units 10
768 Shader --
Yes Hardware Raytracing No
No Frame Generation No
6 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 A17 Pro (6 GPU Cores) GPU ARM Immortalis-G715 MP10
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 Decode / Encode
Decode Codec AVC Decode / Encode
Decode Codec VC-1 Decode / Encode
Decode / Encode Codec JPEG Decode / Encode

Memory & PCIe

The Apple A17 Pro supports a maximum of 8 GB of memory in 1 memory channels. The Google Tensor G3 can connect up to 12 GB of memory in 2 memory channels.

Apple A17 Pro Characteristic Google Tensor G3
LPDDR5-6400 Memory LPDDR5-5500
8 GB Max. Memory 12 GB
1 (Single Channel) Memory channels 2 (Dual Channel)
51.2 GB/s Max. Bandwidth 53.0 GB/s
No ECC No
20.00 MB L2 Cache --
24.00 MB L3 Cache --
-- PCIe version --
-- PCIe lanes --
-- PCIe Bandwidth --

Thermal Management

The TDP (Thermal Design Power) of a processor specifies the required cooling solution. The Apple A17 Pro has a TDP of 11 W, that of the Google Tensor G3 is 10 W.

Apple A17 Pro Characteristic Google Tensor G3
11 W TDP (PL1 / PBP) 10 W
-- TDP (PL2) --
-- TDP up --
-- TDP down --
-- Tjunction max. --

Technical details

The Apple A17 Pro has a 44.00 MB cache, while the Google Tensor G3 cache has a total of 0.00 MB.

Apple A17 Pro Characteristic Google Tensor G3
3 nm Technology 4 nm
Chiplet Chip design Chiplet
Armv8.6-A (64 bit) Instruction set (ISA) Armv9-A (64 bit)
-- ISA extensions --
-- Socket --
None Virtualization None
No AES-NI No
iOS Operating systems Android
Q3/2023 Release date Q3/2023
-- Release price --
show more data show more data


Rate these processors

Here you can rate the Apple A17 Pro to help other visitors make their purchasing decisions. The average rating is 3.9 stars (62 ratings). Rate now:
Here you can rate the Google Tensor G3 to help other visitors make their purchasing decisions. The average rating is 3.9 stars (13 ratings). Rate now:


Average performance in benchmarks

⌀ Single core performance in 2 CPU benchmarks
Apple A17 Pro (100%)
Google Tensor G3 (60%)
⌀ Multi core performance in 3 CPU benchmarks
Apple A17 Pro (100%)
Google Tensor G3 (68%)

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 A17 Pro Apple A17 Pro
6C 6T @ 3.78 GHz
2140 (100%)
Google Tensor G3 Google Tensor G3
8C 8T @ 2.91 GHz
1267 (59%)

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 A17 Pro Apple A17 Pro
6C 6T @ 3.78 GHz
5868 (100%)
Google Tensor G3 Google Tensor G3
8C 8T @ 2.91 GHz
3631 (62%)

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 A17 Pro Apple A17 Pro
6C 6T @ 3.78 GHz
2952 (100%)
Google Tensor G3 Google Tensor G3
8C 8T @ 2.91 GHz
1759 (60%)

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 A17 Pro Apple A17 Pro
6C 6T @ 3.78 GHz
7462 (100%)
Google Tensor G3 Google Tensor G3
8C 8T @ 2.91 GHz
4533 (61%)

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 A17 Pro Apple A17 Pro
Apple A17 Pro (6 GPU Cores) @ 1.40 GHz
2147 (100%)
Google Tensor G3 Google Tensor G3
ARM Immortalis-G715 MP10 @ 0.89 GHz
1 (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.
Apple A17 Pro Apple A17 Pro
6C 6T @ 3.78 GHz
1108570 (100%)
Google Tensor G3 Google Tensor G3
8C 8T @ 2.91 GHz
894587 (81%)

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 A17 Pro Apple A17 Pro
6C 6T @ 3.78 GHz
35 (100%)
Google Tensor G3 Google Tensor G3
8C 8T @ 2.91 GHz
0 (0%)

Devices using this processor

Apple A17 Pro Google Tensor G3
Apple iPhone 15 Pro
Apple iPhone 15 Pro Max
Google Pixel 8
Google Pixel 8 Pro

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