Google Tensor Benchmark, Test and specs

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The Google Tensor has 8 cores with 8 threads and is based on the 1. gen of the Google Tensor series. The processor was released in Q4/2021. The Google Tensor scores 1,043 points in the Geekbench 5 single-core benchmark. In the Geekbench 5 multi-core benchmark, the result is 2,915 points.
Google Tensor

CPU lineage

The segment in which we have classified the Google Tensor. Here you can see if it is a desktop processor or a mobile processor or which processor may be the successor of the Google Tensor.

Name: Google Tensor
Family: Google Tensor (3)
CPU group: Google Tensor (1)
Architecture: G1
Segment: Mobile
Generation: 1
Predecessor: --
Successor: Google Tensor G2

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. The number of CPU cores greatly affects the speed of the processor and is an important performance indicator.

CPU Cores / Threads: 8 / 8
Core architecture: hybrid (Prime / big.LITTLE)
A-Core: 2x Cortex-X1
B-Core: 2x Cortex-A76
C-Core: 4x Cortex-A55
Hyperthreading / SMT: No
Overclocking: No
A-Core Frequency: 2.80 GHz
B-Core Frequency: 2.25 GHz
C-Core Frequency: 1.80 GHz

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.

AI hardware: Google Tensor AI
AI specifications: Google Edge TPU @ 1.6 TOPS

Internal Graphics

The Google Tensor has integrated graphics, called iGPU for short. Specifically, the Google Tensor uses the ARM Mali-G78 MP20, which has 320 texture shaders and 20 execution units. The iGPU uses the system's main memory as graphics memory and sits on the processor's die.

GPU name: ARM Mali-G78 MP20
GPU frequency: 0.76 GHz
GPU (Turbo): No turbo
Compute units: 20
Shader: 320
Hardware Raytracing: No
Release date: Q4/2021
Max. displays: 1
Generation: Vallhall 2
Direct X: 12
Technology: 5 nm
Max. GPU Memory: --
Frame Generation: No

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.

h265 / HEVC (8 bit): Decode / Encode
h265 / HEVC (10 bit): Decode / Encode
h264: Decode / Encode
VP8: Decode / Encode
VP9: Decode / Encode
AV1: Decode
AVC: Decode / Encode
VC-1: Decode / Encode
JPEG: Decode / Encode

Memory & PCIe

The processor can use up to 12 GB memory in 2 (Dual Channel) memory channels. The maximum memory bandwidth is 53.0 GB/s. The memory type as well as the amount of memory can greatly affect the speed of the system.

Memory type: Memory bandwidth:
LPDDR5-5500
53.0 GB/s
Max. Memory: 12 GB
Memory channels: 2 (Dual Channel)
ECC: No
PCIe:
PCIe Bandwidth: --

Thermal Management

The thermal design power (TDP for short) of the processor is 10 W. The TDP specifies the necessary cooling solution that is required to cool the processor sufficiently. The TDP usually gives a rough idea of the actual power consumption of the CPU.

TDP (PL1 / PBP): 10 W
TDP (PL2): --
TDP up: --
TDP down: --
Tjunction max.: --

Technical details

The Google Tensor is made in 5 nm. The smaller the manufacturing process of a CPU, the more modern and energy-efficient it is. Overall, the processor has 8.00 MB cache. A large cache can greatly speed up the processor's speed in some cases such as games.

Technology: 5 nm
Chip design:
Socket: --
L2-Cache: 8.00 MB
L3-Cache: --
AES-NI: No
Operating systems: Android
Virtualization: None
Instruction set (ISA): Armv8-A (64 bit)
ISA extensions: --
Release date: Q4/2021
Release price: --
Part Number: --
Documents: --

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Benchmark results

Verified Benchmark results
The benchmark results for the Google Tensor have been carefully checked by us. We only publish benchmark results that have been created by us or that have been submitted by a visitor and then checked by a team member. All results are based on and fullfill our benchmark guidelines.

Screenshots:

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.
AMD EPYC 7662 AMD EPYC 7662
64C 128T @ 3.30 GHz
1046
Intel Xeon D-1749NT Intel Xeon D-1749NT
10C 20T @ 3.50 GHz
1045
Intel Xeon D-1739 Intel Xeon D-1739
8C 16T @ 3.50 GHz
1044
Google Tensor Google Tensor
8C 8T @ 2.80 GHz
1043
AMD Ryzen 3 7320U AMD Ryzen 3 7320U
4C 8T @ 4.10 GHz
1043
AMD EPYC 7302P AMD EPYC 7302P
16C 32T @ 3.30 GHz
1043
Intel Xeon Gold 6140 Intel Xeon Gold 6140
18C 36T @ 3.70 GHz
1043

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.
Qualcomm Snapdragon 7 Gen 1 Qualcomm Snapdragon 7 Gen 1
6C 6T @ 2.40 GHz
2932
Intel Core i7-3820QM Intel Core i7-3820QM
4C 8T @ 2.70 GHz
2926
Intel Xeon Bronze 3104 Intel Xeon Bronze 3104
6C 6T @ 1.70 GHz
2917
Google Tensor Google Tensor
8C 8T @ 2.80 GHz
2915
Intel Core i5-4690 Intel Core i5-4690
4C 4T @ 3.70 GHz
2913
Intel Core i7-3610QE Intel Core i7-3610QE
4C 8T @ 3.00 GHz
2911
Intel Xeon D-1622 Intel Xeon D-1622
4C 8T @ 3.00 GHz
2909

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.
Intel Core i7-7740X Intel Core i7-7740X
4C 8T @ 4.50 GHz
1497
Intel Core i7-10710U Intel Core i7-10710U
6C 12T @ 4.70 GHz
1496
Qualcomm Snapdragon 7+ Gen 2 Qualcomm Snapdragon 7+ Gen 2
8C 8T @ 2.91 GHz
1496
Google Tensor Google Tensor
8C 8T @ 2.80 GHz
1494
Intel Core i9-9980HK Intel Core i9-9980HK
8C 16T @ 5.00 GHz
1492
Intel Core i5-10400H Intel Core i5-10400H
4C 8T @ 4.60 GHz
1490
Intel Xeon W-2145 Intel Xeon W-2145
8C 16T @ 4.50 GHz
1487

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.
Intel Core i7-4850HQ Intel Core i7-4850HQ
4C 8T @ 3.50 GHz
3648
Intel Xeon E5-2620 v2 Intel Xeon E5-2620 v2
6C 12T @ 2.30 GHz
3643
Intel Xeon E3-1220 v5 Intel Xeon E3-1220 v5
4C 4T @ 3.30 GHz
3642
Google Tensor Google Tensor
8C 8T @ 2.80 GHz
3639
Intel Core i7-4950HQ Intel Core i7-4950HQ
4C 8T @ 2.40 GHz
3637
Intel Core i7-4722HQ Intel Core i7-4722HQ
4C 8T @ 2.40 GHz
3633
Intel Core i5-5675R Intel Core i5-5675R
4C 4T @ 3.30 GHz
3632

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.
AMD Ryzen 7 5700U AMD Ryzen 7 5700U
AMD Radeon RX Vega 8 (Renoir) @ 1.90 GHz
1946
AMD Ryzen 9 5900HX AMD Ryzen 9 5900HX
AMD Radeon RX Vega 8 (Renoir) @ 1.90 GHz
1946
AMD Ryzen 9 5980HX AMD Ryzen 9 5980HX
AMD Radeon RX Vega 8 (Renoir) @ 1.90 GHz
1946
Google Tensor Google Tensor
ARM Mali-G78 MP20 @ 0.76 GHz
1943
Intel Core Ultra 7 155UL Intel Core Ultra 7 155UL
Intel Iris Xe 4 Core Graphics 64 EUs (Meteor Lake) @ 1.95 GHz
1935
Intel Core Ultra 7 155U Intel Core Ultra 7 155U
Intel Iris Xe 4 Core Graphics 64 EUs (Meteor Lake) @ 1.95 GHz
1935
Intel Core i7-1165G7 Intel Core i7-1165G7
Intel Iris Xe Graphics 96 (Tiger Lake) @ 1.30 GHz
1933

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.
Qualcomm Snapdragon 870 Qualcomm Snapdragon 870
8C 8T @ 3.20 GHz
727650
Samsung Exynos 2100 Samsung Exynos 2100
8C 8T @ 2.90 GHz
724660
Qualcomm Snapdragon 865+ Qualcomm Snapdragon 865+
8C 8T @ 3.10 GHz
716498
Google Tensor Google Tensor
8C 8T @ 2.80 GHz
691770
MediaTek Dimensity 1300 MediaTek Dimensity 1300
8C 8T @ 3.00 GHz
689042
MediaTek Dimensity 1200 MediaTek Dimensity 1200
8C 8T @ 3.00 GHz
669042
Qualcomm Snapdragon 865 Qualcomm Snapdragon 865
8C 8T @ 2.84 GHz
668494

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 A14 Bionic Apple A14 Bionic
6C 6T @ 3.00 GHz
628047
MediaTek Dimensity 1200 MediaTek Dimensity 1200
8C 8T @ 3.00 GHz
627817
Qualcomm Snapdragon 865+ Qualcomm Snapdragon 865+
8C 8T @ 3.10 GHz
616032
Google Tensor Google Tensor
8C 8T @ 2.80 GHz
612494
Samsung Exynos 2100 Samsung Exynos 2100
8C 8T @ 2.90 GHz
602990
Qualcomm Snapdragon 865 Qualcomm Snapdragon 865
8C 8T @ 2.84 GHz
598103
Qualcomm Snapdragon 860 Qualcomm Snapdragon 860
8C 8T @ 2.96 GHz
560128

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).
Qualcomm Snapdragon 665 Qualcomm Snapdragon 665
8C 8T @ 2.00 GHz
3
Qualcomm Snapdragon 670 Qualcomm Snapdragon 670
8C 8T @ 2.00 GHz
3
Qualcomm Snapdragon 8cx Qualcomm Snapdragon 8cx
8C 8T @ 2.84 GHz
3
Google Tensor Google Tensor
8C 8T @ 2.80 GHz
1.6
MediaTek Helio G99 MediaTek Helio G99
8C 8T @ 2.20 GHz
1
Apple A11 Bionic Apple A11 Bionic
6C 6T @ 2.39 GHz
0.6
MediaTek MT8183 MediaTek MT8183
8C 8T @ 2.00 GHz
0.5

Benchmarks


Description of the processor

The Google Tensor is a 64-bit system-on-a-chip (SOC) processor developed by the American company Google. It was released in the fourth quarter of 2021 and was used in Googles own smartphones Google Pixel 6, Google Pixel 6 Pro and Google Pixel 6a. The Google Tensor is the first generation of Tensor processors and is manufactured with a structure width of 5 nanometers. With the Google Tensor G2, the successor to the first generation came in 2022, which will be installed in the Google Pixel 7.

The Google Tensor is based on a hybrid Prime big.LITTLE core architecture and has a total of eight processor cores. These are divided into 2 prime cores, 2 performance cores and 4 efficiency cores. The two prime cores clock at up to 2.80 gigahertz and are based on an ARM Cortex-X1 core. The two performance cores are based on the ARM Cortex-A76 and clock at up to 2.25 gigahertz. The four efficiency cores, which are used when no computing power is needed to extend the battery life of the smartphone, are based on the ARM Cortex-A55 and clock at a maximum of 1.80 gigahertz.

With the Google Tensor AI (Google Edge TPU with 1.6 TOPS performance), special hardware is built into the Google Tensor, which supports the calculation of AI or ML in hardware.

The internal graphics unit in the Google Tensor is the ARM Mali-G78 with 20 execution units. This iGPU has a total of 320 shader units and clocks at up to 760 megahertz; the graphics unit does not have a turbo mode. It achieves an FP32 computing power of 1943 GigaFLOPS, with single precision. The ARM Mail-G78 is manufactured with a structure width of 5 nanometers and comes from the Valhall 2 generation.

The Google Tensor G1 was equipped with up to 12 gigabytes of LPDDR5-5500 memory and has 2 memory channels.



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