Google Tensor G2 Benchmark, Test and specs

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The Google Tensor G2 has 8 cores with 8 threads and is based on the 2. gen of the Google Tensor series. The processor was released in Q4/2022. The Google Tensor G2 scores 1,068 points in the Geekbench 5 single-core benchmark. In the Geekbench 5 multi-core benchmark, the result is 3,149 points.
Google Tensor G2

At a glance

Name: Google Tensor G2
Family: Google Tensor (4)
CPU group: Google Tensor G2 (1)
Architecture: G2
Technology: 4 nm
Segment: Smartphone / Tablet
Generation: 2
Predecessor: Google Tensor
Successor: --

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. 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-A78
C-Core: 4x Cortex-A55
Hyperthreading / SMT: No
Overclocking: No
A-Core Frequency: 2.85 GHz
B-Core Frequency: 2.35 GHz
C-Core Frequency: 1.80 GHz

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.

AI hardware: Google Tensor AI
AI specifications: Google Edge TPU @ 4 TOPS
NPU + CPU + iGPU: --

Integrated graphics (iGPU)

The Google Tensor G2 has integrated graphics, called iGPU for short. Specifically, the Google Tensor G2 uses the ARM Mali-G710 MP7, which has -- texture shaders and 7 execution units. The iGPU uses the system's main memory as graphics memory and sits on the processor's die.

GPU name: ARM Mali-G710 MP7
GPU frequency: 0.90 GHz
GPU (Turbo): No turbo
Compute units: 7
Shader: --
Hardware Raytracing: No
Release date: Q2/2021
Max. displays: 1
Generation: Vallhall 3
Direct X: 12
Technology: 4 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 G2 is made in 4 nm. The smaller the manufacturing process of a CPU, the more modern and energy-efficient it is. Overall, the processor has 12.00 MB cache. A large cache can greatly speed up the processor's speed in some cases such as games.

Technology: 4 nm
Chip design: Chiplet
Socket: --
L2-Cache: 8.00 MB
L3-Cache: 4.00 MB
AES-NI: No
Operating systems: Android
Virtualization: None
Instruction set (ISA): Armv8-A (64 bit)
ISA extensions: --
Release date: Q4/2022
Release price: --
Part Number: --
Documents: --

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Benchmark results

Verified Benchmark results
The benchmark results for the Google Tensor G2 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 6 (Single-Core)

Geekbench 6 is a partial load benchmark for modern computers, notebooks and smartphones. In the single-core test, only the fastest CPU core is measured. The test run simulates the performance in practice.
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
Samsung Exynos 2200 Samsung Exynos 2200
8C 8T @ 2.80 GHz
1428
Google Tensor G2 Google Tensor G2
8C 8T @ 2.85 GHz
1426
Apple A12Z Bionic Apple A12Z Bionic
8C 8T @ 2.49 GHz
1351
Apple A12X Bionic Apple A12X Bionic
8C 8T @ 2.49 GHz
1341
Samsung Exynos 2100 Samsung Exynos 2100
8C 8T @ 2.90 GHz
1334

Geekbench 6 (Multi-Core)

The practical Geekbench 6 multi-core benchmark tests the system's performance under partial load. The processor's maximum power consumption is far from being used up.
Qualcomm Snapdragon 888+ Qualcomm Snapdragon 888+
8C 8T @ 3.00 GHz
3436
MediaTek Kompanio 1300T MediaTek Kompanio 1300T
8C 8T @ 2.60 GHz
3389
MediaTek Dimensity 8200 MediaTek Dimensity 8200
8C 8T @ 3.10 GHz
3369
Google Tensor G2 Google Tensor G2
8C 8T @ 2.85 GHz
3342
Samsung Exynos 2100 Samsung Exynos 2100
8C 8T @ 2.90 GHz
3339
Qualcomm Snapdragon 865 Qualcomm Snapdragon 865
8C 8T @ 2.84 GHz
3244
HiSilicon Kirin 990 4G HiSilicon Kirin 990 4G
8C 8T @ 2.86 GHz
3244

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 A12 Bionic Apple A12 Bionic
6C 6T @ 2.49 GHz
1116
Qualcomm Snapdragon 8cx Gen 3 Qualcomm Snapdragon 8cx Gen 3
8C 8T @ 3.00 GHz
1096
Qualcomm Snapdragon 888 Qualcomm Snapdragon 888
8C 8T @ 2.84 GHz
1088
Google Tensor G2 Google Tensor G2
8C 8T @ 2.85 GHz
1068
HiSilicon Kirin 9000 HiSilicon Kirin 9000
8C 8T @ 3.13 GHz
1063
HiSilicon Kirin 9000E HiSilicon Kirin 9000E
8C 8T @ 3.13 GHz
1063
Samsung Exynos 1580 Samsung Exynos 1580
8C 8T @ 2.91 GHzNot verified
1046

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 888 Qualcomm Snapdragon 888
8C 8T @ 2.84 GHz
3250
Qualcomm Snapdragon 870 Qualcomm Snapdragon 870
8C 8T @ 3.20 GHz
3240
MediaTek Dimensity 1300 MediaTek Dimensity 1300
8C 8T @ 3.00 GHz
3225
Google Tensor G2 Google Tensor G2
8C 8T @ 2.85 GHz
3149
MediaTek Kompanio 1300T MediaTek Kompanio 1300T
8C 8T @ 2.60 GHz
3088
MediaTek Dimensity 1200 MediaTek Dimensity 1200
8C 8T @ 3.00 GHz
3075
Qualcomm Snapdragon 780G Qualcomm Snapdragon 780G
8C 8T @ 2.40 GHz
3027

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.
HiSilicon Kirin 990 4G HiSilicon Kirin 990 4G
ARM Mali-G76 MP16 @ 0.60 GHz
737
Qualcomm Snapdragon 845 Qualcomm Snapdragon 845
Qualcomm Adreno 630 @ 0.70 GHz
737
Qualcomm Snapdragon 850 Qualcomm Snapdragon 850
Qualcomm Adreno 630 @ 0.70 GHz
737
Google Tensor G2 Google Tensor G2
ARM Mali-G710 MP7 @ 0.90 GHz
700
Apple A13 Bionic Apple A13 Bionic
Apple A13 @ 1.35 GHz
691
HiSilicon Kirin 820 5G HiSilicon Kirin 820 5G
ARM Mali-G57 MP6 @ 0.85 GHz
653
HiSilicon Kirin 820E 5G HiSilicon Kirin 820E 5G
ARM Mali-G57 MP6 @ 0.85 GHz
653

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 888 Qualcomm Snapdragon 888
8C 8T @ 2.84 GHz
816812
MediaTek Dimensity 8100 MediaTek Dimensity 8100
8C 8T @ 2.85 GHz
811000
Apple A15 Bionic (4-GPU) Apple A15 Bionic (4-GPU)
6C 6T @ 3.23 GHz
806250
Google Tensor G2 Google Tensor G2
8C 8T @ 2.85 GHz
789419
Apple A12Z Bionic Apple A12Z Bionic
8C 8T @ 2.49 GHz
779044
Apple A14 Bionic Apple A14 Bionic
6C 6T @ 3.00 GHz
729968
Qualcomm Snapdragon 870 Qualcomm Snapdragon 870
8C 8T @ 3.20 GHz
727650

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).
MediaTek Dimensity 1000 MediaTek Dimensity 1000
8C 8T @ 2.60 GHz
4.5
MediaTek Dimensity 1000C MediaTek Dimensity 1000C
8C 8T @ 2.00 GHz
4.5
MediaTek Dimensity 1000L MediaTek Dimensity 1000L
8C 8T @ 2.20 GHz
4.5
Google Tensor G2 Google Tensor G2
8C 8T @ 2.85 GHz
4
Qualcomm Snapdragon 732G Qualcomm Snapdragon 732G
8C 8T @ 2.30 GHz
3.6
Qualcomm Snapdragon 730G Qualcomm Snapdragon 730G
8C 8T @ 2.20 GHz
3.6
Qualcomm Snapdragon 730 Qualcomm Snapdragon 730
8C 8T @ 2.20 GHz
3.6

Benchmarks


Description of the processor

The Google Tensor G2 is a smartphone processor developed by Google that is used exclusively in the Google Pixel 7 and Google Pixel 7 Pro from Google. The CPU has 8 CPU cores and uses a hybrid core structure. The special feature is that the Google Tensor G2 does not have one very high-clocked Prime core, but two.

The Prime cores use ARMs Cortex-X1 design and clock at up to 2.85 GHz. They are supplemented by two Cortex-A78s that clock at 2.35 GHz. There are also four additional Cortex-A55 energy-saving cores that only work at 1.8 GHz, but are particularly energy efficient. In mobile devices, this can extend battery life because the larger CPU cores are put into a standby state and are only used when they are needed.

When it comes to AI acceleration, the Google Tensor G2 can rely on the Google Edge TPU with an AI computing power of up to 4 TOPS. The Google Edge TPU accelerates, for example, camera functions, image and video processing. AI acceleration can also help ensure that the CPU cores are required as little as possible.

The Google Tensor G2 uses an ARM Mali-G710 MP7 as the graphics card. With a theoretical GPU computing power of 0.7 TFLOPS, this is quite suitable for playing most smartphone games smoothly.

The Google Tensor G2 supports up to 12 GB of DDR5-5500 memory with a maximum memory bandwidth of up to 53 GB/s. This memory bandwidth is pretty good for a smartphone and is on par with many notebooks.

Google does not directly specify the TDP of the Google Tensor G2, so based on the energy consumption and clock frequencies we estimate the TDP to be 10 watts. This puts it in an area in which many modern smartphone processors work.



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