Google Tensor G2 vs Samsung Exynos 2400

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CPU comparison with benchmarks


Google Tensor G2 CPU1 vs CPU2 Samsung Exynos 2400
Google Tensor G2 Samsung Exynos 2400

CPU comparison

Google Tensor G2 or Samsung Exynos 2400 - 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 Samsung Exynos 2400 has 10 cores with 10 threads and clocks with a maximum frequency of 3.20 GHz. The CPU supports up to 12 GB of memory in 4 memory channels. The Samsung Exynos 2400 was released in Q4/2023.
Google Tensor (3) Family Samsung Exynos (46)
Google Tensor G2 (1) CPU group Samsung Exynos 2400 (1)
2 Generation 7
G2 Architecture Cortex-X4/-A720/-A520
Mobile Segment Mobile
Google Tensor Predecessor --
-- 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 while the Samsung Exynos 2400 has 10 CPU cores and 10 threads can calculate simultaneously. The clock frequency of the Samsung Exynos 2400 is at 3.20 GHz.

Google Tensor G2 Characteristic Samsung Exynos 2400
8 Cores 10
8 Threads 10
hybrid (Prime / big.LITTLE) Core architecture hybrid (Prime / big.LITTLE)
No Hyperthreading No
No Overclocking ? No
2.85 GHz
2x Cortex-X1
A-Core 3.20 GHz
1x Cortex-X4
2.35 GHz
2x Cortex-A78
B-Core 2.90 GHz
5x Cortex-A720
1.80 GHz
4x Cortex-A55
C-Core 1.95 GHz
4x Cortex-A520

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 Samsung Exynos 2400
Google Tensor AI AI hardware Samsung AI engine
Google Edge TPU @ 4 TOPS AI specifications Samsung AI Accelerator @ 44 TOPS

Internal Graphics

The Google Tensor G2 or Samsung Exynos 2400 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 Samsung Xclipse 940
0.90 GHz GPU frequency 1.40 GHz
-- GPU (Turbo) --
Vallhall 3 GPU Generation --
4 nm Technology 4 nm
1 Max. displays 0
7 Compute units 12
-- Shader 384
No Hardware Raytracing No
No Frame Generation No
-- Max. GPU Memory 4 GB
12 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.

ARM Mali-G710 MP7 GPU Samsung Xclipse 940
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 No
Decode Codec AV1 Decode
Decode / Encode Codec AVC No
Decode / Encode Codec VC-1 No
Decode / Encode Codec JPEG No

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 Samsung Exynos 2400 supports up to 12 GB of memory in 4 memory channels and achieves a memory bandwidth of up to 68.3 GB/s.

Google Tensor G2 Characteristic Samsung Exynos 2400
LPDDR5-5500 Memory LPDDR5X-8533
12 GB Max. Memory 12 GB
2 (Dual Channel) Memory channels 4 (Quad Channel)
53.0 GB/s Max. Bandwidth 68.3 GB/s
No ECC No
8.00 MB L2 Cache --
4.00 MB L3 Cache --
-- PCIe version --
-- PCIe lanes --
-- PCIe Bandwidth --

Thermal Management

The thermal design power (TDP for short) of the Google Tensor G2 is 10 W, while the Samsung Exynos 2400 has a TDP of 12 W. The TDP specifies the necessary cooling solution that is required to cool the processor sufficiently.

Google Tensor G2 Characteristic Samsung Exynos 2400
10 W TDP (PL1 / PBP) 12 W
-- TDP (PL2) --
-- TDP up --
-- TDP down --
-- Tjunction max. --

Technical details

The Google Tensor G2 is manufactured in 4 nm and has 12.00 MB cache. The Samsung Exynos 2400 is manufactured in 4 nm and has a 0.00 MB cache.

Google Tensor G2 Characteristic Samsung Exynos 2400
4 nm Technology 4 nm
Chiplet Chip design Unknown
Armv8-A (64 bit) Instruction set (ISA) Armv9-A (64 bit)
-- ISA extensions --
-- Socket --
None Virtualization None
No AES-NI No
Android Operating systems Android
Q4/2022 Release date Q4/2023
-- 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 4.1 stars (15 ratings). Rate now:
Here you can rate the Samsung Exynos 2400 to help other visitors make their purchasing decisions. The average rating is 4.4 stars (18 ratings). Rate now:


Average performance in benchmarks

⌀ Single core performance in 2 CPU benchmarks
Google Tensor G2 (67%)
Samsung Exynos 2400 (100%)
⌀ Multi core performance in 2 CPU benchmarks
Google Tensor G2 (53%)
Samsung Exynos 2400 (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 (68%)
Samsung Exynos 2400 Samsung Exynos 2400
10C 10T @ 3.20 GHz
1579 (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 (56%)
Samsung Exynos 2400 Samsung Exynos 2400
10C 10T @ 3.20 GHz
5651 (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 (66%)
Samsung Exynos 2400 Samsung Exynos 2400
10C 10T @ 3.20 GHz
2168 (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 (49%)
Samsung Exynos 2400 Samsung Exynos 2400
10C 10T @ 3.20 GHz
6856 (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 (38%)
Samsung Exynos 2400 Samsung Exynos 2400
Samsung Xclipse 940 @ 1.40 GHz
1825 (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 (9%)
Samsung Exynos 2400 Samsung Exynos 2400
10C 10T @ 3.20 GHz
44 (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%)
Samsung Exynos 2400 Samsung Exynos 2400
10C 10T @ 3.20 GHz
0 (0%)

Devices using this processor

Google Tensor G2 Samsung Exynos 2400
Google Pixel 7
Google Pixel 7 Pro
Samsung Galaxy S24
Samsung Galaxy S24 Plus

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