Google Tensor | Samsung Exynos 2200 | |
CPU comparisonGoogle Tensor or Samsung Exynos 2200 - 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 has 8 cores with 8 threads and clocks with a maximum frequency of 2.80 GHz. Up to 12 GB of memory is supported in 2 memory channels. The Google Tensor was released in Q4/2021. The Samsung Exynos 2200 has 8 cores with 8 threads and clocks with a maximum frequency of 2.80 GHz. The CPU supports up to 12 GB of memory in 4 memory channels. The Samsung Exynos 2200 was released in Q1/2022. |
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Google Tensor (3) | Family | Samsung Exynos (46) |
Google Tensor (1) | CPU group | Samsung Exynos 2200 (1) |
1 | Generation | 6 |
G1 | Architecture | Cortex-X2/-A710/-A510 |
Mobile | Segment | Mobile |
-- | Predecessor | Samsung Exynos 2100 |
Google Tensor G2 | Successor | -- |
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CPU Cores and Base FrequencyThe Google Tensor has 8 CPU cores and can calculate 8 threads in parallel. The clock frequency of the Google Tensor is 2.80 GHz while the Samsung Exynos 2200 has 8 CPU cores and 8 threads can calculate simultaneously. The clock frequency of the Samsung Exynos 2200 is at 2.80 GHz. |
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Google Tensor | Characteristic | Samsung Exynos 2200 |
8 | Cores | 8 |
8 | Threads | 8 |
hybrid (Prime / big.LITTLE) | Core architecture | hybrid (Prime / big.LITTLE) |
No | Hyperthreading | No |
No | Overclocking ? | No |
2.80 GHz 2x Cortex-X1 |
A-Core | 2.80 GHz 1x Cortex-X2 |
2.25 GHz 2x Cortex-A76 |
B-Core | 2.52 GHz 3x Cortex-A710 |
1.80 GHz 4x Cortex-A55 |
C-Core | 1.82 GHz 4x Cortex-A510 |
Artificial Intelligence and Machine LearningProcessors 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. |
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Google Tensor | Characteristic | Samsung Exynos 2200 |
Google Tensor AI | AI hardware | -- |
Google Edge TPU @ 1.6 TOPS | AI specifications | -- |
Internal GraphicsThe Google Tensor or Samsung Exynos 2200 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. |
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ARM Mali-G78 MP20 | GPU | Samsung Xclipse 920 |
0.76 GHz | GPU frequency | 1.30 GHz |
-- | GPU (Turbo) | 1.30 GHz |
Vallhall 2 | GPU Generation | 1 |
5 nm | Technology | 4 nm |
1 | Max. displays | 0 |
20 | Compute units | 24 |
320 | Shader | 384 |
No | Hardware Raytracing | No |
No | Frame Generation | No |
-- | Max. GPU Memory | 4 GB |
12 | DirectX Version | 12 |
Hardware codec supportA 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. |
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ARM Mali-G78 MP20 | GPU | Samsung Xclipse 920 |
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 & PCIeThe Google Tensor can use up to 12 GB of memory in 2 memory channels. The maximum memory bandwidth is 53.0 GB/s. The Samsung Exynos 2200 supports up to 12 GB of memory in 4 memory channels and achieves a memory bandwidth of up to 51.2 GB/s. |
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Google Tensor | Characteristic | Samsung Exynos 2200 |
LPDDR5-5500 | Memory | LPDDR5-6400 |
12 GB | Max. Memory | 12 GB |
2 (Dual Channel) | Memory channels | 4 (Quad Channel) |
53.0 GB/s | Max. Bandwidth | 51.2 GB/s |
No | ECC | No |
8.00 MB | L2 Cache | -- |
-- | L3 Cache | -- |
-- | PCIe version | -- |
-- | PCIe lanes | -- |
-- | PCIe Bandwidth | -- |
Thermal ManagementThe thermal design power (TDP for short) of the Google Tensor is 10 W, while the Samsung Exynos 2200 has a TDP of --. The TDP specifies the necessary cooling solution that is required to cool the processor sufficiently. |
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Google Tensor | Characteristic | Samsung Exynos 2200 |
10 W | TDP (PL1 / PBP) | -- |
-- | TDP (PL2) | -- |
-- | TDP up | -- |
-- | TDP down | -- |
-- | Tjunction max. | -- |
Technical detailsThe Google Tensor is manufactured in 5 nm and has 8.00 MB cache. The Samsung Exynos 2200 is manufactured in 4 nm and has a 0.00 MB cache. |
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Google Tensor | Characteristic | Samsung Exynos 2200 |
5 nm | Technology | 4 nm |
Unknown | 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 |
Q4/2021 | Release date | Q1/2022 |
-- | Release price | -- |
show more data | show more data | |
Google Tensor
8C 8T @ 2.80 GHz |
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Samsung Exynos 2200
8C 8T @ 2.80 GHz |
Google Tensor
8C 8T @ 2.80 GHz |
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Samsung Exynos 2200
8C 8T @ 2.80 GHz |
Google Tensor
8C 8T @ 2.80 GHz |
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Samsung Exynos 2200
8C 8T @ 2.80 GHz |
Google Tensor
8C 8T @ 2.80 GHz |
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Samsung Exynos 2200
8C 8T @ 2.80 GHz |
Google Tensor
ARM Mali-G78 MP20 @ 0.76 GHz |
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Samsung Exynos 2200
Samsung Xclipse 920 @ 1.30 GHz |
Google Tensor
8C 8T @ 2.80 GHz |
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Samsung Exynos 2200
8C 8T @ 2.80 GHz |
Google Tensor
8C 8T @ 2.80 GHz |
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Samsung Exynos 2200
8C 8T @ 2.80 GHz |
Google Tensor
8C 8T @ 2.80 GHz |
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Samsung Exynos 2200
8C 8T @ 2.80 GHz |
Devices using this processor |
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Google Tensor | Samsung Exynos 2200 |
Google Pixel 6 Google Pixel 6 Pro |
Samsung Galaxy S22 Samsung Galaxy S22 Plus Samsung Galaxy S22 Ultra |