Google Tensor G2 | Apple A9X | |
CPU comparisonGoogle Tensor G2 or Apple A9X - 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 Apple A9X has 2 cores with 2 threads and clocks with a maximum frequency of 2.26 GHz. The CPU supports up to 4 GB of memory in 2 memory channels. The Apple A9X was released in Q3/2015. |
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Google Tensor (3) | Family | Apple A series (22) |
Google Tensor G2 (1) | CPU group | Apple A9/A9X (2) |
2 | Generation | 9 |
G2 | Architecture | A9 |
Mobile | Segment | Mobile |
Google Tensor | Predecessor | Apple A8X |
-- | Successor | Apple A10X Fusion |
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CPU Cores and Base FrequencyThe 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 Apple A9X has 2 CPU cores and 2 threads can calculate simultaneously. The clock frequency of the Apple A9X is at 2.26 GHz. |
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Google Tensor G2 | Characteristic | Apple A9X |
8 | Cores | 2 |
8 | Threads | 2 |
hybrid (Prime / big.LITTLE) | Core architecture | normal |
No | Hyperthreading | No |
No | Overclocking ? | No |
2.85 GHz 2x Cortex-X1 |
A-Core | 2.26 GHz 2x Twister |
2.35 GHz 2x Cortex-A78 |
B-Core | -- |
1.80 GHz 4x Cortex-A55 |
C-Core | -- |
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 G2 | Characteristic | Apple A9X |
Google Tensor AI | AI hardware | -- |
Google Edge TPU @ 4 TOPS | AI specifications | -- |
Internal GraphicsThe Google Tensor G2 or Apple A9X 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-G710 MP7 | GPU | Apple A9X |
0.90 GHz | GPU frequency | 0.65 GHz |
-- | GPU (Turbo) | -- |
Vallhall 3 | GPU Generation | 6 |
4 nm | Technology | 16 nm |
1 | Max. displays | 1 |
7 | Compute units | 48 |
-- | Shader | 384 |
No | Hardware Raytracing | No |
No | Frame Generation | No |
-- | Max. GPU Memory | 4 GB |
12 | DirectX Version | -- |
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-G710 MP7 | GPU | Apple A9X |
Decode / Encode | Codec h265 / HEVC (8 bit) | No |
Decode / Encode | Codec h265 / HEVC (10 bit) | No |
Decode / Encode | Codec h264 | Decode / Encode |
Decode / Encode | Codec VP9 | No |
Decode / Encode | Codec VP8 | Decode |
Decode | Codec AV1 | No |
Decode / Encode | Codec AVC | Decode |
Decode / Encode | Codec VC-1 | Decode |
Decode / Encode | Codec JPEG | Decode / Encode |
Memory & PCIeThe 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 Apple A9X supports up to 4 GB of memory in 2 memory channels and achieves a memory bandwidth of up to 51.2 GB/s. |
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Google Tensor G2 | Characteristic | Apple A9X |
LPDDR5-5500 | Memory | LPDDR4-3200 |
12 GB | Max. Memory | 4 GB |
2 (Dual Channel) | Memory channels | 2 (Dual Channel) |
53.0 GB/s | Max. Bandwidth | 51.2 GB/s |
No | ECC | No |
8.00 MB | L2 Cache | 3.00 MB |
4.00 MB | L3 Cache | 4.00 MB |
-- | PCIe version | -- |
-- | PCIe lanes | -- |
-- | PCIe Bandwidth | -- |
Thermal ManagementThe thermal design power (TDP for short) of the Google Tensor G2 is 10 W, while the Apple A9X has a TDP of 8 W. The TDP specifies the necessary cooling solution that is required to cool the processor sufficiently. |
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Google Tensor G2 | Characteristic | Apple A9X |
10 W | TDP (PL1 / PBP) | 8 W |
-- | TDP (PL2) | -- |
-- | TDP up | -- |
-- | TDP down | -- |
-- | Tjunction max. | -- |
Technical detailsThe Google Tensor G2 is manufactured in 4 nm and has 12.00 MB cache. The Apple A9X is manufactured in 16 nm and has a 7.00 MB cache. |
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Google Tensor G2 | Characteristic | Apple A9X |
4 nm | Technology | 16 nm |
Chiplet | Chip design | Chiplet |
Armv8-A (64 bit) | Instruction set (ISA) | Armv8-A (64 bit) |
-- | ISA extensions | -- |
-- | Socket | -- |
None | Virtualization | None |
No | AES-NI | No |
Android | Operating systems | iOS |
Q4/2022 | Release date | Q3/2015 |
-- | Release price | -- |
show more data | show more data | |
Google Tensor G2
8C 8T @ 2.85 GHz |
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Apple A9X
2C 2T @ 2.26 GHz |
Google Tensor G2
8C 8T @ 2.85 GHz |
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Apple A9X
2C 2T @ 2.26 GHz |
Google Tensor G2
8C 8T @ 2.85 GHz |
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Apple A9X
2C 2T @ 2.26 GHz |
Google Tensor G2
8C 8T @ 2.85 GHz |
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Apple A9X
2C 2T @ 2.26 GHz |
Google Tensor G2
ARM Mali-G710 MP7 @ 0.90 GHz |
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Apple A9X
Apple A9X @ 0.65 GHz |
Google Tensor G2
8C 8T @ 2.85 GHz |
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Apple A9X
2C 2T @ 2.26 GHz |
Google Tensor G2
8C 8T @ 2.85 GHz |
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Apple A9X
2C 2T @ 2.26 GHz |
Google Tensor G2
8C 8T @ 2.85 GHz |
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Apple A9X
2C 2T @ 2.26 GHz |
Google Tensor G2
8C 8T @ 2.85 GHz |
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Apple A9X
2C 2T @ 2.26 GHz |
Devices using this processor |
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Google Tensor G2 | Apple A9X |
Google Pixel 7 Google Pixel 7 Pro |
Apple iPad Pro (1. Gen) |