Google Tensor | Apple A13 Bionic | |
CPU comparisonGoogle Tensor or Apple A13 Bionic - 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 Apple A13 Bionic has 6 cores with 6 threads and clocks with a maximum frequency of 2.65 GHz. The CPU supports up to 4 GB of memory in 1 memory channels. The Apple A13 Bionic was released in Q3/2019. |
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Google Tensor (3) | Family | Apple A series (22) |
Google Tensor (1) | CPU group | Apple A13 (1) |
1 | Generation | 13 |
G1 | Architecture | A13 (Lightning / Thunder) |
Mobile | Segment | Mobile |
-- | Predecessor | Apple A12 Bionic |
Google Tensor G2 | Successor | Apple A14 Bionic |
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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 Apple A13 Bionic has 6 CPU cores and 6 threads can calculate simultaneously. The clock frequency of the Apple A13 Bionic is at 2.65 GHz. |
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Google Tensor | Characteristic | Apple A13 Bionic |
8 | Cores | 6 |
8 | Threads | 6 |
hybrid (Prime / big.LITTLE) | Core architecture | hybrid (big.LITTLE) |
No | Hyperthreading | No |
No | Overclocking ? | No |
2.80 GHz 2x Cortex-X1 |
A-Core | 2.65 GHz 2x Lightning |
2.25 GHz 2x Cortex-A76 |
B-Core | 1.80 GHz 4x Thunder |
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 | Characteristic | Apple A13 Bionic |
Google Tensor AI | AI hardware | Apple Neural Engine |
Google Edge TPU @ 1.6 TOPS | AI specifications | 8 Neural cores @ 6 TOPS |
Internal GraphicsThe Google Tensor or Apple A13 Bionic 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 | Apple A13 |
0.76 GHz | GPU frequency | 1.35 GHz |
-- | GPU (Turbo) | -- |
Vallhall 2 | GPU Generation | 10 |
5 nm | Technology | 7 nm |
1 | Max. displays | 1 |
20 | Compute units | 16 |
320 | Shader | 256 |
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-G78 MP20 | GPU | Apple A13 |
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 | Decode / Encode |
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 can use up to 12 GB of memory in 2 memory channels. The maximum memory bandwidth is 53.0 GB/s. The Apple A13 Bionic supports up to 4 GB of memory in 1 memory channels and achieves a memory bandwidth of up to 34.1 GB/s. |
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Google Tensor | Characteristic | Apple A13 Bionic |
LPDDR5-5500 | Memory | LPDDR4X-4266 |
12 GB | Max. Memory | 4 GB |
2 (Dual Channel) | Memory channels | 1 (Single Channel) |
53.0 GB/s | Max. Bandwidth | 34.1 GB/s |
No | ECC | No |
8.00 MB | L2 Cache | 8.00 MB |
-- | 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 Apple A13 Bionic has a TDP of 6 W. The TDP specifies the necessary cooling solution that is required to cool the processor sufficiently. |
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Google Tensor | Characteristic | Apple A13 Bionic |
10 W | TDP (PL1 / PBP) | 6 W |
-- | TDP (PL2) | -- |
-- | TDP up | -- |
-- | TDP down | -- |
-- | Tjunction max. | -- |
Technical detailsThe Google Tensor is manufactured in 5 nm and has 8.00 MB cache. The Apple A13 Bionic is manufactured in 7 nm and has a 8.00 MB cache. |
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Google Tensor | Characteristic | Apple A13 Bionic |
5 nm | Technology | 7 nm |
Unknown | 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 |
Q4/2021 | Release date | Q3/2019 |
-- | Release price | -- |
show more data | show more data | |
Google Tensor
8C 8T @ 2.80 GHz |
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Apple A13 Bionic
6C 6T @ 2.65 GHz |
Google Tensor
8C 8T @ 2.80 GHz |
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Apple A13 Bionic
6C 6T @ 2.65 GHz |
Google Tensor
8C 8T @ 2.80 GHz |
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Apple A13 Bionic
6C 6T @ 2.65 GHz |
Google Tensor
8C 8T @ 2.80 GHz |
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Apple A13 Bionic
6C 6T @ 2.65 GHz |
Google Tensor
ARM Mali-G78 MP20 @ 0.76 GHz |
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Apple A13 Bionic
Apple A13 @ 1.35 GHz |
Google Tensor
8C 8T @ 2.80 GHz |
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Apple A13 Bionic
6C 6T @ 2.65 GHz |
Google Tensor
8C 8T @ 2.80 GHz |
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Apple A13 Bionic
6C 6T @ 2.65 GHz |
Google Tensor
8C 8T @ 2.80 GHz |
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Apple A13 Bionic
6C 6T @ 2.65 GHz |
Google Tensor
8C 8T @ 2.80 GHz |
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Apple A13 Bionic
6C 6T @ 2.65 GHz |
Devices using this processor |
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Google Tensor | Apple A13 Bionic |
Google Pixel 6 Google Pixel 6 Pro |
Apple iPhone 11 Apple iPhone 11 Pro Apple iPhone 11 Pro Max iPhone SE |