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Google Tensor vs. Apple A15 Bionic (4-GPU)


Cpu Benchmark with benchmarks

Google Tensor
Apple A15 Bionic (4-GPU)
Google Tensor Apple A15 Bionic (4-GPU)
1.80 GHz (2.80 GHz) Frequency 3.23 GHz
1.80 GHz (2.80 GHz) Turbo (1 Core) 3.23 GHz
-- Turbo (All Cores) 2.02 GHz
8 Cores 6
No Hyperthreading ? No
No Overclocking ? No
hybrid (Prime / big.LITTLE) Core architecture hybrid (big.LITTLE)
ARM Mali-G78 MP20 GPU Apple A15 (4 GPU Cores)
12 DirectX Version
1 Max. displays 3
LPDDR5-5500 Memory LPDDR4X-4266
2 Memory channels 1
12 GB Max. Memory 6 GB
No ECC No
8.00 MB L2 Cache 16.00 MB
-- L3 Cache 32.00 MB
PCIe version
PCIe lanes
5 nm Technology 5 nm
N/A Socket N/A
10 W TDP 8.5 W
None Virtualization None
Q4/2021 Release date Q3/2021
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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 1043 (47%)
47% Complete
78% Complete

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 2915 (6%)
6% Complete
10% Complete

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 1943 (9%)
9% Complete
6% Complete

Geekbench 3, 64bit (Single-Core)

Geekbench 3 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 4564 (66%)
66% Complete
0% Complete

Geekbench 3, 64bit (Multi-Core)

Geekbench 3 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 12594 (13%)
13% Complete
0% Complete
Google Tensor vs. Apple A15 Bionic (4-GPU) - Cpu Benchmark Specs & Test
4.0 of 42 rating(s)
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