Google Tensor G2
Apple A16 Bionic
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Google Tensor G2 vs Apple A16 Bionic. Specifications, performance, tests

Overall score
star star star star star
Released
Q4/2022
Google Tensor G2
Google Tensor G2
Released
Q3/2022
Overall score
star star star star star
Apple A16 Bionic
Apple A16 Bionic

What's the best choice Google Tensor G2 or Apple A16 Bionic? Which processor is faster?

We have prepared a comparison to help you choose the best processor. Compare their specifications and benchmarks.

Google Tensor G2 has a maximum frequency of 2.85 GHz. 8 / 8 Cores. Power consumption of 10 W. Released in Q4/2022.

Apple A16 Bionic has a maximum frequency of 3.46 GHz. 6 / 6 Cores. Power consumption of 8.5 W. Released in Q3/2022.

Differences

Google Tensor G2 Reasons to consider
Google Tensor G2
Report a bug
  • Place in the overall ranking

    (based on several benchmarks)

    1036 left arrow score
  • More number of cores

    2 times more cores

    8 left arrow 6

Positions in all rankings

Common positions Google Tensor G2 CPU in popular benchmarks, for comparison with other models.

  • Geekbench 5, 64bit (Single-Core)
    475 place
  • Geekbench 5, 64bit (Multi-Core)
    750 place
  • iGPU - FP32 Performance (Single-precision GFLOPS)
    503 place
Apple A16 Bionic Reasons to consider
Apple A16 Bionic
Report a bug
  • Place in the overall ranking

    (based on several benchmarks)

    162 left arrow score
  • Higher clock speed

    Around 18% better clock speed

    3.46 GHz left arrow 2.85 GHz
  • Performance per watt

    About 0.85 times less performance per watt

    8.5 W left arrow 10 W

Positions in all rankings

Common positions Apple A16 Bionic CPU in popular benchmarks, for comparison with other models.

  • Geekbench 5, 64bit (Single-Core)
    62 place
  • Geekbench 5, 64bit (Multi-Core)
    495 place
  • iGPU - FP32 Performance (Single-precision GFLOPS)
    107 place
  • AnTuTu 9 Benchmark
    5 place
  • Geekbench 6 (Single-Core)
    49 place

Specifications

Technical data
Google Tensor G2 Google Tensor G2
Apple A16 Bionic Apple A16 Bionic
CPU family and group

Background information about the processors being compared, series, generation and market segment.

  • Family
    Google Tensor left arrow Apple A series
  • CPU group
    Google Tensor G2 left arrow Apple A16
  • Segment
    Mobile left arrow Mobile
  • Generation
    2 left arrow 16
  • Predecessor
    Google Tensor left arrow Apple A15 Bionic (5-GPU)
CPU Technical specs

Basic parameters such as number of cores, number of threads, base and turbo frequency, and cache size. These parameters indirectly tell about the speed of the processor, the higher they are the better.

  • CPU Cores / Threads
    8 / 8 left arrow 6 / 6
  • Core architecture
    hybrid (Prime / big.LITTLE) left arrow hybrid (big.LITTLE)
  • A-Core
    2x Cortex-X1 left arrow 2x Everest
  • B-Core
    2x Cortex-A78 left arrow 4x Sawtooth
  • Hyperthreading / SMT
    No left arrow No
  • Overclocking
    No left arrow No
  • A-Core Frequency
    2.85 GHz left arrow 3.46 GHz
  • B-Core Frequency
    2.35 GHz left arrow 2.02 GHz
IGPU

Internal Graphics does not affect the performance of the CPU, performs the work of the graphics card in its absence or on mobile devices.

  • GPU name
    ARM Mali-G710 MP7 left arrow Apple A16 (5 GPU Cores)
  • GPU frequency
    0.90 GHz left arrow 0.70 GHz
  • GPU (Turbo)
    No turbo left arrow No turbo
  • Execution units
    7 left arrow 160
  • Shader
    0 left arrow 1280
  • Max. GPU Memory
    -- left arrow 8 GB
  • Max. displays
    1 left arrow 3
  • Generation
    Vallhall 3 left arrow 13
  • Direct X
    12 left arrow --
  • Technology
    4 nm left arrow 4 nm
  • Release date
    Q2/2021 left arrow Q3/2022
Hardware codec support

Built-in codecs used to encode and decode content. Significantly speeds up the required operations.

  • h265 / HEVC (8 bit)
    Decode / Encode left arrow Decode / Encode
  • h265 / HEVC (10 bit)
    Decode / Encode left arrow Decode / Encode
  • h264
    Decode / Encode left arrow Decode / Encode
  • VP8
    Decode / Encode left arrow Decode / Encode
  • VP9
    Decode / Encode left arrow Decode / Encode
  • AV1
    Decode left arrow No
  • AVC
    Decode / Encode left arrow Decode
  • VC-1
    Decode / Encode left arrow Decode
  • JPEG
    Decode / Encode left arrow Decode / Encode
Memory specs & PCI

Types, channel quantity of RAM supported by Apple A16 Bionic and Google Tensor G2. Depending on the motherboards, higher or lower memory frequencies may be supported.

  • Memory type
    LPDDR5-5500 left arrow LPDDR5-6400
  • Max. Memory
    12 GB left arrow 6 GB
  • Memory channels
    2 (Dual Channel) left arrow 1 (Single Channel)
  • Bandwidth
    53.0 GB/s left arrow 51.2 GB/s
  • ECC
    No left arrow No
  • AES-NI
    No left arrow No
Thermal Management

Compare the TDP requirements of TDP Google Tensor G2 and Apple A16 Bionic to select a cooling system. Note, the TDP value refers to thermal watts, not electrical watts.

  • TDP (PL1)
    10 W left arrow 8.5 W
Technologies and extensions

Architecture, interfaces, additional instructions supported by Google Tensor G2 and Google Tensor G2, virtual machine technologies and process technology.

  • Technology
    4 nm left arrow 4 nm
  • Chip design
    Chiplet left arrow Chiplet
  • Socket
    N/A left arrow N/A
  • L2-Cache
    8.00 MB left arrow 20.00 MB
  • L3-Cache
    4.00 MB left arrow 24.00 MB
  • Architecture
    G2 left arrow A16
  • Operating systems
    Android left arrow iOS
  • Virtualization
    None left arrow None
  • Instruction set (ISA)
    ARMv8-A64 (64 bit) left arrow ARMv8-A64 (64 bit)
  • Release date
    Q4/2022 left arrow Q3/2022

Benchmarks

Performance tests CPUs

Based on the results of several benchmarks, you can more accurately estimate the difference in performance between Google Tensor G2 and Apple A16 Bionic.

Compare the synthetic test values and choose the best processor!

Geekbench 5, 64bit (Single-Core)
Geekbench 5 SC is a popular cross-platform performance test for desktop or mobile processors that uses system memory intensively
1068
Google Tensor G2
1890
Apple A16 Bionic
Geekbench 5, 64bit (Multi-Core)
Geekbench 5 MC is a popular cross-platform performance test for desktop or mobile processors that uses system memory intensively
3149
Google Tensor G2
5465
Apple A16 Bionic
iGPU - FP32 Performance (Single-precision GFLOPS)
The performance of the iGPU - the internal GPU in games
700
Google Tensor G2
2000
Apple A16 Bionic

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