Apple M3 Max (16-CPU 40-GPU) vs Google Tensor

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CPU comparison with benchmarks


Apple M3 Max (16-CPU 40-GPU) CPU1 vs CPU2 Google Tensor
Apple M3 Max (16-CPU 40-GPU) Google Tensor

CPU comparison

In this CPU comparison, we compare the Apple M3 Max (16-CPU 40-GPU) and the Google Tensor and use benchmarks to check which processor is faster.

We compare the Apple M3 Max (16-CPU 40-GPU) 16 core processor released in Q4/2023 with the Google Tensor which has 8 CPU cores and was introduced in Q4/2021.
Apple M series (25) Family Google Tensor (3)
Apple M3 (6) CPU group Google Tensor (1)
3 Generation 1
M3 Architecture G1
Mobile Segment Mobile
Apple M2 Max (30-GPU) Predecessor --
-- Successor Google Tensor G2

CPU Cores and Base Frequency

The Apple M3 Max (16-CPU 40-GPU) is a 16 core processor with a clock frequency of 0.70 GHz (4.06 GHz). The processor can compute 16 threads at the same time. The Google Tensor clocks with 2.80 GHz, has 8 CPU cores and can calculate 8 threads in parallel.

Apple M3 Max (16-CPU 40-GPU) Characteristic Google Tensor
16 Cores 8
16 Threads 8
hybrid (big.LITTLE) Core architecture hybrid (Prime / big.LITTLE)
No Hyperthreading No
No Overclocking ? No
0.70 GHz (4.06 GHz)
12x P-Core
A-Core 2.80 GHz
2x Cortex-X1
0.74 GHz (2.75 GHz)
4x E-Core
B-Core 2.25 GHz
2x Cortex-A76
-- C-Core 1.80 GHz
4x Cortex-A55

Artificial Intelligence and Machine Learning

Processors 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.

Apple M3 Max (16-CPU 40-GPU) Characteristic Google Tensor
Apple Neural Engine AI hardware Google Tensor AI
16 Neural cores @ 35 TOPS AI specifications Google Edge TPU @ 1.6 TOPS

Internal Graphics

Graphics (iGPU) integrated into the processor not only enable image output without having to rely on a dedicated graphics solution, but can also efficiently accelerate video playback.

Apple M3 Max (40 Core) GPU ARM Mali-G78 MP20
0.39 GHz GPU frequency 0.76 GHz
1.40 GHz GPU (Turbo) --
-- GPU Generation Vallhall 2
3 nm Technology 5 nm
5 Max. displays 1
640 Compute units 20
5120 Shader 320
Yes Hardware Raytracing No
No Frame Generation No
128 GB Max. GPU Memory --
-- DirectX Version 12

Hardware codec support

A 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.

Apple M3 Max (40 Core) GPU ARM Mali-G78 MP20
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 Codec VP8 Decode / Encode
Decode Codec AV1 Decode
Decode Codec AVC Decode / Encode
Decode Codec VC-1 Decode / Encode
Decode / Encode Codec JPEG Decode / Encode

Memory & PCIe

Up to 128 GB of memory in a maximum of 4 memory channels is supported by the Apple M3 Max (16-CPU 40-GPU), while the Google Tensor supports a maximum of 12 GB of memory with a maximum memory bandwidth of 53.0 GB/s enabled.

Apple M3 Max (16-CPU 40-GPU) Characteristic Google Tensor
LPDDR5-6400 Memory LPDDR5-5500
128 GB Max. Memory 12 GB
4 (Quad Channel) Memory channels 2 (Dual Channel)
409.6 GB/s Max. Bandwidth 53.0 GB/s
No ECC No
36.00 MB L2 Cache 8.00 MB
-- L3 Cache --
4.0 PCIe version --
-- PCIe lanes --
-- PCIe Bandwidth --

Thermal Management

The Apple M3 Max (16-CPU 40-GPU) has a TDP of 57 W. The TDP of the Google Tensor is 10 W. System integrators use the TDP of the processor as a guide when dimensioning the cooling solution.

Apple M3 Max (16-CPU 40-GPU) Characteristic Google Tensor
57 W TDP (PL1 / PBP) 10 W
-- TDP (PL2) --
-- TDP up --
-- TDP down --
100 °C Tjunction max. --

Technical details

The Apple M3 Max (16-CPU 40-GPU) has 36.00 MB cache and is manufactured in 3 nm. The cache of Google Tensor is at 8.00 MB. The processor is manufactured in 5 nm.

Apple M3 Max (16-CPU 40-GPU) Characteristic Google Tensor
3 nm Technology 5 nm
Chiplet Chip design Unknown
Armv8-A (64 bit) Instruction set (ISA) Armv8-A (64 bit)
Rosetta 2 x86-Emulation ISA extensions --
-- Socket --
Apple Virtualization Framework Virtualization None
Yes AES-NI No
macOS, iPadOS Operating systems Android
Q4/2023 Release date Q4/2021
-- Release price --
show more data show more data


Rate these processors

Here you can rate the Apple M3 Max (16-CPU 40-GPU) to help other visitors make their purchasing decisions. The average rating is 4.9 stars (545 ratings). Rate now:
Here you can rate the Google Tensor to help other visitors make their purchasing decisions. The average rating is 4.3 stars (12 ratings). Rate now:


Average performance in benchmarks

⌀ Single core performance in 2 CPU benchmarks
Apple M3 Max (16-CPU 40-GPU) (100%)
Google Tensor (49%)
⌀ Multi core performance in 2 CPU benchmarks
Apple M3 Max (16-CPU 40-GPU) (100%)
Google Tensor (15%)

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.
Apple M3 Max (16-CPU 40-GPU) Apple M3 Max (16-CPU 40-GPU)
16C 16T @ 4.06 GHz
2150 (100%)
Google Tensor Google Tensor
8C 8T @ 2.80 GHz
1043 (49%)

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.
Apple M3 Max (16-CPU 40-GPU) Apple M3 Max (16-CPU 40-GPU)
16C 16T @ 3.60 GHz
22736 (100%)
Google Tensor Google Tensor
8C 8T @ 2.80 GHz
2915 (13%)

Geekbench 6 (Single-Core)

Geekbench 6 is a benchmark for modern computers, notebooks and smartphones. What is new is an optimized utilization of newer CPU architectures, e.g. based on the big.LITTLE concept and combining CPU cores of different sizes. The single-core benchmark only evaluates the performance of the fastest CPU core, the number of CPU cores in a processor is irrelevant here.
Apple M3 Max (16-CPU 40-GPU) Apple M3 Max (16-CPU 40-GPU)
16C 16T @ 4.06 GHz
3125 (100%)
Google Tensor Google Tensor
8C 8T @ 2.80 GHz
1494 (48%)

Geekbench 6 (Multi-Core)

Geekbench 6 is a benchmark for modern computers, notebooks and smartphones. What is new is an optimized utilization of newer CPU architectures, e.g. based on the big.LITTLE concept and combining CPU cores of different sizes. The multi-core benchmark evaluates the performance of all of the processor's CPU cores. Virtual thread improvements such as AMD SMT or Intel's Hyper-Threading have a positive impact on the benchmark result.
Apple M3 Max (16-CPU 40-GPU) Apple M3 Max (16-CPU 40-GPU)
16C 16T @ 3.60 GHz
21045 (100%)
Google Tensor Google Tensor
8C 8T @ 2.80 GHz
3639 (17%)

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.
Apple M3 Max (16-CPU 40-GPU) Apple M3 Max (16-CPU 40-GPU)
Apple M3 Max (40 Core) @ 1.40 GHz
14200 (100%)
Google Tensor Google Tensor
ARM Mali-G78 MP20 @ 0.76 GHz
1943 (14%)

Performance for Artificial Intelligence (AI) and Machine Learning (ML)

Processors 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. The performance is given in the number (trillions) of arithmetic operations per second (TOPS).
Apple M3 Max (16-CPU 40-GPU) Apple M3 Max (16-CPU 40-GPU)
16C 16T @ 0.70 GHz
35 (100%)
Google Tensor Google Tensor
8C 8T @ 2.80 GHz
1.6 (5%)

Cinebench 2024 (Single-Core)

The Cinebench 2024 benchmark is based on the Redshift rendering engine, which is also used in Maxon's 3D program Cinema 4D. The benchmark runs are each 10 minutes long to test whether the processor is limited by its heat generation.
Apple M3 Max (16-CPU 40-GPU) Apple M3 Max (16-CPU 40-GPU)
16C 16T @ 4.06 GHz
141 (100%)
Google Tensor Google Tensor
8C 8T @ 2.80 GHz
0 (0%)

Cinebench 2024 (Multi-Core)

The Multi-Core test of the Cinebench 2024 benchmark uses all cpu cores to render using the Redshift rendering engine, which is also used in Maxons Cinema 4D. The benchmark run is 10 minutes long to test whether the processor is limited by its heat generation.
Apple M3 Max (16-CPU 40-GPU) Apple M3 Max (16-CPU 40-GPU)
16C 16T @ 4.06 GHz
1607 (100%)
Google Tensor Google Tensor
8C 8T @ 2.80 GHz
0 (0%)

Cinebench R23 (Single-Core)

Cinebench R23 is the successor of Cinebench R20 and is also based on the Cinema 4 Suite. Cinema 4 is a worldwide used software to create 3D forms. The single-core test only uses one CPU core, the amount of cores or hyperthreading ability doesn't count.
Apple M3 Max (16-CPU 40-GPU) Apple M3 Max (16-CPU 40-GPU)
16C 16T @ 4.06 GHz
1968 (100%)
Google Tensor Google Tensor
8C 8T @ 2.80 GHz
0 (0%)

Cinebench R23 (Multi-Core)

Cinebench R23 is the successor of Cinebench R20 and is also based on the Cinema 4 Suite. Cinema 4 is a worldwide used software to create 3D forms. The multi-core test involves all CPU cores and taks a big advantage of hyperthreading.
Apple M3 Max (16-CPU 40-GPU) Apple M3 Max (16-CPU 40-GPU)
16C 16T @ 3.60 GHz
24028 (100%)
Google Tensor Google Tensor
8C 8T @ 2.80 GHz
0 (0%)

Cinebench R20 (Single-Core)

Cinebench R20 is the successor of Cinebench R15 and is also based on the Cinema 4 Suite. Cinema 4 is a worldwide used software to create 3D forms. The single-core test only uses one CPU core, the amount of cores or hyperthreading ability doesn't count.
Apple M3 Max (16-CPU 40-GPU) Apple M3 Max (16-CPU 40-GPU)
16C 16T @ 4.06 GHz
496 (100%)
Google Tensor Google Tensor
8C 8T @ 2.80 GHz
0 (0%)

Cinebench R20 (Multi-Core)

Cinebench R20 is the successor of Cinebench R15 and is also based on the Cinema 4 Suite. Cinema 4 is a worldwide used software to create 3D forms. The multi-core test involves all CPU cores and taks a big advantage of hyperthreading.
Apple M3 Max (16-CPU 40-GPU) Apple M3 Max (16-CPU 40-GPU)
16C 16T @ 3.60 GHz
6311 (100%)
Google Tensor Google Tensor
8C 8T @ 2.80 GHz
0 (0%)

AnTuTu 9 Benchmark

The AnTuTu 9 benchmark is very well suited to measuring the performance of a smartphone. AnTuTu 9 is quite heavy on 3D graphics and can now also use the "Metal" graphics interface. In AnTuTu, memory and UX (user experience) are also tested by simulating browser and app usage. AnTuTu version 9 can compare any ARM CPU running on Android or iOS. Devices may not be directly comparable when benchmarked on different operating systems.

In the AnTuTu 9 benchmark, the single-core performance of a processor is only slightly weighted. The rating is made up of the multi-core performance of the processor, the speed of the working memory, and the performance of the internal graphics.
Apple M3 Max (16-CPU 40-GPU) Apple M3 Max (16-CPU 40-GPU)
16C 16T @ 0.70 GHz
0 (0%)
Google Tensor Google Tensor
8C 8T @ 2.80 GHz
691770 (100%)

AnTuTu 8 Benchmark

The AnTuTu 8 Benchmark measures the performance of a SoC. AnTuTu benchmarks the CPU, GPU, Memory as well as the UX (User Experience) by simulating browser and app usage. AnTuTu can benchmark any ARM CPU that runs under Android or iOS. Devices may not be directly compareable if the benchmark has been performed under different operating systems.

In the AnTuTu 8 benchmark, the single-core performance of a processor is only slightly weighted. The evaluation consists of the multi-core performance of the processor, the speed of the RAM and the performance of the internal graphics.
Apple M3 Max (16-CPU 40-GPU) Apple M3 Max (16-CPU 40-GPU)
16C 16T @ 0.70 GHz
0 (0%)
Google Tensor Google Tensor
8C 8T @ 2.80 GHz
612494 (100%)

Cinebench R15 (Single-Core)

Cinebench R15 is the successor of Cinebench 11.5 and is also based on the Cinema 4 Suite. Cinema 4 is a worldwide used software to create 3D forms. The single-core test only uses one CPU core, the amount of cores or hyperthreading ability doesn't count.
Apple M3 Max (16-CPU 40-GPU) Apple M3 Max (16-CPU 40-GPU)
16C 16T @ 4.06 GHz
266 (100%)
Google Tensor Google Tensor
8C 8T @ 2.80 GHz
0 (0%)

Cinebench R15 (Multi-Core)

Cinebench R15 is the successor of Cinebench 11.5 and is also based on the Cinema 4 Suite. Cinema 4 is a worldwide used software to create 3D forms. The multi-core test involves all CPU cores and taks a big advantage of hyperthreading.
Apple M3 Max (16-CPU 40-GPU) Apple M3 Max (16-CPU 40-GPU)
16C 16T @ 3.60 GHz
3375 (100%)
Google Tensor Google Tensor
8C 8T @ 2.80 GHz
0 (0%)

CPU performance per watt (efficiency)

Efficiency of the processor under full load in the Cinebench R23 (multi-core) benchmark. The benchmark result is divided by the average energy required (CPU package power in watts). The higher the value, the more efficient the CPU is under full load.
Apple M3 Max (16-CPU 40-GPU) Apple M3 Max (16-CPU 40-GPU)
24,028 CB R23 MC @ 57 W
422 (100%)
Google Tensor Google Tensor
2.80 GHz
0 (0%)

Devices using this processor

Apple M3 Max (16-CPU 40-GPU) Google Tensor
Apple MacBook Pro 14 (2023)
Apple MacBook Pro 16 (2023)
Google Pixel 6
Google Pixel 6 Pro

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