Apple M2 Max GPU vs Nvidia V100, P100 and T4 | by Fabrice Daniel

Launched in November 2020, Apple M1 was a revolution in the world of computers dominated by Intel. These new M1 Macs showed impressive performance in many benchmarks as M1 was faster than most high-end desktop computers for only a fraction of their energy consumption.

Here are my previous benchmarks for the M1:

Benchmark M1 vs Xeon® vs Core i5 vs K80 and T4

M1 competes with 20 cores Xeon® on TensorFlow training

In January 2023, Apple announced the new M2 Pro and M2 Max. Their specs let us expect good performance increases, especially regarding the GPU.

Compared M2 Max with M1 specs

This M2 Max has 30 GPU cores, so we estimated the 10.7 TFLOPS from the 13.6 TFLOPS of the 38 GPU cores version.

GPU Compared

By comparison, the M2 Max 38 Cores GPU reaches 13.6 TFlops. My test below will show that the TFlops alone cannot be used to estimate the actual performances of these GPUs.

To get comparable results, I run every test with the default TensorFlow FP32 floating point precision.

You can verify this precision by running :


In this article, I benchmark the M2 Max GPU against Nvidia V100, P100, and T4 for MLP, CNN, and LSTM TensorFlow models.

Benchmark setup

On M1 and M2 Max computers, the environment was created under miniforge. Only the following packages were installed:

conda install python=3.10
pip install…

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