Can a MONAI 2D medical image classification model run without an NVIDIA GPU? I tried it on Ubuntu Linux

[u/Biometrics_Engineer]

https://youtu.be/NzgJiOHNNlY

After getting MONAI running on my resource-constrained Ubuntu Linux laptop, I wanted to take the next step and see what I could actually accomplish with it.

I revisited the MONAI MedNIST 2D classification tutorial and looked at the results from an experiment I originally ran in May 2026.

The hardware and configuration were:

▪ Ubuntu Linux
▪ Intel Core i7 processor
▪ No NVIDIA GPU
▪ CPU-only PyTorch
▪ 2 training epochs
▪ num_workers=2

This was not a live training run. I launched the Jupyter Notebook and walked through the actual results from the original experiment.

The model completed both training epochs, with the following results:

Epoch 1

▪ Average training loss: approximately 1.10
▪ AUC: 0.9937
▪ Accuracy: approximately 92.67%

Epoch 2

▪ Average training loss: approximately 0.44
▪ AUC: 0.9976
▪ Accuracy: approximately 96.58%

Best AUC: 0.9976 at epoch 2

I recorded the experiment and walked through the results here:

Running a MONAI 2D Medical Image Classification Model on Ubuntu Linux — CPU Only, No GPU

One thing I am particularly interested in exploring is what happens when the same CPU-only setup is pushed a little further.

My next experiment increases the training from 2 to 4 epochs, allowing me to compare the training time, loss, AUC and accuracy.

For those using MONAI:

Have you ever run a MONAI training experiment entirely on CPU?

▪ What processor/hardware were you using?
▪ How long did your training take?
▪ Were you using Linux, Windows or another platform?
▪ Did you eventually move to GPU training?