3090 rtx much slower than 2060 rtx

Hello there, how are you guys doing today?

As the title mentions I have quite the problem…

I have a linux laptop: i7 CPU / 2060 rtx GPU / 16gb RAM, running my own keras sequential model around 100 iterations per sec, and it takes around 30 minutes.

Have another windows desktop: i5 CPU / 3090 rtx / 16gb RAM, running same exact code at 40 iterations per sec, and it takes around 1 hour.

They are both running on GPU (rest assured I’m using device context), yet 3090 is so much slower.

I of course tested the CPUs to compare separately, and the i5 is slower than the i7 as expected.

Installation of tensorflow was done in both sides with the pip install guide:

Windows Machine:

1.- Download Microsoft Visual c++ dlls (directly without visual studio)
2.- Install miniconda
3.- Run

conda create --name tf python=3.9

4.- Run

conda install -c conda-forge cudatoolkit=11.2 cudnn=8.1.0


pip install --upgrade pip


pip install tensorflow

Linux Machine: (conda install linux version, works perfectly fine)

Windows runs just fine, and it detects the GPU on tf.config.physical_devices(‘GPU’), but it’s just so slow in comparison to 2060 rtx laptop somehow?

If you guys have any idea why this is happening, or how to fix it, I thank you in advance.

Have a good day!

I have the same problem. May I ask if you have resolved it now?