Nvidia RTX 3500 Ada generation graphic card not recognised by tensorflow?
I think it is not issue with `tf`  but `windows 10`. Please check:

1.  if your system is detecting GPU or not ([How to check GPU in Windows](https://www.microsoft.com/en-us/windows/learning-center/how-to-check-gpu)) if not check this [My RTX 3050 ti is gone and not working](https://answers.microsoft.com/en-us/windows/forum/all/my-rtx-3050-ti-is-gone-and-not-working/3f672229-77c8-4083-b921-03e2e891ca07). 
2. Is `tensorflow` or `jupyter notebook` GPU enabled ([how-to-install-tensorflow-gpu-version-with-jupyter-windows-10-in-8-easy-steps](https://vivek-singh.medium.com/how-to-install-tensorflow-gpu-version-with-jupyter-windows-10-in-8-easy-steps-8797547028a4)) (one change after `tf v2.12` `tensorflow-gpu` & `tensorflow `are same)

Edit:
Similiar issue also reported with linux in #61700, #61673  , might be the case `tf` broken for gpu or check [Tensorflow doesn't seem to see my gpu](https://stackoverflow.com/questions/41402409/tensorflow-doesnt-seem-to-see-my-gpu).
 I did the system check and RTX 3500 can be detected. I found the specifications of the RTX Ada Generation card and the CUDA version seems to be 8.9 (perhaps this is the cuDNN version)? The link is [https://www.techpowerup.com/gpu-specs/rtx-3500-mobile-ada-generation.c4098](url)
So I tried to install CUDA 8.9 and associated cuDNN. The version of python is also downgraded and the GPU card can be detected with the old tensorflow Session function. But because the version of tensorflow is old and I have to debug my current code to get it working. This doesn't make any sense as this graphic card should be used with the latest library. Does anyone have any idea how should the environment be correctly configured? Hi @YiDuan-useismic ,

For native Windows TF2.10v is the last supported version for GPU support.Please refer the attached [source](https://www.tensorflow.org/install/pip#windows-native:~:text=Caution%3A%20TensorFlow%202.10%20was%20the%20last%20TensorFlow%20release%20that%20supported%20GPU%20on%20native%2DWindows.%20Starting%20with%20TensorFlow%202.11%2C%20you%20will%20need%20to%20install%20TensorFlow%20in%20WSL2%2C%20or%20install%20tensorflow%20or%20tensorflow%2Dcpu%20and%2C%20optionally%2C%20try%20the%20TensorFlow%2DDirectML%2DPlugin) here.

For TF versions >=2.11 v you need to install WSL2 on windows. For enabling GPU support with WSL2 please refer the instructions [here](https://www.tensorflow.org/install/pip#step-by-step_instructions).

Thanks! > Hi @YiDuan-useismic ,
> 
> For native Windows TF2.10v is the last supported version for GPU support.Please refer the attached [source](https://www.tensorflow.org/install/pip#windows-native:~:text=Caution%3A%20TensorFlow%202.10%20was%20the%20last%20TensorFlow%20release%20that%20supported%20GPU%20on%20native%2DWindows.%20Starting%20with%20TensorFlow%202.11%2C%20you%20will%20need%20to%20install%20TensorFlow%20in%20WSL2%2C%20or%20install%20tensorflow%20or%20tensorflow%2Dcpu%20and%2C%20optionally%2C%20try%20the%20TensorFlow%2DDirectML%2DPlugin) here.
> 
> For TF versions >=2.11 v you need to install WSL2 on windows. For enabling GPU support with WSL2 please refer the instructions [here](https://www.tensorflow.org/install/pip#step-by-step_instructions).
> 
> Thanks!

Thanks @SuryanarayanaY I will follow the instruction to install the Tensorflow with WSL2. Are you satisfied with the resolution of your issue?
<a href="https://docs.google.com/forms/d/e/1FAIpQLSfaP12TRhd9xSxjXZjcZFNXPGk4kc1-qMdv3gc6bEP90vY1ew/viewform?entry.85265664=Yes&entry.2137816233=https://github.com/tensorflow/tensorflow/issues/61691">Yes</a>
<a href="https://docs.google.com/forms/d/e/1FAIpQLSfaP12TRhd9xSxjXZjcZFNXPGk4kc1-qMdv3gc6bEP90vY1ew/viewform?entry.85265664=No&entry.2137816233=https://github.com/tensorflow/tensorflow/issues/61691">No</a>

### Issue type

Build/Install

### Have you reproduced the bug with TensorFlow Nightly?

Yes

### Source

source

### TensorFlow version

tf 2.13.0

### Custom code

Yes

### OS platform and distribution

Windows 10

### Mobile device

_No response_

### Python version

3.11.4

### Bazel version

_No response_

### GCC/compiler version

_No response_

### CUDA/cuDNN version

v11

### GPU model and memory

RTX 3500 Ada generation mobile 12GB

### Current behavior?

The RTX 3500 card cannot be recognised by tensorflow. I ran tf.config.list_physical_devices('GPU') and tf.test.is_gpu_available(). The results returned "0 GPUs available" and "False".

The microsoft visual studio 2017 is also installed.

### Standalone code to reproduce the issue

```shell
import tensorflow as tf

print("Num GPUs Available: ", len(tf.config.list_physical_devices('GPU')))

tf.test.is_gpu_available()
```


### Relevant log output

_No response_