Does GTX 1650 with Max-Q-Design (D4 GB GDDR5)or MX150 supports cuda for deep learing?

AI & Data Science Deep Learning (Training & Inference) Frameworks (archived)
1

I wanted to buy a loptop for Leep Learning applications. So,wanted to know about the gpu with cuda enabled capabilities. And won’t want to go for gmaing laptops as they are bulky and heavy.
I am palnninf to buy laptop with GTX 1650 with Max-Q-Design (D4 GB GDDR5)or MX150 gpu’s.
So, does these gpu’s support cuda?

2

I’m using a razer stealth with MX150 gpu. It works just fine.

Below is the output from nvidia-smi on my laptop:

+-----------------------------------------------------------------------------+
| NVIDIA-SMI 430.50       Driver Version: 430.50       CUDA Version: 10.1     |
|-------------------------------+----------------------+----------------------+
| GPU  Name        Persistence-M| Bus-Id        Disp.A | Volatile Uncorr. ECC |
| Fan  Temp  Perf  Pwr:Usage/Cap|         Memory-Usage | GPU-Util  Compute M. |
|===============================+======================+======================|
|   0  GeForce MX150       Off  | 00000000:02:00.0 Off |                  N/A |
| N/A   48C    P0    N/A /  N/A |   1168MiB /  4042MiB |      5%      Default |
+-------------------------------+----------------------+----------------------+
3

Any GPU with compute capability >= 3.5 will support TensorFlow. Both MX160 and GTX 1650 are OK. However, you may be limited in what networks you can run by the relatively small amount of GPU memory available on laptop GPUs. The required amount of memory depends on the DL networks you are interested in running.