Running local models on AMD hardware is great—when PyTorch actually sees the GPU. I wasted days trying to figure out why torch.cuda.is_available() kept returning False.

I wrote a detailed guide covering:

· ROCm install

· PyTorch ROCm wheel

· Environment variables

· Verification steps

· Common errors

If you’re on RDNA2 or RDNA3 and stuck, this should save you time:

https://interconnectd.com/blog/305/fix-pytorch-cuda-not-available-on-amd-gpus-complete-rocm-setup-guide/

What’s your setup, and what’s the exact error?

AMD has always been the budget brand. Cheaper isn’t always better 😏😏

This is a no brainer now. Nvidia has DLSS 5. AMD has no answer and the hack to enable DLSS 5 makes it 80% slower. Nvidia wins!

Looks like Intel Nova Lake Desktop and Mobile will both support DDR5 8000MTs as official speed.

Nova Lake Mobile 8000MTs CSO-DIMM

Nova Lake Desktop 8000MTs CU-DIMM

Another one bites the dust

This user, like many AMD owners, sits around for months miserable, troubleshooting instead of gaming. Tinkering instead of casting spells... it is an old story. So simple to just buy Intel and have a great gaming experience. I don't want to troubleshoot and RMA all the time.

Not very good. Much lower than my 5080.

What an absolute shitshow! Just look at the threads on that subreddit. Crashes, black screens, BSOD and driver timeouts going back years with multiple posts every single day.

Seriously it’s pretty darn bad when Reddit has more reports of AMD cards crashing when they don’t even have majority of market share. It just goes to show that you can’t trust AMD to deliver a product and offer support.

https://www.reddit.com/r/AMDHelp/s/TUHgiXROYS

This person went all AMD... Apparently a big mistake.

Only $500 for an old buster 3rd gen 3060!