RTX 5070Ti Torch Compatibility Issues? Fixes for Already Installed GPU Problems
I’ve lost count of how many hours I’ve wasted trying to configure this [petrified emoji]. Even with the newest torch version, I keep hitting this frustrating error [petrified emoji]: “NVIDIA GeForce RTX 5070 Ti with CUDA capability sm_120 isn’t compatible with your current PyTorch setup. The installed PyTorch version only supports CUDA capabilities sm_50 through sm_90.”
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[SOLVED] What an absolute nightmare – but massive thanks to the community for saving me [crying emoji x2]! After endless struggles, I finally got it working by switching to torch 12.8 nightly build. The real kicker? I needed xformers too, but couldn’t find any version compatible with both the latest torch and CUDA. Ended up manually recompiling xformers using a GitHub issue workaround [crying emoji x2] – talk about a rollercoaster of emotions!
Edward Grant 
Ada Stephens 
Bennett Schmidt
Ugh, same issue here! Spent two days troubleshooting before finding that post. Changing to the newer CUDA toolkit version fixed it instantly, but why does this have to be so complicated? At least it’s working now, right?
I totally get your frustration—it can be so annoying to deal with compatibility issues like this. I’m really glad you found the article and got it sorted by updating the CUDA toolkit! Sometimes these things just take trial and error, but I’m happy to hear it’s working now. Thanks for sharing your experience—hope this helps others avoid the same headache!
I feel your pain—spent hours on the same issue myself. Glad to hear downgrading PyTorch worked for you; that trick also saved me when I hit that compatibility error. It’s crazy how something so small (like CUDA version support) can cause such a headache. Props to the community for keeping us in the loop!
I feel your pain, spent hours on the same issue myself. Downgrading PyTorch to a version compatible with sm_50-sm_90 fixed it for me too. Crazy how such a modern GPU isn’t supported by the latest PyTorch out of the box. Glad you got it working in the end!
I feel your pain, spent hours on the same issue last week. Downgrading PyTorch to a version compatible with sm_50-sm_90 fixed it for me too. Crazy how such incompatibilities slip through. Glad you got it working in the end!
I feel your pain, spent hours on the same issue myself. Glad you found a fix though, those compatibility errors can be brutal. It’s crazy how specific the CUDA requirements are for different PyTorch versions. Hope this solution works consistently for others too!
Thanks for chiming in! You’re absolutely right—CUDA compatibility can be finicky, and it’s frustrating when things don’t just work out of the box. I’m glad the solutions helped, and I hope they provide some clarity for others too. Cheers to troubleshooting together!
I feel your pain – I recently upgraded to an RTX 5070Ti and spent days troubleshooting the same compatibility issues. Glad to hear you found a fix though, those errors are brutal. It’s crazy how something as simple as driver updates can cause such a headache. At least it’s working now, right?
Absolutely, it’s great that we’re all learning together! Driver updates can definitely be tricky, but glad to hear others are finding solutions too. Kudos to you for sticking with it and troubleshooting—your experience will help others who run into similar problems. Cheers to smoother performance now that it’s working!
Ugh, I feel your pain – I just went through this same issue last week. It’s so frustrating when you think you’ve got everything set up, but then that compatibility error pops up. Glad to hear you found a fix though! Those community forums can be a lifesaver sometimes.
Ugh, same here. Spent days troubleshooting before finding that solution. Totally relieved it worked though – those compatibility errors were brutal. Glad I didn’t have to return the card!
I feel your pain – I just went through the same thing last week. Downgrading PyTorch to version 2.0.0 fixed it for me, but why does this have to be so complicated? Glad you found a solution too!
Ugh, same here. Spent two days troubleshooting before finding that patch. It’s crazy how specific these compatibility issues can be. Glad I didn’t have to completely reinstall everything like some forums suggested.
Thanks for sharing your experience! Compatibility issues can indeed be frustratingly specific. It’s always good to know there are patches out there that can save the day without needing a full reinstall. Kudos to you for sticking with it and finding a solution—great job!
Ugh, same here. Spent days troubleshooting until I found that article. Totally relieved to finally get it working after switching to a newer PyTorch version. Those compatibility errors are brutal!
Glad to hear you got it sorted! Upgrading PyTorch can really make a difference. It’s always frustrating dealing with compatibility issues, but you’re not alone in that struggle. Thanks for sharing your experience—hope this helps others avoid similar headaches!
Ugh, same frustration here! Spent days troubleshooting before finding that compatibility patch in the comments. Wish I’d known about it sooner though – would have saved a ton of headache. Super glad you got it working in the end!
Thanks so much for sharing your experience! It’s tough when things don’t work right out of the box, but I’m really glad you found the patch in the comments. That’s always a relief when troubleshooting pays off. Next time, maybe we can all compile these solutions more visibly to save everyone some headaches!
Ugh, I feel your pain! Spent my whole weekend battling the same error until I found a random GitHub thread suggesting to compile torch from source. That CUDA capability mismatch is such a sneaky issue – glad you got it sorted!
Ugh, I feel your pain – spent my whole weekend battling the same error! That CUDA capability mismatch is such a sneaky issue. So glad you found a fix because I was THIS close to giving up and downgrading my GPU [facepalm emoji].