No, I don’t think so as the install command works for me in a new and empty conda environment:
conda install pytorch torchvision torchaudio pytorch-cuda=12.4 -c pytorch -c nvidia
...
The following packages will be downloaded:
package | build
---------------------------|-----------------
blas-1.0 | mkl 6 KB
brotli-python-1.0.9 | py310h6a678d5_8 356 KB
certifi-2024.8.30 | py310h06a4308_0 162 KB
cuda-cudart-12.4.127 | 0 198 KB nvidia
cuda-cupti-12.4.127 | 0 16.4 MB nvidia
cuda-libraries-12.4.1 | 0 2 KB nvidia
cuda-nvrtc-12.4.127 | 0 21.0 MB nvidia
cuda-nvtx-12.4.127 | 0 58 KB nvidia
cuda-opencl-12.6.77 | 0 25 KB nvidia
cuda-runtime-12.4.1 | 0 2 KB nvidia
cuda-version-12.6 | 3 16 KB nvidia
...
pytorch-2.5.1 |py3.10_cuda12.4_cudnn9.1.0_0 1.46 GB pytorch
pytorch-cuda-12.4 | hc786d27_7 7 KB pytorch
pytorch-mutex-1.0 | cuda 3 KB pytorch
...
python -c "import torch; print(torch.__version__); print(torch.version.cuda); print(torch.cuda.is_available()); print(torch.randn(1).cuda())"
2.5.1
12.4
True
tensor([0.3827], device='cuda:0')
However, you could also try to use the pip wheels if you are seeing issues with conda as conda binaries will be deprecated as mentioned here.