The binaries are not shipping with CUDA11.1, as we couldn’t prune libs with this version and were running into errors. If you need to use the latest library versions (CUDA, cudnn, NCCL etc.), you could always build PyTorch from source or use the NGC docker containers 14.



 LukePoga:

Say you are spending thousands on A100s, you would not use pytorch because its not maximising the latest CUDA!


Your A100s work with CUDA11.0 and since sm86 is SASS binary compatible with sm80, also the 30XX series works.