Pytorch cuda version compatibility. For more information, see CUDA Compatibility and Upgrades.
Pytorch cuda version compatibility . These predate the html page above and have to be manually installed by downloading the wheel file and pip install downloaded_file Oct 11, 2023 · A discussion thread about how to match CUDA and PyTorch versions for optimal performance and compatibility. PyTorch container image version 24. Note: most pytorch versions are available only for specific CUDA versions. 6 or Python 3. Important Note The CUDA version that PyTorch is compiled against might not necessarily match the highest CUDA version installed on your system. 5. 0 torchvision==0. 07 is based on 2. For a complete list of supported drivers, see the CUDA Application Compatibility topic. 4. PyTorch's Built-in CUDA Version. Feb 2, 2023 · For the upcoming PyTorch 2. Libraries like PyTorch with CUDA 12. GPU Requirements Release 21. 2025-04-26 . _cuda_getDriverVersion() is not the cuda version being used by pytorch, it is the latest version of cuda supported by your GPU driver (should be the same as reported in nvidia-smi). 0 and higher. 1; I’m not sure if this version is compatible with CUDA12. Then, run the command that is presented to you. 8, <=3. My cluster machine, for which I do not have admin right to install something different, has CUDA 12. 1 is not available for CUDA 9. PyTorch versions is compatible with one or a few specific CUDA versions, or more precisely, with corresponding CUDA runtime API versions. I tried to modify one of the lines like: conda install pytorch==2. 0a0+ecf3bae40a. Sep 16, 2024 · PyTorch officially supports CUDA 12. 0 torchaudio==2. Aug 30, 2023 · PyTorch and CUDA. PyTorch will use the libraries it was built with. 0. 7 as the stable version and CUDA 11. 1. Following is the Release Compatibility Matrix for PyTorch, copied from here: The CUDA driver's compatibility package only supports particular drivers. Find out the compatibility table, the installation commands and the verification methods for each library. Apr 26, 2025 · Understanding PyTorch CUDA Compatibility: Drivers and Toolkits . 1 support execute on systems with CUDA 12. 11. Nov 20, 2023 · Learn how to choose and install the right versions of PyTorch, CUDA and xFormers for your AI applications. To install PyTorch via pip, and do have a CUDA-capable system, in the above selector, choose OS: Windows, Package: Pip and the CUDA version suited to your machine. 1, 11. For more information, see CUDA Compatibility and Upgrades and NVIDIA CUDA and Drivers Support. Feb 4, 2025 · I have read on multiple topics “The PyTorch binaries ship with all CUDA runtime dependencies and you don’t need to locally install a CUDA toolkit or cuDNN. 17. 2. 6; The pytorch version I have currently chosen is 2. You would need to install an NVIDIA driver For a complete list of supported drivers, see the CUDA Application Compatibility topic. The relationship between CUDA version and PyTorch compatibility is critical for ensuring optimal performance and functionality when running deep learning workloads. 8 as the experimental version of CUDA and Python >=3. The value it returns implies your drivers are out of date. 6 because the newer driver includes support for all functionality in earlier CUDA versions (12. Keep in mind that these examples will likely run without errors in many cases due to the forward compatibility we discussed, but they might not be utilizing the hardware in the most optimized way. 8 and the GPU you use is Tesla V100, then you can choose the Feb 24, 2024 · If you look at this page, there are commands how to install a variety of pytorch versions given the CUDA version. 0 feature release (target March 2023), we will target CUDA 11. 2 (Old) PyTorch Linux binaries compiled with CUDA 7. 1 through conda, Python of your conda environment is v3. 4 would be the last PyTorch version supporting CUDA9. PyTorch container image version 25. 0 Apr 23, 2025 · hello; I am currently trying to build and install PyTorch for Jetson Orin; CUDA version is 12. 8, as it would be the For a complete list of supported drivers, see the CUDA Application Compatibility topic. 6 Can I get some consultation help Tensors and Dynamic neural networks in Python with strong GPU acceleration - pytorch/RELEASE. Users share their questions, issues and solutions related to CUDA drivers, PyTorch binaries and virtual environments. 08 supports CUDA compute capability 6. For more information, see CUDA Compatibility and Upgrades. Only a properly installed NVIDIA driver is needed to execute PyT… With CUDA. PyTorch, a popular open-source machine learning framework, relies on NVIDIA's CUDA toolkit to accelerate computations on GPUs. 7 builds, we strongly recommend moving to at least CUDA 11. Just select the PyTorch (or Python or CUDA) version or compute capability you have, the page will give you the available combinations. Feb 9, 2021 · torch. _C. Verification May 17, 2025 · Okay, let's illustrate the scenario of using a PyTorch version built for CUDA 11. For example, if you want to install PyTorch v1. If you are still using or depending on CUDA 11. 1 as the latest compatible version, which is backward-compatible with your setup. For example pytorch=1. 0 pytorch-cuda=12. Dec 11, 2020 · I think 1. Note that you don’t need a local CUDA toolkit, if you install the conda binaries or pip wheels, as they will ship with the CUDA runtime. 4, 12. Often, the latest CUDA version is better. 01 is based on 2. 0a0+3bcc3cddb5. 7. 3 on a system with CUDA 11. 8). 6. 7 and Python 3. Using an incompatible version might lead to errors or sub-optimal performance. However, the only CUDA 12 version seems to be 12. 2 using example code. md at main · pytorch/pytorch Feb 25, 2025 · Your locally installed CUDA toolkit won’t be used as PyTorch binaries ship with their own CUDA runtime dependencies. Key Features and Enhancements This PyTorch release includes the following key features and enhancements. fmdxxhraqxxcoeyojivgyardxfhylcqixhwpavrzuitfstnoybw