Pytorch versions 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. This compiled mode has the potential to speedup your models during training and inference. For earlier container versions, refer to the Frameworks Support Matrix. ndarray). Alanna Burke edited this page Apr 23, 2025 · 17 revisions. 4. 0 instead of 1. 0 See full list on phoenixnap. Why 2. PyTorch is a powerful open-source machine learning library for deep learning applications. Installing previous versions of PyTorch Installing previous versions of PyTorch Join us at PyTorch Conference in San Francisco, October 22-23. Jump to bottom. Feb 9, 2025 · in nvidia-smi I have cuda 12. These predate the html page above and have to be manually installed by downloading the wheel file and pip install downloaded_file Apr 23, 2025 · PyTorch Versions. Especially in older PyTorch versions we used the RUNPATH to load libs which could prefer your local libs. 6 One and I have the latest Nvidia drivers also. For example pytorch=1. com Sep 6, 2024 · Learn how to determine the PyTorch version installed on your system using Python code, pip command, or conda command. A deep learning research platform that provides maximum flexibility and speed. 14? PyTorch 2. Pick a version. Often, the latest CUDA version is better. 3 do not provide wheels compatible with newer CUDA versions (e. 0 is the latest PyTorch version. Select your preferences and run the install command. I am on Win 11 PC , intel chip v100 2x-32Gb → Also if somewhere in some env I install torch version 1… PyTorch Documentation . Feb 4, 2025 · Yes, you don’t need to install a CUDA toolkit locally. 1 is not available for CUDA 9. If you use NumPy, then you have used Tensors (a. Stable represents the most currently tested and supported version of PyTorch. compile. md at main · pytorch/pytorch A replacement for NumPy to use the power of GPUs. PyTorch 2. Preview is available if you want the latest, not fully tested and supported, builds that are generated nightly. 2 (Old) PyTorch Linux binaries compiled with CUDA 7. Getting Started. 14 would have been. This simple code imports PyTorch and prints the version, enabling you to seamlessly integrate version checks into your Python workflows. [Beta] FP16 support for X86 CPUs (both eager and Inductor modes) Float16 datatype is commonly used for reduced memory usage and faster computation in AI inference and training. Jun 2, 2025 · Unfortunately, earlier PyTorch versions like 2. 6. Note: most pytorch versions are available only for specific CUDA versions. Domain Version Compatibility Matrix for PyTorch. This causes difficulty for many users who: • Depend on stable older PyTorch versions for reproducibility or compatibility reasons; • Need to utilize newer GPUs (e. For a deeper understanding of your PyTorch installation, especially if you have it in a virtual environment, activate the environment and run the following commands: We will keep the set of C APIs stable across Pytorch versions and thus provide backward compatibility guarantees for AOTInductor-compiled models. Jun 6, 2025 · Install PyTorch. 0 (stable) v2. From Pytorch, I have downloaded 12. 3. PyTorch provides Tensors that can live either on the CPU or the GPU and accelerates the computation by a NVIDIA PyTorch Container Versions The following table shows what versions of Ubuntu, CUDA, PyTorch, and TensorRT are supported in each of the NVIDIA containers for PyTorch. Different PyTorch versions may have different APIs and features. 3 or 12. 0 is what 1. 8. Checking PyTorch version is simple and can be done through Python code or command line. , CUDA 12. PyTorch version can affect compatibility with hardware and software configurations. , 5090) which require updated CUDA runtimes; May 18, 2025 · PyTorch version checking is crucial for project reproducibility and compatibility. 0 offers the same eager-mode development experience, while adding a compiled mode via torch. 5. Jun 4, 2025 · Installation instructions and binaries for previous PyTorch versions may be found on our website. 2. a. This should be suitable for many users. 7. 0. g. k. Three-pointers to get you started: Tensors and Dynamic neural networks in Python with strong GPU acceleration - pytorch/RELEASE. main (unstable) v2. Method 3: Inspecting PyTorch Build Information. 4). PyTorch Documentation . Oct 17, 2024 · Tensors and Dynamic neural networks in Python with strong GPU acceleration - History for PyTorch Versions · pytorch/pytorch Wiki 2. However, you could check if PyTorch still tries to open locally installed CUDA or cuDNN libs by running your workload via LD_DEBUG=libs. 0; v2. pgfjpbptfssufbupkofqacyyupcjmoxclxvngoyofdqsmrf