Pytorch cuda compatibility chart It provides highly optimized implementations of primitives such as convolution, pooling, and normalization operations. 2 without downgrading Jul 24, 2024 · Your don’t need to install a CUDA toolkit as the PyTorch binaries ship with their own CUDA dependencies. For legacy GPUs, refer to Legacy CUDA GPU Compute Capability. The relationship between CUDA version and PyTorch compatibility is critical for ensuring optimal performance and functionality when running deep learning workloads. 7 but now while downloading I see pytorch 11. MemPool () API is no longer experimental and is stable. Oct 2, 2025 · 1. 0a0+34c6371d24. ) don’t have the supported compute capabilities encoded in there file names. 1 in this env i got env conflicts, so i created a python venv inside the conda env and installed 0. 10, pytorch could not use with GPU. 6 and installing CUDA 11. Access and install previous PyTorch versions, including binaries and instructions for all platforms. PyTorch’s biggest strength beyond our amazing community is that we continue as a first-class Python integration The GPU type you choose for your workload dictates the necessary Nvidia driver and CUDA Toolkit version for your virtual machine. Apr 20, 2024 · The following sections highlight the compatibility of NVIDIA® cuDNN versions with the various supported NVIDIA CUDA® Toolkit, CUDA driver, and NVIDIA hardware versions. It seems like I cannot get rid of a warning ( UserWarning: Failed to initialize NumPy: _ARRAY_API not found (Triggered internally at . CUDA 13. 6 days ago · PyTorch is a popular open - source deep learning framework known for its dynamic computational graphs and user - friendly API. CUDA (Compute Unified Device Architecture) is a proprietary [3] parallel computing platform and application programming interface (API) that allows software to use certain types of graphics processing units (GPUs) for accelerated general-purpose processing, significantly broadening their utility in scientific and high-performance computing. We would like to show you a description here but the site won’t allow us. 8 is supposed to be the first version to support the RTX 4090 cards. Jun 2, 2023 · This article will cover setting up a CUDA environment in any system containing CUDA-enabled GPU (s) and a brief introduction to the various CUDA operations available in the Pytorch library using Python. md May 31, 2024 · I would like to leverage the Python (3. Versions outside the ranges may unofficially work in some cases. Nov 20, 2023 · If you have trouble finding compatible versions you can refer to the cuDNN Support Matrix documentation page, where you will find compatibility tables between different combinations of operating systems, drivers and CUDA/cuDNN versions. 01 supports CUDA compute capability 6. 0 and later. Understanding the compatibility between PyTorch and CUDA driver 410 is crucial for users who have systems with this specific driver version. Jan 30, 2025 · Tensors and Dynamic neural networks in Python with strong GPU acceleration - PyTorch Versions · pytorch/pytorch Wiki The CUDA driver's compatibility package only supports particular drivers. Processing meta-data is a fixed cost while the cost of the computational work Aug 6, 2024 · When installing pytorch 0. 1+cpu. Features for Platforms and Software # Jan 1, 2025 · Hello Everyone. Below is a detailed breakdown of the compatibility between PyTorch, CUDA, and cuDNN. PyTorch System Requirements In this article, we’ll walk through the essential system requirements for PyTorch, including hardware . Key Features and Enhancements This PyTorch release includes the following key features and enhancements. 2 supports the same GPU architectures as 10. 8, as it would be the minimum versions required for PyTorch 2. It is recommended, but not required, that your Windows system has an NVIDIA GPU in order to harness the full power of PyTorch’s CUDA support. For a complete list of supported drivers, see CUDA Application Compatibility. CPU cores process meta-data like tensor shapes in order to prepare arguments needed to launch GPU kernels. If you use --index-url instead of --extra-index-url, it replaces PyPI entirely, which will likely break other dependencies. yml (Ubuntu 20. 0 Update 2 - Release Notes 1. The installation packages (wheels, etc. To fine-tune it, i chose autotrain-advanced with Python Oct 21, 2021 · We are excited to announce the release of PyTorch 1. See the compatibility matrix, basic concepts, and examples for different GPU architectures and CUDA toolkits. I'm seeking advice on how to find compatible library versions or how others generally resolve version compatibility issues. NVIDIA Ada GPU Architecture Compatibility 1. 8, CUDNN 8. Ensuring compatibility between Mar 6, 2025 · The following sections highlight the compatibility of NVIDIA cuDNN versions with the various supported NVIDIA CUDA Toolkit, CUDA driver, and NVIDIA hardware versions. something like an R535 driver will not prevent you from using e. MLPerf training v1. csv. 1. 8, but would fail to run the binary with CUDA 12. I have windows 11 pro, rtx 4080, i9 13900h and 64 gb ram in my system. 4, CUDNN Dec 2, 2024 · When working with PyTorch, it’s essential to ensure compatibility between the PyTorch version, CUDA version, and the NVIDIA driver version. Aug 5, 2025 · complete list of nvidia gpus and their cuda compute capabilities Dec 4, 2024 · This comprehensive guide clarifies TensorFlow and CUDA version compatibility, ensuring you choose the right combination for optimal deep learning performance. PyTorch 1. Depending on your system and compute requirements, your experience with PyTorch on Windows may vary in terms of processing time. The full release notes are available here. 13. 3 -c pytorch Pytorch is an open source machine learning framework with a focus on neural networks. This topic is somewhat similar to a past question here. This guide provides a clear compatibility matrix to help you set up your deep learning environment without a hitch. x. 1 using pip. md Oct 28, 2022 · I’m current experiencing inter-op issues for code compiled for torch 1. 8 , python 3. 0 version. CUDA provides developers with tools to Is there somewhere a searchable version compatibility database? As in all python projects reconciling versions is a pretty annoying problem, I meet it again and again. 6 or Python 3. Sep 5, 2025 · 🔥 PyTorch & CUDA Compatibility Cheatsheet 🔥 Finding the right combination of PyTorch, CUDA, torchvision, and torchaudio can be tricky. 0 feature release (target March 2023), we will target CUDA 11. It enables mixing multiple CUDA system allocators in the same PyTorch program. 2) libraries / frameworks, which are PyTorch and CUDA. 0a0+e000cf0ad9, 2. 05 release, torchtext and torchdata have been removed in the NGC PyTorch container. Dec 11, 2020 · Alpha December 11, 2020, 8:06am 1 Is there a table which shows the supported cuda version for every pytorch version? Thanks. 0 to 2. Avoid common setup errors and ensure your ML environment is correctly configured. GPU Requirements Release 21. 2 v2. CUDA Compatibility # CUDA Compatibility describes the use of new CUDA toolkit components on systems with older base installations. 1 -c pytorch-nightly -c nvidia Check if the CUDA is compatible with the installed PyTorch by running Feb 9, 2021 · PyTorch doesn't use the system cuda when installed via pip or conda. If you are still using or depending on CUDA 11. CUDA 11. 04, CUDA 11. Different tensorflow-gpu versions can be installed by creating different anaconda environments (I prefer to use miniconda that offers minimal installed packages). x/6. For results see table. Overview Introducing PyTorch 2. md at main · pytorch/pytorch Mar 5, 2024 · Furthermore, you are referring to CUDA versions which PyTorch provides prebuilt binaries for—you are also free to build PyTorch from source (and PyTorch’s CUDA components using your local CUDA toolkit) if you wish to use a newer CUDA toolkit. 8. GPU Requirements Release 22. For more information, see CUDA Compatibility and Upgrades. 35. The CUDA driver's compatibility package only supports particular drivers. 0 and cuDNN / NVIDIA driver versions PyTorch: 1. 0 and higher. I tried to install pytorch=1. 2. 7) and sm_90 (using the binaries shipping with CUDA 11. 5. 11. 1, so I’m unsure why you would need to use 10. Feb 25, 2025 · Your locally installed CUDA toolkit won’t be used as PyTorch binaries ship with their own CUDA runtime dependencies. 04. 6 Can I get some consultation help Aug 20, 2021 · The compatibility of PyTorch with CUDA can be seen in the PyTorch Versions Page added on the Official PyTorch Website. 8 as the experimental version of CUDA and Python >=3. See full list on pytorch. so files. Apr 17, 2025 · Struggling with TensorFlow and NVIDIA GPU compatibility? This guide provides clear steps and tested configurations to help you select the correct TensorFlow, CUDA, and cuDNN versions for optimal performance and stability. Your RTX 3000 mobile GPU should be a Turing GPU and is thus also supported. 0–7. You would need to install an NVIDIA driver first and can install any binaries afterwards. However, the performance and compatibility of PyTorch on NVIDIA GPUs are highly dependent on the correct NVIDIA driver version 2 days ago · How to Fix: Can’t Install GPU-Enabled PyTorch in Conda Environment from environment. 1 is 0. 6 I have hard time to find the right PyTorch packages that are compatib… Jul 9, 2025 · The following sections highlight the compatibility of NVIDIA cuDNN versions with the various supported NVIDIA CUDA Toolkit, CUDA driver, and NVIDIA hardware versions. Mask R-CNN Deep learning frameworks use GPUs to accelerate computations, but a significant amount of code still runs on CPU cores. There you can find which version, got release with which version! Dec 10, 2024 · Hi, In the pytorch installation documentation, it is mentioned to check the compatibility matrix: to install the correct pytorch version but this matrix is inconsistent with what I can download in the Jetson Download Center | NVIDIA Developer I cannot find the compatible pytorch wheels for the JetPack 6. 08 supports CUDA compute capability 6. In any case, the latest versions of Pytorch and Tensorflow are, at the time of this writing, compatible with Cuda 11. x family of toolkits. 03 supports CUDA compute capability 6. So, Installed Nividia driver 450. Here are the key points regarding compatibility based on the latest information: Mar 28, 2022 · Hi How can I find whether pytorch has been built with CUDA/CuDNN support? Is there any log file about that? Jul 15, 2020 · Recently, I installed a ubuntu 20. 0a0+b465a5843b). Aug 30, 2023 · Learn how to match CUDA, GPU, base image, and PyTorch versions for optimal performance and compatibility. 8 => * PyTorch 1. One of its key features is the ability to leverage the power of NVIDIA GPUs through the CUDA Toolkit. Currently I try to use pytorch2. 2 . 7 builds, we strongly recommend moving to at least CUDA 11. 03 CUDA Version: 12. This is my version of NVIDIA driver and CUDA I installed the newest version of pytorch with python 3. Where are they ? Do I have to The CUDA driver's compatibility package only supports specific drivers. The table below indicates the coverage of tested versions in our CI. 2 in PyTorch. Sep 27, 2023 · 🐛 Describe the bug Hi, Context I want to fine-tune Llama2-70B-chat-hf with any dataset on an Nvidia H100 instance running with CUDA 12. 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. 0a0+df5bbc0, 2. Aug 14, 2025 · CUDA & PyTorch Compatibility by Compute Capability (CC) This cheat sheet maps Compute Capability (CC) → newest usable CUDA Toolkit → a recent PyTorch version with official wheels → ready-to-copy pip command. Data Source: This information is compiled from the official PyTorch Previous Versions Page. 8). pytorch_compute_capabilities. Your current driver should allow you to run the PyTorch binary with CUDA 11. Sep 19, 2022 · I have installed recent version of cuda toolkit that is 11. 4 support? Nov 30, 2024 · I want to use GPU to train my model. x drops support for these architectures in the toolkit. To ensure optimal performance, it is essential to use compatible versions of CUDA and cuDNN with PyTorch. 02 (Linux) / 452. Sep 16, 2024 · Hello, I’m in the process of fine tuning a LLM, and my machine has these specifications: NVIDIA RTX A6000 NVIDIA-SMI 560. post201 CUDA version by PyTorch: 11. I want to rely on the compatible versions stated by using ~= for both of these on a single line. To get both TensorFlow and PyTorch working with your GPU you could use multiple versions of CUDA and cuDNN CUDA Toolkit 13. The easiest way is to look it up in the previous versions section. Please Jul 31, 2018 · I have noticed that some newer TensorFlow versions are incompatible with older CUDA and cuDNN versions. cuda. 0 being called from python running torch 1. 0 was released with an earlier driver version, but by upgrading to Tesla Recommended Drivers 450. Only a properly installed NVIDIA driver is needed to execute PyT… Apr 23, 2025 · hello; I am currently trying to build and install PyTorch for Jetson Orin; CUDA version is 12. txt, use the --extra-index-url parameter. 1 and vice-versa. 06 is based on 2. 2 or go with PyTorch built for CUDA 10. Over the last few years we have innovated and iterated from PyTorch 1. My question is, should I downgrade the CUDA package to 10. GPU Feb 8, 2025 · Step-by-step guide to installing PyTorch with NVIDIA GPU support using venv, Conda, or Docker. NVIDIA GPUs are widely used to accelerate PyTorch computations due to their parallel processing capabilities. 13 and moved to the newly formed PyTorch Foundation, part of the Linux Foundation. 1; I’m not sure if this version is compatible with CUDA12. Nvidia drivers serve as intermediaries between the operating system (OS) and Nvidia GPUs, and compatibility varies for each GPU model. Jul 5, 2025 · 🚀 Mastering CUDA Compatibility: Which Version Matches Your GPU? 🔍 🧠 Unlock the Power of NVIDIA GPUs Without the Guesswork If you’re diving into AI, deep learning, or high-performance … Feb 26, 2025 · For Cuda 11. 4 toolkit? Or could I build pytorch with cuda 11. As shown in your screenshot you’ve installed a CPU-only binary: 2. 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. 2 should not break your PyTorch GPU support. Oct 26, 2021 · Table 1. Lucky me, for Cuda 11. If you've ever struggled to determine the correct library versions for your setup, this tool provides a streamlined solution. 0a0+5228986c39. Understanding the system requirements for PyTorch is crucial for ensuring optimal performance and compatibility. 0, our first steps toward the next generation 2-series release of PyTorch. org Nov 13, 2025 · Support Matrix # GPU, CUDA Toolkit, and CUDA Driver Requirements # The following sections highlight the compatibility of NVIDIA cuDNN versions with the various 6 days ago · PyTorch CUDA Toolkit Compatibility: A Comprehensive Guide PyTorch is a popular open - source machine learning library that provides a seamless experience for building and training deep learning models. Ensuring compatibility between these components is critical for optimal performance. 1 witt … What are the compatible CUDA and cuDNN versions for PyTorch? PyTorch is a popular deep learning framework that leverages NVIDIA GPUs for accelerated computing. For a complete list of supported drivers, see the CUDA Application Compatibility topic. Nov 26, 2021 · Hi all! Does Pytorch supports CUDA 11. 39 (Windows) as indicated, minor version compatibility is possible across the CUDA 11. Prerequisites Supported Windows Aug 4, 2023 · Hello, Transformers relies on Pytorch, Tensorflow or Flax. 9 is undefined. When running nvcc --version, it shows CUDA 9. 4 Opening this RFC to discuss CUDA version support for future PyTorch releases: Option 1 - CUDA 11 and CUDA 12: CUDA 11. 9, made by 426 contributors. 1 are compatible. This documentation is organized into two main sections: General CUDA Focuses on the core CUDA infrastructure including component versions, driver compatibility, compiler/runtime Aug 6, 2024 · When installing pytorch 0. 4. The GPU's driver must be supported by the operating system running on the virtual machine. Example of compatibility matrix: Nov 13, 2025 · Table of Contents Fundamental Concepts What are CUDA Drivers? What is PyTorch? The Relationship between CUDA Drivers and PyTorch Versions Usage Methods Installing the Right CUDA Driver Installing the Compatible PyTorch Version Common Practices Checking CUDA Driver and PyTorch Compatibility Handling Compatibility Issues Best Practices Keeping CUDA Drivers and PyTorch Up - to - Date Testing New Feb 2, 2023 · For the upcoming PyTorch 2. 7 as the stable version and CUDA 11. Jul 16, 2025 · The following sections highlight the compatibility of NVIDIA cuDNN versions with the various supported NVIDIA CUDA Toolkit, CUDA driver, and NVIDIA hardware versions. 04 supports CUDA compute capability 6. 05 version and CUDA 11. Apr 26, 2022 · On the website of pytorch, the newest CUDA version is 11. 08 is based on 2. May 25, 2024 · 💡 Insight: PyTorch library uses the CUDA Toolkit to offload computations to the GPU. 8, <=3. To my surprise, Pytorch for CUDA 11 has not yet been rolled out. 2) should stay on CUDA 12. Thus, users should upgrade from all R418, R440, and R460 drivers, which are not forward-compatible with CUDA 11. Jan 20, 2024 · Addendum 2 – 2025. Well, not fully, apparently: MapSMtoCores for SM 8. Highlights include: CUDA Nov 3, 2025 · Support Matrix # These support matrices provide an overview of the supported platforms, features, and hardware capabilities of the TensorRT APIs, parsers, and layers. This is a standard compatibility path in CUDA: newer drivers support older CUDA toolkit versions. It comes delivered with its own version of cuda. Installing on Windows PyTorch can be installed and used on various Windows distributions. 6 is there, are they two compatible? Note CUDA 11. Oct 11, 2023 · No, you don’t need to download a full CUDA toolkit and would only need to install a compatible NVIDIA driver, since PyTorch binaries ship with their own CUDA dependencies. 80. 0 (stable) conda install pytorch torchvision torchaudio cudatoolkit=11. 2-specific operators were added which require this minimal release from 2019. 23: To include the torch, torchvision, torchaudio packages into a requirements. 6; The pytorch version I have currently chosen is 2. PyTorch’s biggest strength beyond our amazing community is that we continue as a first-class Python integration The CUDA driver's compatibility package only supports particular drivers. 3. 04 on my system. 10. CUDA and PyTorch Compatibility PyTorch Apr 5, 2024 · 🚀 [RFC] Cuda support matrix for Release 2. GPU Requirements Release 20. 1 with cuda 11. The PyTorch version that you want to use must be compatible with the CUDA version and also with the Python version installed. 0 performance improvement with PyTorch CUDA graph. PyTorch itself is developed independently and needs to be compatible with the installed CUDA version. You could check which 10. CUDA GPU Compute Capability Compute capability (CC) defines the hardware features and supported instructions for each NVIDIA GPU architecture. 0 Update 2. I wonder which cuda, cudnn and torch versions will work smoothly for my system? I am also using the nvdia game ready driver. 0-12. Find the compute capability for your GPU in the table below. Thank you in advance. 1 is compatible with all GPUs between sm_37 to sm_89 (using the binaries shipping with CUDA 11. I typically use the first. CuDNN (CUDA Deep Neural Network library) is a GPU - accelerated library for deep neural networks developed by NVIDIA. Jan 24, 2023 · PyTorch is generally backwards-compatible with previous CUDA versions, so uninstalling CUDA 11. Overview Welcome to the release notes for NVIDIA® CUDA® Toolkit 13. Sep 18, 2024 · Compatibility Between Upstream and Downstream Device-Generic Unit Tests Most unit tests in PyTorch focus on CPU and CUDA devices, which limits participation from users with other hardware. 3, pytorch version will be 1. Jul 13, 2023 · conda install pytorch torchvision torchaudio pytorch-cuda=12. All the commands in this tutorial will be done inside the … Overview Introducing PyTorch 2. \torch\csrc\utils\tensor Aug 29, 2023 · PyTorch 2. How have you determined that your pytorch is using cuda 9. By looking at the Compatibility Chart we see that with CUDA 11. This release includes enhancements and fixes across the CUDA Toolkit and its libraries. Does an overview of the compatible versions or even a list of officially tested combinations Check CUDA version compatibility with PyTorch: learn how to verify and update for optimal performance. 4 => Which pytorch latest versions are available? Nov 28, 2019 · Even if a version of pytorch uses a “cuda version” that supports a certain compute capability, that pytorch might not support that compute capability. Maxwell/Pascal/Volta (CC 5. 9. To address this, a plan to modify PyTorch’s unit testing framework, enabling better support for non-CUDA devices. For more information, see CUDA Compatibility and Upgrades and NVIDIA CUDA and Drivers Support. CUDA was created by Nvidia starting in 2004 and was Apr 10, 2024 · The Simple Guide: Deep Learning Installation with RTX 4090 (CUDA, cuDNN, Tensorflow, PyTorch) This tutorial is tested with RTX4090. Default to use 128 Cores/SM Check cuDNN version compatibility with PyTorch on NVIDIA GPUs: a step-by-step guide to ensure optimal performance. Apr 2, 2021 · My Configuration In my development environment with NVIDIA RTX 2070 GPU I have following multiple configurations in my system. 0 we can Compatibility matrix PyTorch Lightning follows NEP 29 which PyTorch also follows (#74203). py checks the compute capabalities of each pytorch package in the PyTorch conda channel by running cuobjdump from the CUDA Toolkit on the included *. Jul 13, 2023 · Seriously?! Isn’t “PyTorch Build from Source” the whole purpose of building any PyTorch on any CUDA? No, and it wouldn’t make sense trying to support CUDA 1. GPU Requirements Release 19. 0 to the most recent 1. Also note that 10. 1 Like ptrblck December 11, 2020, 9:57am 2 Tensors and Dynamic neural networks in Python with strong GPU acceleration - pytorch/RELEASE. . Starting with the 24. 1 or is it a miracle it worked for the other minor versions of PyTorch so far? The CUDA driver's compatibility package only supports particular drivers. 1 (2. For earlier container versions, refer to the Frameworks Support Matrix. 29 CUDA 12. 2” driver e. TorchVersionSpecifier is a tool designed to simplify the process of finding compatible PyTorch, TorchVision, and Torchaudio versions for various Python and CUDA environments. 12. And you can follow normal installation process for installing different version of CUDA and cuDNN together. 10 updates are focused on improving training and performance of PyTorch, and developer usability. What are the cuDNN and CUDA version requirements for TensorFlow and PyTorch? TensorFlow and PyTorch, two of the most popular deep learning frameworks, rely on NVIDIA's CUDA and cuDNN libraries for GPU acceleration. 51. An unofficial list of supported compute capability by each release of PyTorch (linux) - evelthon/PyTorch-supported-compute-capability Jan 19, 2023 · Hi, When I was checking the versions of CUDA and PyTorch in the docker container that is used in pets-prize-challenge-runtime, I noticed that the version numbers returned through various interfaces seem to be inconsistent. However, you may need to reinstall PyTorch with the appropriate CUDA version specified in order for it to work properly. Only if you couldn't find it, you can have a look at the torchvision release data and pytorch's version. This release is composed of over 3,400 commits since 1. 2 CUDA version by Ensure seamless integration between CUDA, cuDNN, and PyTorch with version compatibility best practices and troubleshooting tips. Dec 22, 2023 · The latest currently available driver will work on all the GPUs you mention, and using a “CUDA 12. torch. Since it was a fresh install I decided to upgrade all the software to the latest version. 1) - Resolving 'Torch Not Compiled with CUDA Support' Error 6 days ago · The CUDA driver version 410 was a widely used driver release at a certain point in time. What compatibility should I expect for code compiled for different patch versions of torch? Is this a bug introduced by 1. 7 and Python 3. Oct 14, 2025 · Nvidia driver and CUDA version compatibility chart - nvidia_driver_cuda_version_compatibility_chart. 0? What model of GPU do you have? Apr 3, 2022 · The corresponding torchvision version for 0. About this Document This application note, NVIDIA Ada GPU Architecture Compatibility Guide for CUDA Applications, is intended to help developers ensure that their NVIDIA ® CUDA ® applications will run on the NVIDIA ® Ada Architecture based GPUs. 0. x/7. PyTorch container image version 25. What about Cuda 12. This adds the PyTorch CUDA-specific index in addition to PyPI. - PyTorch GPU Setup. 1 Update 1 as it’s too old. 6. 6 days ago · PyTorch is an open-source machine learning library based on the Torch library, used for applications such as computer vision and natural language processing. 7. Pytorch has a supported-compute-capability check explicit in its code. We want to sincerely thank our community for continuously improving PyTorch. g. Additionally, the Pytorch versions listed on the official website are incompatible with the server's CUDA version. Jul 23, 2025 · PyTorch, an open-source machine learning library, is widely used for applications ranging from natural language processing to computer vision. rrzgiq qheqpvhv oiamu gnbykq stt zyqvkkkw aafql hhgjfzm jjyoquice hlfferm xzitgti qafzne bax fjlfn yjbcwnx