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Cuda toolkit version compatibility

  • Cuda toolkit version compatibility. Apr 2, 2021 · My Configuration. 10 is not compatible for GPU support in Windows native. Version Information. A GPU will support a specific compute version, and if your CUDA version minimum compute capability is higher than that supported by your GPU, your code will not compile or run. 0, to ensure that nvcc will generate cubin files for all recent GPU architectures as well as a PTX version for forward compatibility with future GPU architectures, specify the appropriate -gencode= parameters on the nvcc command line as shown in the examples below. Need advice on if I am c Table 1 CUDA 12. Use the CUDA APT PPA to install and update the CUDA Toolkit easily and quickly. Dec 11, 2020 · I think 1. Normally, when I work in python, I use virtual environments to set all Nov 3, 2022 · 上の図より、ディスプレイドライバ「515. NVIDIA GPUs power millions of desktops, notebooks, workstations and supercomputers around the world, accelerating computationally-intensive tasks for consumers, professionals, scientists, and researchers. Oct 23, 2020 · Maximum CUDA Version Supported: CUDA 10. 5 (sm_75). 1) Versions… TensorFlow. Reload to refresh your session. 0 for Windows and Linux operating systems. GPU Coder has been tested with CUDA Toolkit v9. There was no reason to suspect that, but the suspicion grew its roots because, I see that latest Nsight version does not mentions 950M as supported card. 8. CUDA Components. 80. Or should I download CUDA separately in case I wish to run some Tensorflow code. Previously, a standalone version of NVIDIA JetPack supports a single release of CUDA, and you did not have the ability to upgrade CUDA on a given NVIDIA JetPack version. 111. 0: Architectures Supported: Turing and below. I used different options for Aug 29, 2024 · When using CUDA Toolkit 8. 0 (through CUDA compatibility platform). 3 (November 2021), Versioned Online Documentation Jun 21, 2022 · Running (training) legacy machine learning models, especially models written for TensorFlow v1, is not a trivial task mostly due to the version incompatibility issue. . Applications that used minor version compatibility in 11. 6 | 2 Component Name Version Information Supported Architectures Aug 29, 2024 · CUDA on WSL User Guide. 64 RN-06722-001 _v11. _C. 7), you can run: Sep 27, 2018 · This package introduces a new CUDA compatibility package on Linux cuda-compat-<toolkit-version>, available on enterprise Tesla systems. Turing and below. 14. 7 | 2 Component Name Version Information Supported Architectures Mar 18, 2019 · I also downloaded the cuDNN whatever the latest one is and added the files ( copy and paste ) to the respective folders in the cuda toolkit folder. The generated code automatically calls optimized NVIDIA CUDA libraries, including TensorRT, cuDNN, and cuBLAS, to run on NVIDIA GPUs with low latency and high-throughput. Aug 29, 2024 · 1. Sep 19, 2022 · How to run pytorch with NVIDIA "cuda toolkit" version instead of the official conda "cudatoolkit" version 13 Difference between versions 9. 1. I see a lot of questions on the forum related to Visual Studio 2022 support. Applications Using CUDA Toolkit 9. 08 supports CUDA compute capability 6. Sep 2, 2019 · GeForce GTX 1650 Ti. com/deploy/cuda-compatibility/index. 7 Please Note: There is a recommended patch for CUDA 7. 6 Release Notes NVIDIA CUDA Toolkit 11. The CUDA driver's compatibility package only supports particular drivers. CUDA 10. To check compatibility: Verify the CUDA version using nvcc Oct 8, 2021 · NVIDIA-SMI 460. Feb 4, 2023 · So the CUDA Runtime compatibility also depends on CUDA Driver. 4 Component Versions. com/object/cuda_learn_products. CUDA applications built using CUDA Toolkit 9. 17. Jul 31, 2024 · CUDA 11 and Later Defaults to Minor Version Compatibility. CUDA applications built using CUDA Toolkit 11. js TensorFlow Lite TFX All libraries RESOURCES Models & datasets Tools Responsible AI Recommendation systems Groups Contribute Blog Forum The CUDA driver's compatibility package only supports particular drivers. The general flow of the compatibility resolving process is * TensorFlow → Python * TensorFlow → Cudnn/Cuda Mar 16, 2012 · As Jared mentions in a comment, from the command line: nvcc --version (or /usr/local/cuda/bin/nvcc --version) gives the CUDA compiler version (which matches the toolkit version). 6 Update 1 Component Versions ; Component Name. Jul 31, 2024 · CUDA 11. 06) with CUDA 11. In the future, when more CUDA Toolkit libraries are supported, CuPy will have a lighter maintenance overhead and have fewer wheels to release. CUDA Toolkit Major Component Versions. You might be able to use a GPU with an architecture beyond the supported compute capability range. Install cuDNN. Aug 29, 2024 · When using CUDA Toolkit 6. 3+ (currently using pytorch 1. Any CUDA version from 10. Then, run the command that is presented to you. For more information, see CUDA Compatibility and Upgrades and NVIDIA CUDA and Drivers Support . x . Download CUDA 11. pip No CUDA. NVIDIA Ampere and below. Sep 23, 2020 · CUDA 11. It Feb 9, 2021 · torch. minor of CUDA Python. The version of CUDA Toolkit headers must match the major. TensorFlow 2. x family of toolkits. 4 specifies the compatibility with a particular CUDA version. For next steps using your GPU, start here: Run MATLAB Functions on a GPU. A list of GPUs that support CUDA is at: http://www. 7 Release Notes NVIDIA CUDA Toolkit 11. 0, multiple versions of CUDA can be installed on the same machine. Generally, backward compatibility is maintained, and the CUDA Toolkit version Jan 29, 2024 · In this article, you learned how to install the CUDA Toolkit on Ubuntu 22. x Which is the command to see the "correct" CUDA Version that pytorch in conda env is seeing?This, is a similar question, but doesn't get me far. It is essential that your GPU is compatible with the installed CUDA Toolkit version. x driver? Apr 7, 2024 · nvidia-smi output says CUDA 12. This driver branch supports CUDA 10. You can learn more about Compute Capability here. Are you looking for the compute capability for your GPU, then check the tables below. My application is not giving me right prediction results for the GPU trained model(it is returning the base score as prediction output). Applications Built Using CUDA Toolkit 11. 0 which support cuda 11. 0, or 12. CUDA Documentation/Release Notes; MacOS Tools; Training; Archive of Previous CUDA Releases; FAQ; Open Source Packages CUDA 11. 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. Jul 5, 2015 · The rationale is that GeForce 950M supports all features till CUDA 5. 1, but I do not have the nvidia driver compatible with 9. 1. CUDA Python simplifies the CuPy build and allows for a faster and smaller memory footprint when importing the CuPy Python module. During the build process, environment variable CUDA_HOME or CUDA_PATH are used to find the location of CUDA headers. The CUDA Toolkit End User License Agreement applies to the NVIDIA CUDA Toolkit, the NVIDIA CUDA Samples, the NVIDIA Display Driver, NVIDIA Nsight tools (Visual Studio Edition), and the associated documentation on CUDA APIs, programming model and development tools. choosing the right CUDA version depends on the Nvidia driver version. Nov 12, 2023 · Find out your Cuda version by running nvidia-smi in terminal. I transferred cudnn files to CUDA folder. Apr 2, 2023 · † CUDA 11. 2\extras\CUPTI\include , C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12. For CUDA 11. NVIDIA’s official documentation provides a comprehensive list of supported GPUs across its different series, including Tesla, GeForce, Quadro, and Titan. I attempted to install CUDA 9. Supported Architectures. The list of CUDA features by release. CUDA Driver library is always backward compatible. 0 GA2. g. Alternatively, you can configure your project always to build with the most recently installed version of the CUDA Toolkit. CUDA C++ Core Compute Libraries Aug 29, 2024 · 1. I have all the drivers (522. The Release Notes for the CUDA Toolkit. 0 torchvision==0. 0 (October 2021), Versioned Online Documentation CUDA Toolkit 11. CUDA Documentation/Release Notes; MacOS Tools; Training; Archive of Previous CUDA Releases; FAQ; Open Source Packages Jul 25, 2024 · This guide is for the latest stable version of TensorFlow. via conda), that version of pytorch will depend on a specific version of CUDA (that it was compiled against, e. Because of Nvidia CUDA Minor Version Compatibility, ONNX Runtime built with CUDA 11. Different tensorflow-gpu versions can be installed by creating different anacond a environments (I prefer to use miniconda that offers minimal installed packages). Some of the best practices for using CUDA on Ubuntu are: Keep your system and NVIDIA drivers up to date to ensure the compatibility and stability of the CUDA Toolkit. 1 Jan 17, 2024 · CUDA Version Supported: This shows the version of CUDA compatible with the driver (e. Aug 29, 2024 · Open the Visual Studio project, right click on the project name, and select Build Dependencies > Build Customizations…, then select the CUDA Toolkit version you would like to target. Jan 30, 2023 · CUDA Toolkit のバージョン NVIDIA Driver. You can find these details in System Requirements section of TensorFlow install page. 2) will work with this GPU. CUDA Minor Version Compatibility* CUDA Toolkit Linux x86_64 Driver Version Linux AArch64 Driver Version Windows x86_64 Driver Version CUDA 12. The guide for using NVIDIA CUDA on Windows Subsystem for Linux. If that doesn't work, you need to install drivers for nVidia graphics card first. 1 (seen https&hellip; Aug 29, 2024 · Release Notes. I downloaded and installed this as CUDA toolkit. _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). CUDA 11. 5 Component Versions ; Component Name. This post will show the compatibility table with references to official pages. 0 Nov 2, 2022 · I'm trying to use my GPU as compute engine with Pytorch. 03 CUDA Version: 11. 7, 12. TheNVIDIA®CUDA Jul 31, 2018 · I had installed CUDA 10. 2 and cuDNN 8. Jul 1, 2024 · Release Notes. 6. For best performance, the recommended configuration for GPUs Volta or later is cuDNN 9. If you are on a Linux distribution that may use an older version of GCC toolchain as default than what is listed above, it is recommended to upgrade to a newer toolchain CUDA 11. x may have issues when linking against 12. 1 GPU, which means I can't install a CUDA toolkit more recent than CUDA 8. 3. , CUDA Version: 12. Oct 3, 2022 · For more information on CUDA compatibility, including CUDA Forward Compatible Upgrade and CUDA Enhanced Compatibility, visit https://docs. 2). 4 (February 2022), Versioned Online Documentation CUDA Toolkit 11. The value it returns implies your drivers are out of date. 4, the table below indicates the versions: Table 1. 16. 0, and is cheaper. 4 as follows. ) CUDA® Toolkit 12. 7であることが分かりました。 cuDNNのバージョンを知るには. CUDA Features Archive. CUDA C++ Core Compute Libraries Jan 19, 2018 · I’m having trouble installing CUDA for my setup due to a driver compatibility issue with nvidia driver version 384. 74 RN-06722-001 _v11. Look up which versions of python, tensorflow, and cuDNN works for your Cuda version here. 9. 2 and CUDA 11. x. And results: I bought a computer to work with CUDA but I can't run it. CUDA compatibility allows customers to access features from newer versions of CUDA without requiring a full NVIDIA driver update. 10 is compatible with CUDA 11. If I install the current v10. I assume this is a GeForce GTX 1650 Ti Mobile, which is based on the Turing architecture, with compute capability 7. This comprehensive guide will teach you how to verify CUDA toolkit and driver versions, understand compatibility requirements, and keep your system up-to-date. However minor version compatibility should be a May 23, 2017 · I plan to use cuDNN on Linux: how to know which cuDNN version I need? Should I always use the most recent one? E. Resources. Users will benefit from a faster CUDA runtime! Download CUDA Toolkit 11. Learn more Explore Teams. CUDA 12. The CUDA Toolkit contains CUDA libraries and tools for compilation. x or Later, to ensure that nvcc will generate cubin files for all recent GPU architectures as well as a PTX version for forward compatibility with future GPU architectures, specify the appropriate -gencode= parameters on the nvcc command line as shown in the examples below. 0. 2 may not be fully compatible with RTX 4090, but is worth to take a try. 1 also introduces library optimizations, and CUDA graph enhancements, as well as updates to OS and host compiler support. js TensorFlow Lite TFX LIBRARIES TensorFlow. BTW I use Anaconda with VScode. nvidia-smi says I have cuda version 10. You can use following configurations (This worked for me - as of 9/10). For the host GPU device, GPU Coder has been tested with cuDNN v8. To install PyTorch (2. 1 For additional insights on CUDA for this these platforms, check out our blogs and on-demand GTC sessions below: In computing, CUDA (originally Compute Unified Device Architecture) is a proprietary [1] 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, an approach called general-purpose computing on GPUs (). 7 . For a complete list of supported drivers, see the CUDA Application Compatibility topic. Thrust. This version of Nsight Compute adds a GPU and Memory Workload Distribution section to help users understand the balance of work across SMs and the memory system. My cluster machine, for which I do not have admin right to install something different, has CUDA 12. 2. I took a look into my system, I currently have an NVIDIA GTX1650 that contains CUDA v-11, yet I see that hasn’t been installed. x86_64, arm64-sbsa, aarch64-jetson CUDACompatibility,Releaser555 CUDACompatibility CUDACompatibilitydescribestheuseofnewCUDAtoolkitcomponentsonsystemswitholderbase installations. Although each version of the CUDA Toolkit releases ships both CUDA Runtime library and CUDA Driver library that are compatible with each other, they can come from different sources and be installed separately. 5 devices; the R495 driver in CUDA 11. x toolkit, will there be conflicts with the 10. so, I am speculating it as the CUDA version incompatibility Sep 8, 2023 · To install PyTorch using pip or conda, it's not mandatory to have an nvcc (CUDA runtime toolkit) locally installed in your system; you just need a CUDA-compatible device. 1 and CUDNN 7. Aug 29, 2024 · When using CUDA Toolkit 11. 12. 3, the table below indicates the versions: Jan 2, 2021 · Now available on Stack Overflow for Teams! AI features where you work: search, IDE, and chat. 2 Update 1 Component Versions ; Component Name. Jul 30, 2020 · However, regardless of how you install pytorch, if you install a binary package (e. 2\extras\CUPTI\lib64 . 39 (Windows) as indicated, minor version compatibility is possible across the CUDA 11. However, the only CUDA 12 version seems to be 12. WSL or Windows Subsystem for Linux is a Windows feature that enables users to run native Linux applications, containers and command-line tools directly on Windows 11 and later OS builds. Get the latest feature updates to NVIDIA's compute stack, including compatibility support for NVIDIA Open GPU Kernel Modules and lazy loading support. 4. CUDA C++ Core Compute Libraries Sep 29, 2021 · All 8-series family of GPUs from NVIDIA or later support CUDA. 0 and higher. Dec 12, 2022 · For more information, see CUDA Compatibility. 0 through CUDA compatibility platform. Dec 24, 2021 · In other answers for example in this one Nvidia-smi shows CUDA version, but CUDA is not installed there is CUDA version next to the Driver version. More details on CUDA compatibility and deployment will be published in a future Table 1. EULA. nvidia. x86_64, arm64-sbsa, aarch64-jetson Oct 11, 2023 · hi everyone, I am pretty new at using pytorch. May 5, 2024 · OS compatibility: AlmaLinux $ man nvcc $ man nvidia-smi Do check the NVIDIA developer website to grab the latest version of CUDA toolkit and read documentations. 1 refers to a specific release of PyTorch. Minor version compatibility continues into CUDA 12. html. 2,10. 0」ということが分かります。 Use GPU Coder to generate optimized CUDA code from MATLAB code for deep learning, embedded vision, and autonomous systems. 0 pytorch-cuda=12. Howveer I was curious if CUDA Toolkit 7 supports this card. 7. x CUDA 11. 上述の「Table 1. NVIDIA CUDA deep neural network library (cuDNN) for NVIDIA GPUs. 03 Driver Version: 460. I know from the past that supporting a new version of Visual Studio is a big thing and takes a lot of time, but it would be great if you share something with the community. html Aug 15, 2024 · Version compatibility; Introduction Tutorials Guide Learn ML TensorFlow (v2. See Forward Compatibility for GPU Devices. Aug 29, 2024 · Release Notes. 0 through 11. 0 or later toolkit. With CUDA Feb 24, 2024 · If you look at this page, there are commands how to install a variety of pytorch versions given the CUDA version. From CUDA 11 onwards, applications compiled with a CUDA Toolkit release from within a CUDA major release family can run, with limited feature-set, on systems having at least the minimum required driver version as indicated below. This driver branch supports CUDA 11. 02 (Linux) / 452. x, but I’ve had problems with the corresponding version of the toolkit. Set up and Dec 9, 2021 · Guys, I mean from Nvidia, That isn’t very pleasant. , one created using the cudaStreamNonBlocking flag of the CUDA Runtime API or the CU_STREAM_NON_BLOCKING flag of the CUDA Driver API). 2 or Earlier), or both. 1 with CUDA 11. Starting with CUDA 11, the various components in the toolkit are versioned independently. CUDA Toolkit のバージョンとドライバのバージョンの互換性は以下にあった。 これをみると上のバージョンの CUDA Toolkit を使うほど、必要なドライバのバージョンも上がっていく傾向にあることがわかる。 CUDA 11. In my development environment with NVIDIA RTX 2070 GPU I have following multiple configurations in my system. GPU, CUDA Toolkit, and CUDA Driver Requirements The NVIDIA® CUDA® Toolkit provides a development environment for creating high-performance, GPU-accelerated applications. Currently, I have been trying to understand the concepts of using CUDA for performing better loading data and increasing speed for training models. 0 with CUDA 12. 2) and you cannot use any other version of CUDA, regardless of how or where it is installed, to satisfy that dependency. Mar 5, 2024 · Would using a CUDA version like 11. 10. 0 which resolves an issue in the cuFFT library that can lead to incorrect results for certain inputs sizes less than or equal to 1920 in any dimension when cufftSetStream() is passed a non-blocking stream (e. 1 debuts with CUDA Toolkit 12. 32. To download the CUDA Toolkit, see CUDA Toolkit Archive (NVIDIA). Oct 4, 2022 · NVIDIA JetPack provides a full development environment for hardware-accelerated AI-at-the-edge on Jetson platforms. Version 2024. x are compatible with Turing as long as they are built to include kernels in either Volta-native cubin format (see Compatibility between Volta and Turing) or PTX format (see Applications Using CUDA Toolkit 8. Nov 6, 2022 · If you try to build it on Linux you need to install a compatibility version of Cuda and CuDNN Compatibility Matrix; Last I read this question multiple of times, you still can download target versions of CuDA archived CuDA and CuDNN archive link; That is because they question then screenshot added see TF2. For more information, see CUDA Compatibility and Upgrades and NVIDIA CUDA and Drivers Support. The other half is the Compute Capability. x version; ONNX Runtime built with CUDA 12. 11 and WSL2. Introduction to CUDA CUDA (Compute Unified Device Architecture) is a parallel programming platform created by NVIDIA in 2007. However, you should check which version of CUDA Toolkit you choose for download and installation to ensure compatibility with Tensorflow (looking Mar 6, 2024 · NVIDIA Nsight Compute provides detailed profiling and analysis for CUDA kernels. 5. (See Application Compatibility for details. But I found that RTX 4090 also work well under CUDA 11. Because of this i downloaded pytorch for CUDA 12. 0 to the most recent one (11. Often, the latest CUDA version is better. With it, you can develop, optimize, and deploy your applications on GPU-accelerated embedded systems, desktop workstations, enterprise data centers, cloud-based platforms, and supercomputers. 0 related to my answers Dec 6, 2019 · Is there an easy way to determine whether a new version of the CUDA toolkit will be compatible with an installed CUDA driver? Specifically, the driver is v10. 2 (February 2022), Versioned Online Documentation CUDA Toolkit 11. Version 11. You signed out in another tab or window. 1 installed and only want to upgrade to CUDA 10. Back to the question, CUDA 11. CUDA C++ Core Compute Libraries. and downloaded cudnn top one: There is no selection for 12. I tried to modify one of the lines like: conda install pytorch==2. 2 cause any issues? if you wish to use a newer CUDA toolkit. Jul 17, 2024 · Ensuring GPU and CUDA Toolkit Compatibility. CUDA Documentation/Release Notes; MacOS Tools; Training; Archive of Previous CUDA Releases; FAQ; Open Source Packages Apr 10, 2023 · Although in the official CUDA toolkit documentation RTX 40 series support starts with CUDA 11. 8 are compatible with any CUDA 11. x are compatible with any CUDA 12. x-v12. However, it is able to return accurate prediction results for the CPU-trained model. Oct 30, 2023 · Understanding your current CUDA version is crucial for developing performant GPU-accelerated software. Installation Methods (Choose one): Using conda (recommended): May 21, 2024 · You signed in with another tab or window. To install PyTorch via pip, and do not have a CUDA-capable system or do not require CUDA, in the above selector, choose OS: Windows, Package: Pip and CUDA: None. 5 installer does not. 1 for GPU support on Windows 7 (64 bit) or later (with C++ redistributable). For instance, my laptop has an nVidia CUDA 2. 7 are compatible with the NVIDIA Ada GPU architecture as long as they are built to include kernels in Ampere-native cubin (see Compatibility between Ampere and Ada) or PTX format (see Applications Built Using CUDA Toolkit 10. NVIDIA states that each version of CUDA toolkit requires certain minimum NVIDIA display Aug 1, 2024 · 1. Use the legacy kernel module flavor. 3). 1,10. : Tensorflow-gpu == 1. The CUDA Toolkit (free) can be downloaded from the Nvidia website here. 1 Component Versions ; Component Name. Supported NVIDIA Hardware and CUDA Version」からcuDNNのバージョンは「8. 0, as shown in Fig 6. 4 would be the last PyTorch version supporting CUDA9. 2,11. 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. Feb 1, 2011 · Table 1 CUDA 12. NVIDIA GPU Accelerated Computing on WSL 2 . Supported Platforms. 76」に対応するCUDA ToolkitのバージョンはCUDA 11. 0 or Earlier) or both. TensorFlow > 2. Aug 1, 2024 · The following sections highlight the compatibility of NVIDIA cuDNN versions with the various supported NVIDIA CUDA Toolkit, CUDA driver, and NVIDIA hardware versions. Dec 8, 2018 · CUDA version upgrade itself can be a misleading term because since CUDA 8. 8 installed in my local machine, but Pytorch can't recognize my GPU. CUDA C++ Core Compute Libraries Dec 11, 2020 · I think 1. x86_64, arm64-sbsa, aarch64-jetson CUDA Toolkit 11. x Jul 27, 2024 · Version 1. 0 of cuda for PyTorch 1. then added the 2 folders to the path: C:\Program Files\NVIDIA GPU Computing Toolkit\CUDA\v12. CUDA Toolkit. Table 1. 10. 0 was released with an earlier driver version, but by upgrading to Tesla Recommended Drivers 450. Note that ONNX Runtime Training is aligned with PyTorch CUDA versions; refer to the Optimize Training tab on onnxruntime. 1 (November 2021), Versioned Online Documentation CUDA Toolkit 11. 6 by mistake. You switched accounts on another tab or window. Apr 16, 2021 · CUDA Components. Column descriptions: Min CC = minimum compute capability that can be specified to nvcc (for that toolkit version) Deprecated CC = If you specify this CC, you will get a deprecation message, but compile should still proceed. Install the Cuda Toolkit for your Cuda version. 0 torchaudio==2. 2 Component Versions ; Component Name. In particular, if your headers are located in path /usr/local/cuda/include, then you Sep 2, 2022 · If you want to generate CUDA® kernel objects from CU code or use GPU Coder™ to compile CUDA compatible source code, libraries, and executables, you must install a CUDA Toolkit. 2. Note that minor version compatibility will still be maintained. 0 is a new major release, the compatibility guarantees are reset. I want to download Pytorch but I am not sure which CUDA version should I download. 5 still "supports" cc3. CUDA Toolkit: A collection of libraries, compilers, and tools developed by NVIDIA for programming GPUs (Graphics Processing Units). Bin folder added to path. At the original time of writing this tutorial, the default version of CUDA Toolkit offered is version 10. However, as 12. ai for supported versions. 04. GPU Requirements Release 21. But let’s have a simple scenario where we already have CUDA 9. 0 For GCC and Clang, the preceding table indicates the minimum version and the latest version supported. jwnft qxepa qcnx suxbet ovvd jcolosq qdr hjrl bsn qvwlq