ONNX Radeon™ GPUs (9000 select 7000 Series) Windows® PyTorch Ryzen™ APUs (AI Max 300 Series，。
facilitating the development， and introduces support for Ryzen™ APUs， Windows® PyTorch Your Local。
featuring up to 48GB of VRAM， you can now harness the full potential of high-end AMD Radeon™ GPUs and Ryzen™ APUs for your AI workflows on both Linux® and Windows®. ROCm™ 7.2.1 supports the latest Radeon™ 9000 Series (RDNA™ 4) and select 7000 Series (RDNA™ 3) GPUs， CAD， ROCm™ gives you the freedom to inspect， enabling cost-effective， JAX， scientific computing， select AI 400 Series select AI 300 Series) Linux®， Private AI Powerhouse Modern AI models demand significant computational power and memory. A local workstation equipped with a Radeon™ GPU。
and deployment of AI workloads， and other applications. As a primarily open-source ecosystem， GPU-accelerated HPC， Use ROCm on Radeon and Ryzen Contents Use ROCm on Radeon and Ryzen Unlock Local AI Development on Your AMD Hardware Transform your AMD-powered system into a powerful and private machine learning workstation. With the latest ROCm™ software stack， testing， offers a secure and economical alternative to relying solely on cloud-based solutions. Furthermore， TensorFlow， backed by a collaborative community of developers. ROCm™ Key Capabilities Frequent ROCm™ releases introduce major platform expansions and key software improvements. New Platform Updates : Established Features Framework Support (Radeon on Linux) : Get Started Ready to build? Find all the resources you need at the links below. next Prerequisites to use ROCm on Radeon desktop GPUs for machine learning development ， allowing you to develop applications locally and deploy them at scale with confidence. This maximizes GPU hardware investments， expanded support to Ryzen™ APUs， and tailor the software stack to your specific needs。
with up to 128GB of shared memory， local development and inference for researchers and engineers using Pytorch. Expanded Platform Support Quickly see what’s supported on your system. ROCm™ 7.2.1 focuses on bringing PyTorch support to new platforms while maintaining robust support on our established Linux platform for Radeon GPUs. Hardware Operating System Supported Frameworks Radeon™ GPUs (9000 select 7000 Series) Linux® PyTorch， allow even laptop users to develop ML workflows securely and efficiently. Leadership in Open-Source GPU Programming ROCm is the leading open-source software foundation for GPU programming . The same ROCm™ stack that powers your desktop development on RDNA™ architecture GPUs also supports AMD Instinct™ accelerators on CDNA™ architecture in the datacenter. This unified platform creates a seamless migration path， customize。