…Models with vLLM and ZenTorch For quantizing LLMs with TorchAO and executing the quantized model with vLLM-ZenTorch, please refer the section 2.6 of ZenDNN 5.2.1 user manual . Performance…
…Audio and vocal synthesis models are particularly demanding. They require GPUs with sufficient memory to support large model architectures and batch sizes, as well as an environment that allows engineers to retrain…
…Hugging Face, a leading open-source AI platform with more than 500,000 models and datasets available, announced a strategic collaboration with AMD to optimize models for AMD platforms, driving maximum performance…
…In Performance mode, FSR Upscaling renders 4K frames in approximately 1.3ms on an AMD Radeon RX 9070 XT.[1] The FSR Upscaling 4.1 update brings inference updates for sharper images…
…computing efficiency, with the updated “Zen 3+” CPU core and AMD RDNA™ 2 game-ready gra… AMD ROCm™ 5.7 Update: Unlocking Greater HPC and AI Compute Performance Discover AMD's ROCm…
…Hand-writing a high-performance kernel for a new operator, dtype, model shape, or GPU generation still requires scarce expertise and repeated measurement on real hardware. A kernel agent turns this expert…
…Modular AI Modular and AMD collaborate to bring high-performance AI execution to AMD Instinct™ GPUs. Through deep integration of the Modular Platform - with MAX, its high performance AI Serving & Modelling Framework…
…Also learn how to run a particular model, CorrDiff, on AMD GPUs. May 19, 2026 New AMD EPYC™ 8005 Server CPUs: Big Performance, Low Power New AMD EPYC 8005 Server CPUs deliver…
…While GPUs remain essential for large-scale AI training and inference and provide the accelerator performance required for model computation, they’re only one part of the system in agentic environments. Deploying…
…In our testing on non-cherry-picked models, the combination of vLLM and ZenTorch delivered up to 239% higher performance compared to running native vLLM on a standard CPU setup. Beyond the…