AMD NPU runs LLaDA-8B-Instruct diffusion model efficiently
Diffusion language models are mostly benchmarked on GPUs, so this shows a practical path to running one locally on consumer NPUs where power budgets matter. The measured 8.9x energy gain over CPU INT4 is the kind of number edge-deployment engineers can use when sizing on-device inference. Anyone working on AMD Ryzen AI hardware or quantized LLM deployment should watch for the full poster at PyTorchCon North America 2026.
