Boost AI Performance with GGUF Quantization on AMD Instinct Mi60! Speed Tests with ROCm 6.4

In this tutorial, we dive deep into configuring ComfyUI with GGUF Quantization running ROCm 6.4 on a Linux system using the powerful AMD Instinct Mi60 32GB HBM2 GPU. This screencast follows up on our earlier tutorial where we reinstalled ComfyUI on Fedora 43 with unsupported ROCm 6.4 (read that blog post here: https://www.ojambo.com/reinstall-comfyui-and-rocm-6-4-for-unsupported-amd-instinct-mi60-gpu).

The main focus of this video is to benchmark speed tests for FP32, FP16, Q8, and Q4_K_M, demonstrating how each quantization method affects performance and output quality when using stable-diffusion.cpp. Whether you're looking to optimize your system for AI image generation or just curious about how these different formats compare, this tutorial will give you practical insights on improving your setup.

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