How I Configure the Ryzen AI Halo (Strix Halo) for 10-15% Faster Local Inference

A walkthrough of the Ryzen AI Halo, AMD's new compact platform built around the Ryzen AI Max+ 395 (Strix Halo) APU with 128GB of LPDDR5X unified memory. The focus is on how I configure it as a headless AI server to maximise memory availability and inference throughput. The video covers the out-of-the-box Linux experience, the bundled software stack (llama.cpp, vLLM, ComfyUI, Lemonade, LM Studio), and AMD's AI Playbooks project. It then goes through the specific tuning steps: switching to multi-user mode to free desktop memory, setting GTT allocation to 124GB, enabling performance mode via tuned, and disabling IOMMU in the BIOS to reduce memory access overhead on the shared unified memory pool. The result is a 10-15% improvement in prompt processing speed on some models. The benchmarks section shows before-and-after throughput numbers for this configuration. The final section demonstrates a coding agent workflow: SSHing into the headless Halo box from a primary machine and using the ds4 coding agent inside VSCode with llama.cpp endpoints. This video is sponsored by AMD. AMD AI Developer Program ---------------------------------------------- Join the AMD AI Developer Program for free cloud credits, expert access, and premium AI training - everything you need to build, optimize, and scale on AMD. Start building today: https://www.amd.com/en/developer/ai-d... Timestamps 00:00 | Introduction 01:16 | Out-of-the-Box Experience 02:16 | Hardware Specs 03:30 | Performance Optimizations 06:28 | Benchmarks 10:42 | Hands-on Coding Agent Demo 19:55 | Conclusion Links & Resources AMD Ryzen AI Halo: https://www.amd.com/en/products/proce... AMD AI Playbooks (forked): https://github.com/kyuz0/amd-playbooks Strix Halo Toolboxes & Guides: https://strix-halo-toolboxes.com Buy Me a Coffee: https://buymeacoffee.com/dcapitella