Running local LLMs on consumer AMD GPUs often comes with two pain points: configuring backend overrides (HSA_OVERRIDE_GFX_VERSION) and figuring out whether Vulkan or HIP/ROCm gives better token throughput on your setup.
I created two open-source tools to solve this:
1. ROCmFix Repo: github.com/xanpavle/rocmfix
Zero-dependency Python script runnable via single-line terminal command.
Detects GPU PCI IDs directly (Windows Registry / Linux lspci) to map the correct HSA_OVERRIDE_GFX_VERSION.
Automatically updates shell profiles (PowerShell, CMD, Bash, Zsh, Fish) and includes an undo command and driver diagnostic runner (rocmfix doctor).
2. InferBench Repo: github.com/xanpavle/inferbench
Automated benchmarking tool for local LLM servers (Ollama, LM Studio).
Rigorously compares Vulkan vs HIP/ROCm performance with warm-up passes, median of N runs, and cold-start VRAM unloading between test cycles.
Both projects are MIT-licensed. Check them out and let me know your benchmarking results!
betterdeadthanreddit@lemmy.world 11 hours ago
lemmy.world/post/49151085
call_me_xale@lemmy.zip 11 hours ago
Please tag AI-related posts.
betterdeadthanreddit@lemmy.world 11 hours ago
And, more generally, read sidebars.