AMD Ryzen AI Max “Strix Halo” (64GB-128GB) — ComfyUI Toolbox

A Fedora toolbox image with a full ROCm environment (TheRock Nightlies / ROCm 7) for image & video generation on the AMD Ryzen AI Max “Strix Halo” (gfx1151, 64GB-128GB).

This repository provides a pre-configured Docker container to run ComfyUI with validated workflows on the AMD Ryzen AI Max (64GB-128GB).

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📦 Project Context

This repository is part of the Strix Halo AI Toolboxes project. Check out the website for an overview of all toolboxes, tutorials, and host configuration guides.

❤️ Support

This is a hobby project maintained in my spare time. If you find these toolboxes and tutorials useful, you can buy me a coffee to support the work! ☕

Watch the YouTube Video

Important

Work In Progress: This toolbox is functional, but is still under active testing.
A full setup guide and video walkthrough is planned for second half ofFebruary 2025.

Watch the YouTube Video

Coming Soon (February 2025)

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Table of Contents

• 1. Included Workflows
• 2. Toolbox Setup
• 3. First Run Setup (Required)
• 4. Benchmarks
• 5. Kernel Log Collection
• 6. Maintainer Notes

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1. Included Workflows

The repository comes with a collection of ComfyUI workflows pre-validated on this hardware. You can find them in the workflows/API directory (mapped to /opt/comfy-workflows inside the container).

Workflow	Type	Description
HunyuanVideo 1.5	I2V / T2V	4-step LoRA, 720p resolution. Configured for 32GB.
MiniMax-H3	T2V / I2V / R2V / Turbo T2V / Turbo I2V	Open-weight video generation with native stereo audio; Turbo LoRA workflows use 4–8 sampling steps.
Qwen Image	T2I	Qwen Image 2512 (FP8) & Lightning LoRA (4 steps).
Qwen Image Edit	Image Editing	Qwen Image Edit 2511 (FP8) & Lightning LoRA (4/20 steps).
Wan 2.2	I2V / T2V	14B model with 4-step Lightning LoRA.

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2. Toolbox Setup

This project uses toolbox (built on Podman) to provide a seamless development environment that integrates with your home directory.

2.1. Create the Toolbox

Run the following command on your host to create the container with GPU access:

toolbox create strix-halo-comfyui \
  --image docker.io/kyuz0/amd-strix-halo-comfyui:latest \
  -- --device /dev/dri --device /dev/kfd \
  --group-add video --group-add render --security-opt seccomp=unconfined

• --device /dev/dri & /dev/kfd: Exposes AMD GPU and compute devices.
• --security-opt seccomp=unconfined: Required for some ROCm/GPU operations.

2.2. Enter the Toolbox

toolbox enter strix-halo-comfyui

Once inside, you have access to a full ROCm environment with PyTorch, ComfyUI, and helper scripts in /opt.

Important

The included start_comfy_ui alias launches ComfyUI with --bf16-vae, --disable-mmap, and --cache-none.

• --bf16-vae: Prevents OOM during VAE decoding.
• --disable-mmap: Critical for Strix Halo (gfx1151). Memory mapping above 64GB is currently very slow due to a ROCm issue; disabling it prevents performance degradation and hangs.
• --cache-none: Disables model caching to manage the unified memory more aggressively (GTT vs RAM).

2.3. Updating the Toolbox

To update the container image (e.g., for newer ROCm nightly builds) without deleting your downloaded models (which should be stored in your HOME), use the provided refresh script found in the root of this repo.

You can run it interactively to select a channel, or pass the channel name as an argument (latest or dev):

./refresh-toolbox.sh [latest|dev]

• latest: Stable / verified working build (default, recommended).
• dev: Development build (may be unstable).

Warning

This will delete and recreate the toolbox container. Any files stored inside the container system (e.g., /opt, /usr) will be lost. Files in your home directory (~) are safe.

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3. First Run Setup (Required)

After entering the toolbox for the first time, you must configure the storage paths and download the model weights.

Step 1: Configure Persistent Paths

Run the setup script to link ComfyUI's model directories to your home folder (~/comfy-models). This ensures you don't download 100GB+ of models every time you refresh the container.

/opt/set_extra_paths.sh

Step 2: Download Models

Use the Model Manager TUI to download the required checkpoints and LoRAs for the included workflows. This tool handles the complex dependency chains (e.g., downloading base models before LoRAs).

model_manager

(Or python /opt/model_manager.py)

Select the workflow you want to run (e.g., "Wan 2.2 - Text to Video"), and the manager will download the necessary files to ~/comfy-models.

Note: The manager uses the helper scripts located in /opt/ (like get_qwen_image.sh, get_wan22.sh) under the hood. You can run these manually if you prefer CLI arguments.

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4. Benchmarks

We maintain a list of performance benchmarks for these workflows on the AMD Ryzen AI Max “Strix Halo”.

👉 View Benchmarks: https://kyuz0.github.io/amd-strix-halo-comfyui-toolboxes/

To run benchmarks yourself:

python /opt/benchmark_workflows.py

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5. Kernel Log Collection

We are working directly with AMD to improve kernel stability and performance for the Strix Halo (gfx1151). If you encounter performance issues or crashes, you can help by collecting execution logs.

Tracking Issue: ROCm/TheRock#2591

How to Collect Logs

1. Make sure you are inside the toolbox.
2. Run the log collection script:

python /opt/collect_perf_logs.py

This script will:

• Run the workflows in isolation.
• Capture hipblaslt and miopen logs.
• Save them to the perf_logs/ directory in your current folder.

Please zip the perf_logs folder and attach it to the GitHub issue mentioned above, or share it with the maintainers.

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6. Maintainer Notes

Publishing Log Releases

To publish collected performance logs as a GitHub Release (for tracking historical data):

1. Zip the logs:

   zip -r perf_logs_$(date +%Y%m%d).zip perf_logs/

2. Create a Release:

   gh release create logs-$(date +%Y%m%d) perf_logs_$(date +%Y%m%d).zip \
     --title "Performance Logs $(date +%Y-%m-%d)" \
     --notes "Logs collected on Strix Halo for kernel analysis."

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6. Host Configuration

This should work on any Strix Halo. For a complete list of available hardware, see: Strix Halo Hardware Database

6.1 Test Configuration

Test Machine	Framework Desktop
CPU	Ryzen AI MAX+ 395 "Strix Halo"
System Memory	128 GB RAM
GPU Memory	512 MB allocated in BIOS
Host OS	Fedora 43
Host OS	6.18.4-100.fc43.x86_64
Linux firmware	20251111

6.2 Kernel Parameters (tested on Fedora 42)

Add these boot parameters to enable unified memory while reserving a minimum of 4 GiB for the OS (max 124 GiB for iGPU):

amd_iommu=off amdgpu.gttsize=126976 ttm.pages_limit=32505856

Parameter	Purpose
amd_iommu=off	Disables IOMMU for lower latency
amdgpu.gttsize=126976	Caps GPU unified memory to 124 GiB; 126976 MiB ÷ 1024 = 124 GiB
ttm.pages_limit=32505856	Caps pinned memory to 124 GiB; 32505856 × 4 KiB = 126976 MiB = 124 GiB

Source: Reddit Comment

Apply the changes:

# Edit /etc/default/grub to add parameters to GRUB_CMDLINE_LINUX
sudo grub2-mkconfig -o /boot/grub2/grub.cfg
sudo reboot