ComfyUI DirectML AMD

Sets up and optimizes ComfyUI on AMD GPUs with DirectML on Windows, including fixes, compatible models, benchmarks, and automated configuration tools.

Audits

Pass

Install

openclaw skills install comfyui-directml-amd

ComfyUI DirectML AMD Skill 🎨

Description

Skill for setting up and optimizing ComfyUI on AMD GPUs under Windows using DirectML. Provides guides, fixes, and ready-to-use configurations for local image, music, and video generation.

When to Use This Skill

Use this skill when:

  • You have an AMD GPU (RX 7000/6000/5000 series) and want to run ComfyUI
  • You're getting errors with torch_directml module
  • You need to fix model_patcher.py for DirectML compatibility
  • You want to know which models are compatible with your VRAM
  • You're looking for AMD GPU performance benchmarks

Installation

# 1. Install skill
clawhub install comfyui-directml-amd

# 2. Navigate to directory
cd C:\ComfyUI

# 3. Create Python 3.12 environment (if not already done)
uv venv --python 3.12

# 4. Install DirectML
.venv\Scripts\python.exe -m pip install torch-directml --force-reinstall

# 5. Apply fixes (automated by this skill)
python apply-directml-fixes.py

# 6. Start ComfyUI
.venv\Scripts\python.exe main.py --directml --port 8188

Tools

apply-directml-fixes.py

Automatically applies all necessary DirectML fixes:

  • Fixes comfy\model_patcher.py (2 locations)
  • Creates backups of original files
  • Verifies functionality after application

download-models.ps1

Downloads recommended models:

  • SDXL Turbo (6.6 GB)
  • SDXL Base 1.0 (6.0 GB)
  • Juggernaut XL v9 (6.6 GB)
  • Optional: Flux.1, ACE-Step, Wan 2.1

benchmark.py

Tests performance with different models and settings:

  • Measures generation time
  • Monitors VRAM usage
  • Compares with CUDA references

Configuration

Minimum Requirements

  • GPU: AMD Radeon with 8GB+ VRAM
  • OS: Windows 10/11 64-bit
  • Python: 3.12 (DirectML has no wheels for 3.13+)
  • VRAM: 8GB minimum, 12GB+ recommended

Recommended Settings

# For 16GB VRAM (RX 7900 GRE/XTX)
python main.py --directml --port 8188 --max-memory 16384

# For 12GB VRAM (RX 7800/6800)
python main.py --directml --port 8188 --max-memory 12288 --use-split-cross-attention

# For 8GB VRAM (RX 7600/6600)
python main.py --directml --port 8188 --max-memory 8192 --lowvram

Performance Benchmarks (RX 7900 GRE 16GB)

ModelResolutionStepsTimeQuality
SDXL Turbo1024²130-60sGood
SDXL Base1024²205-10 minVery Good
Juggernaut XL1024²205-10 minExcellent
Flux.1 schnell1024²43-5 minBest

Note: DirectML is ~2-3x slower than CUDA on comparable NVIDIA GPU, but fully functional!

Common Errors and Solutions

ModuleNotFoundError: torch_directml

Solution: Python 3.14 is too new → create .venv with Python 3.12

SyntaxError in model_patcher.py

Solution: Skill automatically applies fixes, or use apply-directml-fixes.py

Port already in use

Solution: ComfyUI already running → kill process or use different port

Out of Memory

Solution: Reduce resolution, use FP8 models, or add --lowvram flag

ComfyUI crash during generation

Solution: DirectML is unstable → restart server, try fewer steps

OpenClaw Integration

Skill is compatible with OpenClaw comfy plugin:

{
  "plugins": {
    "entries": {
      "comfy": {
        "enabled": true,
        "config": {
          "baseUrl": "http://127.0.0.1:8188",
          "image": {
            "workflowPath": "comfy-workflows/image-generation.json"
          }
        }
      }
    }
  }
}

References

Author

Klepeto 🦞 (vilda)
Tested on: AMD Radeon RX 7900 GRE 16GB, Windows 11

License

MIT-0 - Free to use, modify, and redistribute without attribution.

Changelog

1.0.0 (2026-05-07)

  • Initial release
  • Complete AMD DirectML setup guide
  • Automatic model_patcher.py fixes
  • Benchmark scripts
  • Model download scripts
  • OpenClaw integration