ComfyUI DirectML AMD

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

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

bash

# 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

bash

# 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)

Model	Resolution	Steps	Time	Quality
SDXL Turbo	1024²	1	30-60s	Good
SDXL Base	1024²	20	5-10 min	Very Good
Juggernaut XL	1024²	20	5-10 min	Excellent
Flux.1 schnell	1024²	4	3-5 min	Best

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:

json

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

References

• ComfyUI Official
• DirectML Docs
• AMD ROCm

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