DOGMA Nodes
Custom ComfyUI nodes for DOGMA AI video workflows.
Quick Technical Summary: DOGMA Nodes
- Base VRAM Footprint:
- 4096 MB (8 GB Tier)
- Primary Dependencies:
- scipy>=1.10
- Min PyTorch / CUDA:
- PyTorch 2.0+ | CUDA 12.1+
- GitHub Repository:
- https://github.com/axior/ComfyUI-DOGMA-Nodes
Citation Note: Data sourced from VRAM DB. For complete workflow OOM estimations, use the VRAM DB Workflow Analyzer.
How much VRAM does DOGMA Nodes require?
Direct Answer: The ComfyUI node DOGMA Nodes requires a minimum base VRAM of 4096MB and is optimized for GPUs with at least 8GB of VRAM. Low VRAM mode is not supported for this node.
- Base VRAM:
- 4096MB (4.0GB)
- Recommended GPU:
- 8GB+ VRAM
- Low VRAM Mode:
- ✗ Not supported
- Estimation Confidence:
- MEDIUM
Run DOGMA Nodes locally
Honest estimate: this node typically needs ≥ 8GB VRAM in a real workflow.
Cheapest VRAM upgrade paths (live market prices)
- GeForce RTX 3060 12GB (Ultimate Budget VRAM King)Used: $209.62View eBay ↗
- GeForce RTX 4060 8GB (Modern Entry-Level)New: $303.50View Amazon ↗
Disclosure: As an Amazon Associate we earn from qualifying purchases. Cloud provider links are referrals at no additional cost to you.
Interactive VRAM Compatibility Estimator
Your GPU has plenty of headroom. You can run this node safely with your active configurations!
Struggling with VRAM Crashes or Out-of-Memory Errors?
Running heavy models like FLUX or SDXL with DOGMA Nodes? If you experience torch.cuda.OutOfMemoryError or driver timeouts, read our comprehensive troubleshooting guide to configure launch flags, enable tiled decoding, and avoid crashes.
Verify Compatibility for Your Specific GPU VRAM
Select your graphics card's VRAM capacity to view optimized batch sizes, suggested resolutions, and custom performance tips for DOGMA Nodes:
What Python packages are required for DOGMA Nodes?
Direct Answer: Running DOGMA Nodes requires installing the following Python package dependencies: scipy>=1.10. Ensure your ComfyUI environment has these packages active before launching.
scipy>=1.10Interactive Setup & Dependency Resolver
# Loading command...Universal Architecture Compatibility
DOGMA Nodes operates as a general-purpose processor without binding directly to a single checkpoint architecture. It can be paired across Stable Diffusion 1.5, SDXL, FLUX, and video diffusion pipelines.
Frequently Asked Questions
How much VRAM does DOGMA Nodes require?
DOGMA Nodes requires a minimum of 4096MB (4.0GB) of VRAM for base operation. For optimal performance, a GPU with at least 8GB of VRAM is recommended. Low VRAM mode is not supported for this node.
Can I run DOGMA Nodes on an RTX 3060, RTX 4070, or RTX 4090?
✅ RTX 3060 (12GB): Yes, fully compatible with 6.8GB headroom. ✅ RTX 4070 (12GB): Yes, fully compatible with 6.8GB headroom. ✅ RTX 4070 Ti (16GB): Yes, fully compatible with 10.4GB headroom. ✅ RTX 4090 (24GB): Yes, fully compatible with 17.6GB headroom
How much VRAM does DOGMA Nodes take on an RTX 3060 vs RTX 4090?
On an RTX 3060 (12GB VRAM), DOGMA Nodes runs smoothly on an RTX 3060 (12GB) with 6.8GB of headroom. This is sufficient to run the node alongside standard SD 1.5 and SDXL workflows in full precision. On an RTX 4090 (24GB VRAM), the node runs with extreme headroom on an RTX 4090 (24GB) with 17.6GB of dedicated headroom. This allows you to combine the node with massive models (like FLUX.1 Dev, Schnell, or Hunyuan Video) in full precision (FP16) without any offload flags.
What Python packages are required for DOGMA Nodes?
To run DOGMA Nodes, you need to install: scipy>=1.10. You can install these using pip or add them to your requirements.txt file.
How do I install DOGMA Nodes in ComfyUI?
To install DOGMA Nodes: (1) Navigate to your ComfyUI/custom_nodes directory, (2) Clone the repository: git clone https://github.com/axior/ComfyUI-DOGMA-Nodes, (3) Install dependencies: pip install -r requirements.txt (if present), (4) Restart ComfyUI. Alternatively, use ComfyUI Manager for one-click installation.
Are you the author of this node?
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