OpenH3-IR
Four nodes for MiniMax H3: type a plain prompt, name your pictures, clips and sounds with @, lock exact dialogue, and get the structured brief H3 wants in its own published format, checked before it runs. Nothing to start beside ComfyUI. Needs any OpenAI-compatible model you run or have access to.
Quick Technical Summary: OpenH3-IR
- Base VRAM Footprint:
- 1536 MB (6 GB Tier)
- Primary Dependencies:
- open-h3-ir>=0.4.0
- Min PyTorch / CUDA:
- PyTorch 2.0+ | CUDA 12.1+
- GitHub Repository:
- https://github.com/ruashots/ComfyUI-OpenH3-IR
Citation Note: Data sourced from VRAM DB. For complete workflow OOM estimations, use the VRAM DB Workflow Analyzer.
How much VRAM does OpenH3-IR require?
Direct Answer: The ComfyUI node OpenH3-IR requires a minimum base VRAM of 1536MB and is optimized for GPUs with at least 6GB of VRAM. Low VRAM mode is fully supported for resource-constrained setups.
- Base VRAM:
- 1536MB (1.5GB)
- Recommended GPU:
- 6GB+ VRAM
- Low VRAM Mode:
- ✓ Supported
- Estimation Confidence:
- MEDIUM
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 OpenH3-IR? 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 OpenH3-IR:
What Python packages are required for OpenH3-IR?
Direct Answer: Running OpenH3-IR requires installing the following Python package dependencies: open-h3-ir>=0.4.0. Ensure your ComfyUI environment has these packages active before launching.
open-h3-ir>=0.4.0Interactive Setup & Dependency Resolver
# Loading command...Universal Architecture Compatibility
OpenH3-IR 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 OpenH3-IR require?
OpenH3-IR requires a minimum of 1536MB (1.5GB) of VRAM for base operation. For optimal performance, a GPU with at least 6GB of VRAM is recommended. This node supports low VRAM mode for resource-constrained setups.
Can I run OpenH3-IR on an RTX 3060, RTX 4070, or RTX 4090?
✅ RTX 3060 (12GB): Yes, fully compatible with 9.3GB headroom. ✅ RTX 4070 (12GB): Yes, fully compatible with 9.3GB headroom. ✅ RTX 4070 Ti (16GB): Yes, fully compatible with 12.9GB headroom. ✅ RTX 4090 (24GB): Yes, fully compatible with 20.1GB headroom
How much VRAM does OpenH3-IR take on an RTX 3060 vs RTX 4090?
On an RTX 3060 (12GB VRAM), OpenH3-IR runs smoothly on an RTX 3060 (12GB) with 9.3GB 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 20.1GB 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 OpenH3-IR?
To run OpenH3-IR, you need to install: open-h3-ir>=0.4.0. You can install these using pip or add them to your requirements.txt file.
How can I reduce VRAM usage when running OpenH3-IR?
OpenH3-IR supports low VRAM mode. To reduce memory usage: (1) Enable --lowvram or --medvram flags in ComfyUI, (2) Reduce batch size to 1, (3) Use fp16 or fp8 precision if supported, (4) Close other GPU applications.
How do I install OpenH3-IR in ComfyUI?
To install OpenH3-IR: (1) Navigate to your ComfyUI/custom_nodes directory, (2) Clone the repository: git clone https://github.com/ruashots/ComfyUI-OpenH3-IR, (3) Install dependencies: pip install -r requirements.txt (if present), (4) Restart ComfyUI. Alternatively, use ComfyUI Manager for one-click installation.
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