ComfyUI-TensorRT-Reforge
Building upon the excellent foundation of ComfyUI_TensorRT, this version focuses on full support for the Anima architecture and advanced TensorRT acceleration. It aims to push NVIDIA RTX™ GPU performance to its limits for the next generation of Stable Diffusion workflows.
VRAM Requirements
Direct Answer: The ComfyUI node ComfyUI-TensorRT-Reforge requires a minimum base VRAM of 128MB and is optimized for GPUs with at least 4GB of VRAM. Low VRAM mode is fully supported for resource-constrained setups.
- Base VRAM:
- 128MB (0.1GB)
- Recommended GPU:
- 4GB+ 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!
Deploy on High-Performance GPUs
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Deploy on Cloud GPUs
Need more VRAM to run ComfyUI with this node? Rent low-cost, high-performance cloud GPUs on RunPod instantly.
Python Dependencies
Direct Answer: Running ComfyUI-TensorRT-Reforge requires installing the following Python package dependencies: coloredlogs, flatbuffers, numpy, onnx>=1.18.0,<1.20.0, onnxruntime-gpu>=1.24.1,<1.27.0 # Use onnxruntime-gpu for TensorRT execution (1.27+ requires cu13), onnxscript, packaging, protobuf, sympy, tensorrt-cu12>=10.15.1,<11.0.0, tensorrt-cu12-bindings>=10.15.1,<11.0.0, tensorrt-cu12-libs>=10.15.1,<11.0.0. Ensure your ComfyUI environment has these packages active before launching.
coloredlogs
flatbuffers
numpy
onnx>=1.18.0,<1.20.0
onnxruntime-gpu>=1.24.1,<1.27.0 # Use onnxruntime-gpu for TensorRT execution (1.27+ requires cu13)
onnxscript
packaging
protobuf
sympy
tensorrt-cu12>=10.15.1,<11.0.0
tensorrt-cu12-bindings>=10.15.1,<11.0.0
tensorrt-cu12-libs>=10.15.1,<11.0.0🛠️ Interactive Setup & Dependency Resolver
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