ComfyUI-Upscaler-Tensorrt

ComfyUI-Upscaler-Tensorrt
★ 238

加速超分TensorRTFP16优化ComfyUI节点
在ComfyUI中集成TensorRT的超分节点，自动构建FP16引擎，提速3-4倍，支持256–1280px输入并可4×放大至高分辨率。
💡 在ComfyUI中将中等分辨率图像快速放大为高分辨率
🍴 38 Forks💻 Python🔄 2026-01-12
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https://pan.quark.cn/s/6862a2001521
📦 requirements.txt
tensorrt
polygraphy
requests
📄 README

ComfyUI Upscaler TensorRT ⚡

[](https://www.python.org/downloads/release/python-3123//)

[](https://developer.nvidia.com/cuda-downloads)

[](https://developer.nvidia.com/tensorrt)

[](https://creativecommons.org/licenses/by-nc-sa/4.0/deed.en)

This project provides a Tensorrt implementation for fast image upscaling using models inside ComfyUI (2-4x faster)

Last tested: 12 January 2026 (ComfyUI v0.8.2@c623804 | Torch 2.9.1 | Tensorrt 10.14.1.48 | Python 3.12.3 | RTX5090 | CUDA 13.1 | Ubuntu 24.04)

⭐ Support

If you like my projects and wish to see updates and new features, please consider supporting me. It helps a lot!

[](https://github.com/yuvraj108c/ComfyUI-Depth-Anything-Tensorrt)

[](https://github.com/yuvraj108c/ComfyUI-Upscaler-Tensorrt)

[](https://github.com/yuvraj108c/ComfyUI-Dwpose-Tensorrt)

[](https://github.com/yuvraj108c/ComfyUI-Rife-Tensorrt)

[](https://github.com/yuvraj108c/ComfyUI-Whisper)

[](https://github.com/yuvraj108c/ComfyUI_InvSR)

[](https://github.com/yuvraj108c/ComfyUI-Thera)

[](https://github.com/yuvraj108c/ComfyUI-Video-Depth-Anything)

[](https://github.com/yuvraj108c/ComfyUI-PiperTTS)

[](https://www.buymeacoffee.com/yuvraj108cZ)

[](https://paypal.me/yuvraj108c)

⏱️ Performance

_Note: The following results were benchmarked on FP16 engines inside ComfyUI, using 100 identical frames_

| Device | Model | Input Resolution (WxH) | Output Resolution (WxH) | FPS |

| :—-: | :———–: | :——————–: | :———————: | :-: |

| RTX5090 | 4x-UltraSharp | 512 x 512 | 2048 x 2048 | 12.7 |

| RTX5090 | 4x-UltraSharp | 1280 x 1280 | 5120 x 5120 | 2.0 |

| RTX4090 | 4x-UltraSharp | 512 x 512 | 2048 x 2048 | 6.7 |

| RTX4090 | 4x-UltraSharp | 1280 x 1280 | 5120 x 5120 | 1.1 |

| RTX3060 | 4x-UltraSharp | 512 x 512 | 2048 x 2048 | 2.2 |

| RTX3060 | 4x-UltraSharp | 1280 x 1280 | 5120 x 5120 | 0.35 |

🚀 Installation

  • Install via the manager
  • Or, navigate to the /ComfyUI/custom_nodes directory

    • git clone https://github.com/yuvraj108c/ComfyUI-Upscaler-Tensorrt.git
cd ./ComfyUI-Upscaler-Tensorrt
pip install -r requirements.txt

    🛠️ Supported Models

  • These upscaler models have been tested to work with Tensorrt. Onnx are available here
  • The exported tensorrt models support dynamic image resolutions from 256×256 to 1280×1280 px (e.g 960×540, 512×512, 1280×720 etc).

  • 4x-AnimeSharp
  • 4x-UltraSharp
  • 4x-WTP-UDS-Esrgan
  • 4x_NMKD-Siax_200k
  • 4x_RealisticRescaler_100000_G
  • 4x_foolhardy_Remacri
  • RealESRGAN_x4
  • 4xNomos2_otf_esrgan
  • 4x-ClearRealityV1
  • 4x_UniversalUpscalerV2-Neutral_115000_swaG
  • 4x-UltraSharpV2_Lite

    • ☀️ Usage

  • Load example workflow
  • Choose the appropriate model from the dropdown
  • The tensorrt engine will be built automatically
  • Load an image of resolution between 256-1280px
  • Set resize_to to resize the upscaled images to fixed or custom resolutions

    • 🔧 Custom Models

  • To export other ESRGAN models, you’ll have to build the onnx model first, using export_onnx.py
  • Place the onnx model in /ComfyUI/models/onnx/YOUR_MODEL.onnx
  • Then, add your model to this list load_upscaler_config.json
  • Finally, run the same workflow and choose your model
  • If you’ve tested another working tensorrt model, let me know to add it officially to this node

    • 🚨 Updates

    12 January 2026

  • Add more resizing scale factors
  • Add custom resolution resizing

    • 27 August 2025

  • Support 4x-UltraSharpV2_Lite, 4x_UniversalUpscalerV2-Neutral_115000_swaG, 4x-ClearRealityV1
  • Load models from config PR#57

    • 30 April 2025

  • Merge https://github.com/yuvraj108c/ComfyUI-Upscaler-Tensorrt/pull/48 by @BiiirdPrograms to fix soft-lock by raising an error when input image dimensions unsupported

    • 4 March 2025 (breaking)

  • Automatic tensorrt engines are built from the workflow itself, to simplify the process for non-technical people
  • Separate model loading and tensorrt processing into different nodes
  • Optimise post processing
  • Update onnx export script

    • ⚠️ Known issues

  • If you upgrade tensorrt version, you’ll have to rebuild the engines
  • Only models with ESRGAN architecture are currently working
  • High ram usage when exporting .pth to .onnx

    • 🤖 Environment tested

  • Ubuntu 24.04, Debian 12
  • Windows 11

    • 👏 Credits

  • NVIDIA/Stable-Diffusion-WebUI-TensorRT
  • comfyanonymous/ComfyUI

    • License

    Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)