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smthemex/comfyui_joyai_echo

★ 21PythonAudience · vibe coderComplexity · 4/5Setup · hard

TLDR

A ComfyUI plugin that adds a video-plus-audio generation model from JD, letting you produce multi-minute videos from text prompts on a consumer GPU with as little as 6 GB of video memory.

Mindmap

mindmap
  root((comfyui_joyai_echo))
    What it does
      Text to video with audio
      Long video generation
      Low VRAM support
    Tech Stack
      Python
      ComfyUI nodes
      GGUF compressed models
    Setup
      Clone to custom nodes
      Download Hugging Face models
      Connect nodes visually
    Limitations
      Inference only
      Image to video needs v1.5
      Large model downloads
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Things people build with this

USE CASE 1

Generate a five-minute AI video with synchronized audio from a text description on a consumer GPU with only 6 GB of video memory.

USE CASE 2

Add JoyAI-Echo video generation nodes to an existing ComfyUI workflow to produce long-form video output alongside other AI image tools.

USE CASE 3

Use GGUF compressed model files to run video generation on hardware that would otherwise lack enough memory for full-precision models.

Tech stack

PythonComfyUIGGUF

Getting it running

Difficulty · hard Time to first run · 1h+

Requires downloading several large model files from Hugging Face and placing them in specific folders, GGUF format available to reduce VRAM requirements.

In plain English

This is a plugin for ComfyUI, a visual workflow tool used to run AI image and video models on your own computer. The plugin adds support for JoyAI-Echo, a video generation system developed by JD (a large Chinese tech company) that can produce videos up to several minutes long, with synchronized audio, from a text description. What makes it notable is the low hardware bar. According to the README, a graphics card with just 6 GB of video memory can generate a five-minute video at 848 by 512 pixels. That is unusually accessible for long-video AI work, which normally demands much more powerful hardware. The plugin achieves this partly by supporting compressed model files in the GGUF format, which trade a small amount of quality for much lower memory use. To use it, you clone the plugin into ComfyUI's custom nodes folder, install the Python dependencies, and then download several large model files from Hugging Face. The file layout the README describes includes a video model, separate audio and video compression models, and a language model that processes your text prompts. Once those are in place, you connect the nodes in ComfyUI's visual editor and run inference. The current release is inference-only, meaning you can generate videos but not train or fine-tune the underlying model yourself. Text-to-video works with the provided checkpoints, image-to-video requires a version 1.5 model that was still in training when the README was written. The project includes one example workflow image to get started. The README has a mix of Chinese and English notes, with the technical instructions in English.

Copy-paste prompts

Prompt 1
I cloned comfyui_joyai_echo into my ComfyUI custom nodes folder. Which model files do I need to download from Hugging Face, and exactly where do I place them in the ComfyUI folder structure?
Prompt 2
Walk me through connecting the JoyAI-Echo nodes in ComfyUI using the example workflow image to generate a one-minute text-to-video clip with audio.
Prompt 3
The comfyui_joyai_echo plugin is running out of VRAM on my 6 GB GPU. Should I switch to the GGUF model files and what quality difference should I expect?
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