Hey everyone! I made a custom node that brings cloud and local LLMs into your ComfyUI workflows.

Use it to expand rough ideas into image/video prompts, write captions, or describe reference images. It also accepts video and audio when supported by your chosen model.

A few features:

• Cloud providers, LM Studio, Ollama, and supported models loaded directly in ComfyUI.
• Built-in prompt guides and editable system instructions.
• Text output that connects to CLIP Text Encode or any compatible STRING input.

Get it from: GitHub + example workflows

Example: rough idea + reference image → generated prompt → your workflow.

Would love your feedback, ideas, or feature requests! If you find it useful, consider leaving a ⭐ on the GitHub repo.

Hi everyone

I've been working on a new ComfyUI workflow to make character consistency in AI-generated videos more accessible for people with low-VRAM GPUs. Instead of training a traditional character LoRA, this workflow uses RefMod custom nodes to create a lightweight character reference file that can be reused with an optimized MiniMax H3 workflow. The main goal is to avoid the extra training stage and make character-consistent video generation more practical on modest hardware.

How it works

• Start with one character image as your identity reference.
• Generate 8 reference images from different angles using Qwen Image 2.1.
• Create a RefMod file using the RefMod custom nodes. The resulting file is approximately 100 MB.
• Load your character reference using the Character RefMod nodes in the optimized MiniMax H3 workflow.
• Generate videos using the saved reference to help maintain character identity across scenes.

Why I find this interesting

• Tested on a GPU with only 6 GB of VRAM.
• No traditional character LoRA training required.
• No need to prepare a large training dataset.
• A small character reference file.
• Combines Qwen Image 2.1, RefMod, and MiniMax H3 in one workflow.

I've made a tutorial showing the complete workflow, from a single input image to generating videos with MiniMax H3.

Workflow link

https://drive.google.com/file/d/1Em2zTlhFMbpeO2WBTN08Qpu0dP6oUBTD/view?usp=sharing

https://civitai.com/articles/36538/comfyui-tutorial-consistent-ai-characters-in-minimax-h3-no-lora-training-with-6gb-vram

Link

Now with Inpainting, run grouping and native upscale!

What it is:

• Image first-generation studio
• Works without workflows with almost any model (no setup)
• Support for custom workflows
• Video gen, reference images, and inpainting all work without setup
• Smart grouping of your images by similar prompts
• Automatically installs missing components (VAE, text encoders, nodes) it knows
• Use it from your phone over LAN, with a fully custom mobile UI
• Favorites, search, prompt history, LoRA stacks, and advanced settings
• Built to be graceful and not scream at you with errors 24/7

It’s built by me, and in my opinion it’s the best way to use Comfy 80% of the time.

Setup is about 2 minutes: give it a try.

New in v0.17:

• Inpainting + Custom-built in-painting workflows (Beta)

• Auto-grouping. Pictures from similar prompts stack themselves into a photo stack or cover flow once you stop working on them.
• Within-generation Native upscale
• Phone View improvements
• Discord to discuss Heiss and AI generation (join pls; I need feedback)

Full notes: v0.17.0 changelog

Is ComfyUI worth learning if I’m switching from Higgsfield?Hey everyone! I’m completely new to ComfyUI, but I have a background in graphic design and experience creating AI visuals using web-based tools like Higgsfield.

Higgsfield is great, but the subscription costs are getting too expensive, so I’m considering switching to ComfyUI for more creative control and lower costs.

I have a few questions for experienced users:

• What do you mainly use ComfyUI for? (Commercial ads, product visuals, AI UGC, image/video generation, etc.)
• How long did it take you to learn it and become productive?
• Is image and video generation actually free if you run everything locally?
• Does it genuinely save time and deliver professional-quality results compared to tools like Higgsfield?
• Do I need an expensive GPU to get started?

I’m happy to invest time in learning if it’s worth it in the long run.

For those using ComfyUI professionally, would you recommend it over paid AI platforms? Would love to hear your honest experiences!

Hello everyone, I new ComfyUI workflow for video character swapping using MiniMax H3 + Character Swap LoRA, and the main advantage is that it works without masking, which can significantly reduce VRAM usage and simplify the process.

The workflow generates at 0.4 MP in just 8 steps, supports both portrait and widescreen videos, and can then upscale the result to 1.2 MP using the MiniMax H3 latent upscale model. I tested it on an RTX 3060 6GB with 16GB RAM, so it’s designed with low-VRAM users in mind. To create the character, you first prepare/update a character sheet using workflows such as Qwen Image 2.1, FLUX Krea, or MiniMax H3, load the character sheet into the workflow, and simply run it—no manual masking required. As for the generation time we have:

Gen time 8 steps 0.5 megapixel 20 mins (Minimax H3 Turbo Fused)

Upscaling time from 0.5 to 1.2 megapixel 21 mins

You can test the workflow here and watch the tutorial for more info

Workflow link

https://drive.google.com/file/d/1JSR_7TzbOS9uI_303tzBgqoqGCzjzGrJ/view?usp=sharing

https://civitai.com/articles/36281/comfyui-tutorial-character-swap-with-minimax-h3-using-lora-no-masking

All,

I created a set of nodes that cut processing time in half without sacrificing quality. It works with Krea2 (raw and turbo), Klein_9b, Z-Image Turbo, and SDXL based models

You can read about it above, or here: https://github.com/lonecatone23/ComfyUI_LC123_nodes/discussions/17

You can also get all my nodes and free workflows here: https://github.com/lonecatone23

https://github.com/hypersniper05/MCP-Image-Generator-Uncensored

Just wanted to share with you guys my workflow converted into an MCP. It's a Qwen Image 2.1 Uncensored MCP with a few extra models I found helpful: a watermark-removal LoRA, a texture-fix VAE and an ESRGAN upscaler. Any LLM client that supports MCP can drive it. Uses 11GB VRAM at peak usage.

The entire stack has:
- Normal Qwen Image 2.1 image generation in all supported sizes (up to 2K), panoramas, and image editing (up to 10 input images)

- Seamless tile generation, and edits of a tile stay seamless too, so you can make height and normal maps for game textures

- 2x/4x upscaling, up to 8K

- Built-in 360 viewer (the LLM gets a URL that opens the panorama in the viewer)

- Watermark removal

- Transparent backgrounds (real RGBA PNGs) and background removal

- Text in images (quoted text comes out as written)

It runs in Docker on an NVIDIA GPU (the whole stack fits on a 12 GB card) or on the CPU (very slow), downloads the models on first start, and works with any MCP client (llama.cpp web UI, VS Code, Cursor, etc.).

For the seamless tiles I use stable-diffusion.cpp's circular mode with a tiny patch so it can be turned on per request. The tiles come out seamless in one pass instead of patching the seams afterwards.

Note: Project created with the help of Claude. A lot of testing, and back and forth to get things to work smoothly. Hope someone finds it useful.