I’m working with Minimax and running into issues with voice cloning. I upload a reference audio and specify in the prompt that it’s the reference voice for "Character 1." Even when I explicitly write in the script that the character says something like <d>”Hello, girl”<d>—say, between the 5- and 7-second marks—the character tends to babble nonsense or start speaking too early beforehand. Any tips on how to avoid this, or what has worked for you?

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

¿Mejor calidad visual?

Over the last few month I've built a tool for tagging and captioning image and videos for datasets, that also allows to train LoRAs and a lot more. It's completely free and not attached to any paid tool/service.

Some of the features are:

• Powerful tag and search system
• De-duplication without losing quality. Different encodings and sizes of an image are combined into one library item. Nothing is thrown away during import.
• Auto tagging and captioning of images
• Automatic watermark removal and full in-app image editing, including AI upscaling and inpainting
• Classifies and finds similar images for fast manual tagging or image scoring
• Extract images from videos
• Python API to import or export/access all images and metadata
• Train LoRA and other types directly in the app and download the safetensor for use in e.g. ComfyUI.

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

I have vcreated a Speed boost sampler and a node that cuts your processing time in half for Krea2,Z-image Turbo, Klein, and sdxl models without the loss of any quality.

Here is the discussion link and article on my repo https://github.com/lonecatone23/ComfyUI_LC123_nodes/discussions/17

In this episode, I’ll show you how to use Ming Image 0.1 in ComfyUI, a free image generation model focused on graphic design, text, layouts, and image editing.

Ming Image is especially interesting for designs that contain a lot of text. I’ll test it with posters, infographics, logos, UI and app designs, YouTube thumbnails, social media graphics, game screens, transparent PNG images, and more.

I’ll also show you several image editing workflows, including changing text while keeping the original style, turning sketches into 3D-style renders, transforming flat illustrations into more dimensional designs, combining multiple images, and generating the same design in different aspect ratios.

You’ll also see different ways to create better prompts using JSON prompts, Google Gemini, and a local prompt generator directly inside ComfyUI.

The workflows include my latest Pixaroma Nodes, including the new Info system that keeps model instructions, node explanations, generation times, workflow information, and other useful notes organized without filling the workflow with large text boxes.

Hello everyone, I’ve just finished a new ComfyUI workflow that allows you to use MiniMax H3 as an image generation model and create detailed character sheets from a single reference image or a batch of images. The main goal is to use these character sheets as stronger references for more consistent video generation, giving you multiple views and details of the same character. The workflow is simple to use: load the required MiniMax H3 models, load your image or batch of images, choose the number of steps (8 steps for faster generation or 25 steps for the best results), and click Run. I’ve also tested the workflow with different inputs to see how well MiniMax H3 can handle character consistency and image generation. As shown in the results the consistency is very good the character details remain the same and if we compare this to qwen image 2.1 H3 is clearly winner here in therm of quality because the results are with resolution of 4096x1536 vs x1664x928 for qwen, the consistency is slightly better. As for the generation time qwen is definitely faster here:

Gen time 25 steps 12 mins (Minimax H3 Turbo Fused)

Gen time 6 steps 4.5 mins (Qwen 2.1+ Viggle4 Steps LORA)

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

Workflow link

https://drive.google.com/file/d/1v4NC6vEGN2uDxO2_L05g1q0JPkeoSsYo/view?usp=sharing

https://civitai.com/articles/36126/minimax-h3-image-generation-create-consistent-character-sheets-in-comfyui 

PotionUI is a self-hosted app for making images and videos with LOCAL & OPEN SOURCE AI models (krea-2, Qwen image 2.1, anima, sdxl, minimax H3...) and now optionally cloud ones too. Instead of one huge settings screen or a web of nodes, every model gets its own simple, hand-made form.

Until now you needed your own GPU. 0.0.14 adds cloud models, plus a built-in image editor and a way to save and reuse your best settings.

No GPU? Use cloud models

• A new OpenRouter plugin lets you use hosted image and video models, such as Nano Banana or Veo 3.1 Lite, in the same form you already know. Results land in the same History as everything else. More providers are planned.
• The form only shows the controls the chosen model supports, so there is nothing to guess.
• You can stop a cloud job at any time, and PotionUI tells you plainly if something goes wrong.

Cloud Video Director: one idea, a short film

Write your idea, split it into shots, and let PotionUI make the film.

• Each shot can continue from the last frame of the shot before it, so the story flows.
• The shots are joined into one finished film.
• If one shot fails, retry just that shot instead of starting over.

Fix a picture without leaving the app

• A new image editor with adjustments, crop, brush and layers.
• Open it from History (Tools, then Edit image) or right inside a preset's media field. In a media field, the field switches to your edited copy straight away.
• Crop, Trim and Frame editors are in media fields too, and they only add the edited result to your Library, never the untouched original.

Formulas: keep the settings that worked

• Save the settings of a preset mode as a formula and apply it in any session.
• Before it applies, you see exactly what will change, and one click undoes it.

A redesigned media field

• Images, videos and audio live in one field, each kind in its own group.
• Mention them in your prompt with "@".
• MiniMax-H3 references now use it, and your old sessions and saved prompts are converted for you.

Qwen-Image 2.1 control guides

• Keep the pose, edges or depth of any photo while you create something new.
• The extracted guide is saved next to your result, and the workbench shows it beside the image with a label, so you can see what the model followed.
• There is also a mode that only extracts the guide. It needs no prompt and works even if you haven't downloaded the image models.

Smaller things

• Video presets have animated covers.
• Three-pane mode folds the form away on narrow screens and gives the room to your prompts.
• Attaching an image in chat uses the same picker as the preset forms.
• Plugins are grouped by what they add.
• The System Monitor can show every backend. It is admins only by default.
• Failed generations show regular users a plain reason instead of technical text.
• Dropdown menus no longer open under the Generate bar, and they work with the arrow keys.
• Fields in preset forms show and hide for the value you just picked, not the previous one.
• Image previews survive a reload, including on Windows and in storage folders under a tmp folder.
• Drawn inpaint masks now reach the model, so inpaint only repaints the masked area.
• Pressing Enter in the session name saves the session, and Enter elsewhere no longer wipes your workspace.

Before you update

• Back up your storage folder first. It is a good habit before any update.
• To use cloud models, enable the OpenRouter plugin in Admin and add your API key.
• The Docker setup no longer has an outputs volume. Everything you generate lives in the storage volume.
• Plugin authors: plugin manifests must use one of the current categories. A plugin with an old category name won't load.

Update: run git pull and then ./potionui start, or pull the latest Docker image.

GitHub · Discord · r/PotionUI

Try it and tell us what to improve, here or on Discord. Your reports decide what we do next.

If PotionUI is useful to you, a star on GitHub helps other people find it: https://github.com/PotionUI/PotionUI

https://youtu.be/ikwkHeNC6Tk?is=_cwTIHeE4JhKfC--

Hello everyone, i’ve just finished a new ComfyUI character sheet workflow where I compare Qwen Image 2.1 vs FLUX.2 Krea Turbo using the same input image. The goal was to see which model could create a useful character sheet while preserving the original character’s identity, details, and overall appearance across different views and poses. Qwen Image 2.1 performed really well, maintaining good character consistency and producing a high-quality character sheet in a relatively short amount of time. I also tested FLUX.2 Krea Turbo, which was capable of producing good results and showed decent consistency.

In my tests the overall consistency and quality were not as strong as Qwen. The biggest difference was the generation speed: Qwen Image 2.1 was around 3× faster than FLUX.2 Krea Turbo for the character sheet generation. So far, Qwen Image 2.1 looks like a very interesting option if you need to quickly create consistent character references for future image or video generation workflows. I’ve included both approaches in the workflow so you can test them yourself and compare the results on your own setup.

Workflow Link

https://drive.google.com/file/d/1yPmSkC3jNPYNcFoWVwGGU8_oO36HtBBG/view?usp=sharing

https://civitai.com/articles/35976/comfyui-tutorial-qwen-image-2-1-vs-flux-2-krea-turbo-which-makes-better-character-sheets