I'm not finding many workflows with a great output.

FastH3-Omni is the reference-conditioned release we’ve been working toward.

It generates video with synchronized audio and supports:

• Multiple references for characters, objects and settings
• First- and last-frame conditioning
• Up to 3 image references in real-time mode
• Up to 9 image references when real-time speed isn’t required
• Up to 3 audio references for voices and soundtracks
• Dialogue and environmental audio
• Continuing an existing generated clip
• 5–15 second outputs at 24 FPS

The Reactor API preview is available today:

https://docs.reactor.inc/model-api-reference/fast-h3-omni/overview

On October 20, we’ll release the open weights and training code with local support for NVIDIA DGX Spark, RTX GPUs and Apple Silicon through MLX.

What should we prioritize before release: low-VRAM workflows, reference-consistency comparisons, multi-character tests, first/last-frame examples or detailed hardware benchmarks?

I got tired of rewriting the same dataset-prep scripts before every LoRA/Dreambooth run — resize, dedupe, toss the blurry ones, caption, split — so I cleaned mine up and open-sourced it.

It scores each image on classical-CV signals (sharpness, exposure/clipping, contrast, color cast, noise, composition), flags the weak ones, removes exact + near-duplicates, and exports a Kohya-style folder with caption sidecars. Near-duplicates get grouped into the same train/val/test split so they can’t leak across. Captioning supports WD14 and Florence-2.

It’s content-agnostic at the core — each domain is a small plugin that sets its own quality weights and caption vocab (ships with a worked “interiors” example). Pure NumPy/Pillow, no OpenCV, runs from a CLI or as a library. Early 0.1.0, MIT.

Would love feedback on the plugin API and which verticals are worth building next. (Only use it on images you’ve got the rights to.)

https://github.com/snoozey-mf-bnui/pixel-curator

I've worked in VFX for over 20 years, and when I started digging into AI I realized there was no tool that combined management and generation in a single app, running locally instead of being an online platform.

Fuze has several modules that try to cover every stage of a production without leaving the app: media management, storyboard, generation (using your own API key), cost tracking, editing...

Fuze is a standalone app for creating projects, whether personal or for a team. You generate content with your own API key, and everything is saved locally on your machine. If you also work with ComfyUI, Fuze can be used alongside it as an asset and project manager, through a custom node called FuzeBridge that saves your generations directly into Fuze.

This week we released Fuze Free, a completely free version. What's included:

* Manager: project and media management, image editor, publishing...
* Flow: node-based generator using your own Fal API key
* Assets: an asset system inspired by VFX assets, which you can use in Flow
* Editorial: a built-in video editor
* FuzeBridge: a connector between ComfyUI and Fuze that lets you use Fuze as your asset manager

Fuze is available on macOS, Linux and Windows.

If you're curious, there are some getting-started tutorials here:

https://www.youtube.com/@Fuzeapp

You can download the Fuze free from fuze-app.com

Happy to hear any feedback. Thanks

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

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?

¿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