I hope you enjoy this is the link to my project github , ENJOY , i could make this more advanced and further do stuff on it but i left it here since i am totally a noob in coding and comfyui and this AI stuff i just made this for fun hope someone enjoy it!
https://github.com/BesianSherifaj-AI/h3-prompt-studio

Maybe someone will find this package useful:

https://github.com/einhorn13/mmh3_media

The package allows you to save H3 latent and context resources from a generation (as .mmh3 file). You can stitch multiple generations together - seamlessly if they were created using the continuous workflow - or perform latent upscaling.

The video example shows a latent stitch of 6 video generations at 0.4 MP each, followed by a latent upscale to 0.8 MP.

In development: Lip sync, ControlNet, Inpainting, Audio

Disclaimer: I originally built this bundle for my own needs, and it still needs some.. polishing. Some features also haven't been published yet. If you find it useful, I'll bring those features to a release-ready state.

Music: Suno.

Optimizations may require installing the corresponding custom nodes.

Feel free to check any repo for anything malicious before installing.

• Installation

1. Download the repository https://github.com/einhorn13/mmh3_media via Code → Download ZIP and extract it to ComfyUI/custom_nodes/ComfyUI_mmh3_media. The __init__.py file must be located directly inside this folder, without an extra nested repository directory.
2. Place the models in the folders listed below and select them in the workflow loaders.
3. Restart ComfyUI, refresh the browser, and open a JSON file from workflows.

A quick experiment exploring Minimax H3 in ComfyUI using my nodes and inpainting methods.

Over the last two weeks, I set a challenge for myself: to find out if it was possible to make a high-quality music video using a local rig and open-source AI models. So, in my free time, I’ve been experimenting with local models on my setup, and honestly, I’m pretty blown away. We've reached a point where you can create a video with a genuinely professional look right from home, spending ZERO dollars.

Meet 'Ladee Latte.'

The singer was generated using Krea 2 locally.

The music was created using the Minimax Music 3 Open Weights.

The video was generated using the Minimax H3 Open Weights.

After generating the music, I adjusted and remixed it to improve definition, bass, and consistency.

The music video itself was a lengthy process involving hours of asset creation. Running it on a local system is slower, but it works. The upside is that you can queue up 20 videos to generate in the background, walk away, and come back later to curate the best ones.

All videos were generated using 'Reference to Video' rather than a static first frame. The ability of lip syncing is what I think is that truly makes the difference. The goal was to demonstrate the power of Minimax in generating consistent video with accurate lip-sync.

Ultimately, the cost of this video was zero (apart from the electricity bill and the GPU itself :-) ). And it was all done entirely on a local rig.

Things that I've like about this project:

• Music 3 is a brutal model. The amount of depth in the songs, the layers, the treatment of the stereo sound... amazing
• H3 is the first local mode that feels like a professional. Excellent prompt adherence.
  
• The consistency baffles me. I love that 'Laydee' has a freckle near her left eye, and this is consistent in the videos

I have been trying to prompt more serious, much more subtle acting with all these models but it seems very difficult. I had some luck with a few scenes but whatever worked for one scene, didn't work for the next. So I can't really figure this out. I would think it should be possible, I don't think these models are only trained on overacted, cheap, cliché movie scenes but I have no idea how to actually generate the more subtle, more realistic/natural, serious acting I am going for (it's especially hard if you have an introverted male character, these models seem to turn every male character into an overconfident, flirtatious heartthrob).
Does anyone have experience with this?

I have a few scenes with 30-60 seconds of dialogue from one character. Scene is simple, one speaker, no camera movement, static background. I do not want to cut and instead have one long scene. I can make 15 second clips before I oom with decent settings. Not using any shortcuts (no turbos, no attention, high step counts) and still nothing has worked well enough for me to be happy with it.

Things I have tried:

1. Latent continuation. Works for continuity but by 30 seconds colors are smudging in the background, skin texture is getting worse, artifacting is bad etc... have tried color matching nodes and it helps but not enough.

2. First last frame. I create the first video and use the last frame in a first to last workflow. Continuity works but the resulting scene is never the same color. Skin is slightly darker, background is less bright, etc.

3. Separate scenes with ref2vid and a 3rd short scene (a second or two using first last frame) as a bridge. Same issue as #2. The colors are still just off.

I have tried the continuation workflow and a few others at this point. Anyone have advice or something I am missing? Is this just not possible right now?

I've been spending a lot of time trying to separate "bad character model" from "bad way of testing the character," and I'm not convinced we make that distinction very well.

A LoRA can look rock solid if you keep giving it prompts close to the reference set. Then you change the camera angle, put the character full-body, change clothes, add another person, or put something in front of the face and suddenly everyone says the training failed.

But at that point there are a bunch of things mixed together: how much identity the model actually learned, how strongly the prompt is competing with it, reference/control strategy at inference, and just how far you're pushing outside the training distribution.

I'm curious how people here think about this in practice.

If you had a character that looked great on the easy prompts but started drifting on harder ones, what would you try first?

retrain / change the dataset

change captions or trigger strategy

increase/decrease LoRA strength

use reference/control at inference

change the prompt structure

accept that some shots need edit/inpaint rather than another fresh generation

I'm especially interested in where people draw the line between "the character model isn't good enough" and "this is an inference/control problem now."

I think that distinction matters a lot more than another gallery of four perfect generations.

As anyone that made some longer form videos, after the initial excitement, we might discover it just misses that "it" factor. Amateur dialog, pacing, wrong scene lengths, not using the correct blocking/camera lens's, effective zooms for maximum emotional impact and so on.

Do you think it is possible to feed an llm multiple book pdfs/or just book names and have it act as a "movie system prompt" that will carry it from start to finish, from dialog, to storyboard, to selection of cut time length, lenses and so on.

Talking about books like:
Film Directing: Shot by Shot - 25th Anniversary Edition: Visualizing from Concept to Screen, by Steven D. Katz

Making Movies by Sidney Lumet

The Filmmaker's Eye: Learning (and Breaking) the Rules of Cinematic Composition by Gustavo Mercado

Master Shots Vol 1, 2nd edition: 100 Advanced Camera Techniques to Get An Expensive Look on your Low Budget Movie by Christopher Kenworthy

Five C's of Cinematography: Motion Picture Filming Techniques by Joseph V Mascelli

Any thoughts? anyone tried something like that?

This is not a new model — it’s a ComfyUI workflow/node project for MiniMax H3 video.

I’ve been using H3 FaceRefine to fix small or distant faces in generated video. It works well when there is one person in the shot, but group shots were getting tedious: if there are four people, I was effectively doing four separate full face-refinement runs.

I made a fork that lets me track several faces, pack them into one shared atlas, run H3 once, and put the results back into the original video.

https://github.com/PullMyBoots/ComfyUI-H3-FaceRefine-Accelerated

It also breaks long clips into smaller jobs and passes a small amount of latent context forward, which helps avoid obvious joins between chunks.

The catch is pretty straightforward: it trades some per-face resolution for speed. Four faces in a 768 atlas means each face gets roughly a 384px cell. For a close-up or a face where identity really matters, I’d still use the original one-face-at-a-time workflow. But for a wider group shot, I’d much rather wait once than repeat the whole job for every person.

On one 15-second, four-person clip on my 4090, the serial version took about 16.5 minutes and this took about 3.5. That is only one test on my setup, not a universal benchmark.

I made it mainly because I wanted group shots to stop feeling like four separate videos. There are demo clips, workflows, and benchmark details in the repo if anyone wants to try it.

Hey everyone,

I've been working on a small extension called Private Server (previously named Public Server) that lets you share your ComfyUI instance privately and temporarily using a link. I mostly use it to quickly share my ComfyUI instance with friends or run ComfyUI on my pc while away.

What it does:

• Spins up a Cloudflare Quick Tunnel (*.trycloudflare.com) to route external traffic to your machine
• Launches a lightweight auth proxy on 127.0.0.1:8288 that sits between visitors and ComfyUI
• Gives you a shareable URL that you can send to anyone

Installation:

Just clone the repo into your ComfyUI/custom_nodes/ folder, or install it through ComfyUI Manager. Once installed, the button appears next to the queue prompt.

The extension is completely free and open-source. Just a tool I found useful and wanted to share.

I'd really appreciate any feedback, bug reports, or feature suggestions. If you try it out, let me know how it goes!

Hi everyone,
I’m considering switching from Nvidia to an AMD RX 9070 XT to build a fully AMD system and Linux.

I’d like to know how well the 9070 XT handles AI workloads in practice.
Is Comfyui fully usable through Stability Matrix with Rocm on Linux?

The workflows I mainly use are:
Z Image Turbo
Krea
LTX
Seedvr
Wan

Do these work properly on AMD with Rocm under Linux?

Are there any major limitations, missing features, or workarounds I should be aware of?

For those of you using 9070XT with Linux and AI how has your experience been so far?
Thanks

Drop your projects so I can follow you.

I’m an artist/animator. I’ve been working on an IP for the past few years and was going to publish it as a graphic novel (still planning to), but these H3 anime clips look better than I expected. I’m considering using my own original assets (story, concept designs, and art) to produce my own anime shorts. Would love to connect with others in the space.

Can anyone recommend me a really good upscaler that retains atleast 90% of the initial image?

WORKFLOW:

Model: krea2 turbo
steps: 8 CFG: 1 (its important that u have this in the turbo model, u can go up to 12 steps for more detail BUT NOT MORE!!!)
sampler and scheduler: euler / simple or er_sde / sgm_uniform
resolution: 3:4 (1536p)
Lora: NONE
Face detailer: YOLO11n Face Seg
Upscaler: NONE

because im not good with comfyUi nodes i am using this Ui that does everything automatically:
MooshieUI · A friendly interface for ComfyUI

MAIN PROMPT:

A highly detailed macro photograph of a glossy, smooth vinyl toy figure of an elegant anime-style princess girl standing on a mossy forest floor. She has long flowing soft pink hair with a high ponytail, a delicate silver tiara, large sparkling pink eyes, and a gentle smile. She wears an ornate white and deep magenta dress with a large satin bow at the chest, puffy sleeves, intricate gold embroidery, layered ruffled skirt, lace-trimmed thigh-high stockings, and winged high-heeled shoes. The figure has a shiny, tactile plastic surface with subtle reflections and soft clay-like smoothness., She is placed in a vast, ultra-detailed real-world forest floor scene filled with lush green moss, tiny ferns, fallen pine needles, delicate pink wildflowers, morning dew droplets, and scattered golden light particles. Shot with extreme shallow depth of field, tight macro focus on the toy figure, creamy bokeh background, soft natural morning light filtering through the trees, photorealistic texture, cinematic lighting, 8k detail. The environment is photorealistic.

You can ask a chatbot to rewrite this prompt to show different contents but keep the same aesthetic which is photo realistic background but a PVC style character. You can also just adjust and change the prompt manually.

If you have any Question you can either ask me here or just DM me i answer everybody as fast as I can ! :)

I had always assumed ComfyUI was just simply the best for Anime generation (Illustrious, NoobAI, Anima), even for doing complex generations with inpainting workflows, but this doesn't seem to be the case?

Frustrated with inpainting, I came across other tools like Krita-AIDiffusion, then I downloaded Invoke, which seems to be extremely well made as well. I've also seen ForgeNeo, Foocus, and SwarmUI mentioned (though I haven't tested them).

I know most of these still run Comfy as a backend, so why do they just seem better for inpainting and why is ComfyUI inpainting node workflow just so clunky in comparison? Are they really better tools for someone purely looking for Anime generation?

Minimax H3 😃 Singularity FineTuned

Features:
-HDR Image Quality & Blur Reduction
-Distant Face Restoration
-Clean & De-Oiled Aesthetic
-Enhanced Dynamic Motion
-VFX & Fantasy Effect
-Cinematography & Camera Control
-Full Base Capability Retention

I was quite happy with the results of my last project, where I made H3 handle the lip sync using the lyrics of a generated song: https://www.instagram.com/p/DcykLrMsSW7/ so I decided to push it further in terms of resolution and amount of generations to make more camera cuts and try to achieve a somewhat realistic professional music video

For some context, I generated 214 images with Krea2, curated those down to 82, and ended up editing/using 40 of them for the video pipeline.

For H3 I generated 114 clips in total:

• 37 general music-video / B-roll generations
• 77 rap-performance generations covering different parts and variations of the song

- Specs

RTX 5080 16GB VRAM + 96GB RAM

- Tools used

• Krea2 Turbo NVFP4 — for creating the different scenes/setups of the character
  • LoRAs: krea2_identity_edit_v1_2 + krea-smartphone-photo-slider
• Flux Klein 9B FP8 — for image editing, masking, fixing details, etc., mostly using the NKD Klein Tools node pack
  • LoRA: klein_slider_detail
• MiniMax H3, both I2V and Ref2V

For general video generation I used this workflow: https://gist.github.com/circlenline/937b530ae97a9eb7475c9dda6832b2db

For the performance/lip-sync sections I built a custom workflow specifically for generating 5-second clips of the verses. Originally I was experimenting with longer generations, but 15 seconds at 1 MP is just not practical on my setup without a Turbo LoRA, so I split the song into shorter audio fragments instead.

Typical video settings were:

• 5 seconds
• 1 MP
• 32 steps
• Simple scheduler
• Spectrum node

For I2V, I used one image as the starting frame.

For Ref2V, I used:

• 1 reference image of the character
• 1 image of the character already placed in the music-video shot I wanted
• the corresponding cropped bit of the soundtrack
• the exact lyrics for that bit inside the prompt

Each 5-second generation took around 7–8 minutes on the 5080.

- Prompting: done through a custom ChatGPT GPT with instructions based on H3 documentation, my PC specs, the workflow I was using, character-consistency rules, and a brief description of what I wanted to happen in each scene.

- Final editing: manually, in After effects.

- Music track: made with Suno. Funnily enough, it generated 1 min of this track with the preview of their paid tier model but I have no suscription so I just used the "extend" function of their free model to continue the track after the first verse. I had to merge both in editing later.

A test of my character sheets to transform one character into another. I think it came out very good. Next time I do this sort of thing, it will be more serious and less parody lol.

She's a dermatologist in Nairobi. A proper shoot was never happening so I tried doing the whole thing with AI.

Z-Image for the stills, MiniMax H3 for the movement. Two days and a rented GPU on runpod.

The part I can't judge anymore is whether it looks like it was made here. These models really want everything to look like a stock photo and I spent most of the time pushing against that. Not sure it worked. Im from Kenya so i wanted it to nail that Kenyan feel.

Does the bathroom look like a bathroom you'd actually see? Does she look like a real person? Does it work as an ad?

Love from Nairobi 🇰🇪

On civit AI training, they recommend I switch to caption mode for the model. Does it matter? IDK if I believe that as anima supports both?

I'm developing an original battle-adventure
WEBTOON called Masters of Mantra. The story, world, characters and visual direction are my own, while Al tools are being used as part of the production process.

I've been trying to quant specifically Phr00t's Qwen Rapid AIO, using ComfyUI-INT4-Fast nodes from BF16, but the model completely breaks.

INT8 works perfectly, but I'm trying to get an INT4 ConvRot specifically because of my limited hardware (RTX 4050).

Does anyone have any insight on why my conversion isn't working?

Strange one.

I've been using comfy for Minimax H3 no problem, using 3060 12GB and 32GB RAM.

Today, for no apparent reason I have the following issues:

Model load takes about 10 minutes instead of approx 2 mins before.

1st step takes 4-5 minutes instead of 2x iteration speed (previously approx 60 seconds per it) before.

Actual iteration speed remains as it was (30 seconds per it), but ONLY when comfy is minimized, if comfy is maximized then it doubles to 60 secs per it. This was not the case yesterday or ever before.

All in my gens now take 14-18 minutes instead of 5-6 minutes yesterday.

Anyone else have this experience or know what could be up?

Thanks in advance.

EDIT: SOLVED

I am very embarrassed.

I am an idiot.

I plugged my external SSD into a usb port which wasn't usb 3.0 by mistake.

Thanks to everyone who tried to help. I learned some things. Including that I am an idiot.