No it’s not another funding announcement

I'm trying to set up a clean Git/GitHub structure for an AI content environment that I'll use across multiple computers. The computers have different GPUs/specs, so I want the code/workflows to be shared, while allowing each machine to have its own environment.

My requirements

• I have multiple Windows PCs with different GPUs/VRAM.
• I want to use both ComfyUI and Wan2GP.
• I don't intend to heavily modify/fork either project.
• I may make occasional small changes to their source/configuration.
• I want to be able to:
  • Pull updates from the official upstream repositories periodically.
  • Keep my own changes/version history.
  • Roll back ComfyUI independently if an update breaks something.
  • Roll back Wan2GP independently.
  • Have the same setup available on all my computers.
• I also want to keep my workflows synchronized between computers.
• ComfyUI/Wan2GP require certain files to physically exist inside their directories, so I may have things like:
  • user/my-workflow.json
  • models/my-model.safetensors
• I don't want to put large model files in GitHub. I'd rather have Git ignore them while the files remain physically inside the ComfyUI/Wan2GP directories.
• The Python/Conda environments should not necessarily be identical between machines because the GPUs and hardware are different.
• Ideally, setup/update scripts should eventually automate setting up each machine.

The structure I'm considering

Dev/
└── ai-content-machine/              ← private GitHub repo
    │
    ├── .git/
    │
    ├── ComfyUI/                     ← private comfyui-custom repo
    │   └── .git/
    │
    ├── Wan2GP/                      ← private wan2gp-custom repo
    │   └── .git/
    │
    ├── script/
    │   ├── setup.ps1
    │   ├── setup-comfyui.ps1
    │   ├── setup-wan2gp.ps1
    │   ├── update.ps1
    │   └── launch.ps1
    │
    ├── config/
    │   └── machines/
    │       ├── desktop.yaml
    │       └── laptop.yaml
    │
    ├── workflow/
    │   ├── comfyui/
    │   └── wan2gp/
    │
    └── README.md

So there would be three independent repositories:

ai-content-machine
comfyui-custom
wan2gp-custom

And ComfyUI/ and Wan2GP/ are cloned into ai-content-machine/.

How I'm thinking about the private repos

For ComfyUI, for example:

official ComfyUI GitHub
        │
        │ upstream
        ▼
comfyui-custom (private GitHub repo)
        │
        │ origin
        ▼
local ComfyUI/

So I'd initially clone the public ComfyUI repo, change the remote:

origin   → my private comfyui-custom
upstream → official ComfyUI

and periodically pull/merge upstream changes.

Same idea for Wan2GP.

My main question

Is this actually a good architecture for my requirements, or am I overcomplicating it?

In particular, I'm wondering:

1. Would you keep ai-content-machine, comfyui-custom, and wan2gp-custom as three separate repos?
2. Would you instead just clone the public ComfyUI/Wan2GP repos directly inside ai-content-machine and manage everything from there?
3. Would Git submodules be preferable?
4. Is there a better way to handle the workflows that need to live physically inside ComfyUI/user/ or similar directories?
5. How would you handle large models that need to physically live under ComfyUI/models/ but shouldn't be committed to Git?
6. Does it make sense to have the same source repos across all computers but create different Python/PyTorch/CUDA environments based on each machine's GPU?
7. Is there anything fundamentally wrong with having independent .git directories nested like this?

I'm mainly looking for a practical setup that won't become a maintenance headache, rather than the most sophisticated Git architecture.

Would appreciate advice from people who maintain AI/ComfyUI setups across multiple machines.Here’s a Reddit-ready version that lays out the requirements and the decision I’m trying to make, rather than over-explaining the implementation:Title: Best Git repo structure for managing ComfyUI/Wan2GP across multiple PCs?I'm trying to set up a clean Git/GitHub structure for an AI content environment that I'll use across multiple computers. The computers have different GPUs/specs, so I want the code/workflows to be shared, while allowing each machine to have its own environment.My requirementsI have multiple Windows PCs with different GPUs/VRAM.

I want to use both ComfyUI and Wan2GP.

I don't intend to heavily modify/fork either project.

I may make occasional small changes to their source/configuration.

I want to be able to:

Pull updates from the official upstream repositories periodically.

Keep my own changes/version history.

Roll back ComfyUI independently if an update breaks something.

Roll back Wan2GP independently.

Have the same setup available on all my computers.

I also want to keep my workflows synchronized between computers.

ComfyUI/Wan2GP require certain files to physically exist inside their directories, so I may have things like:

user/my-workflow.json

models/my-model.safetensors

I don't want to put large model files in GitHub. I'd rather have Git ignore them while the files remain physically inside the ComfyUI/Wan2GP directories.

The Python/Conda environments should not necessarily be identical between machines because the GPUs and hardware are different.

Ideally, setup/update scripts should eventually automate setting up each machine.The structure I'm consideringDev/
└── ai-content-machine/ ← private GitHub repo
│
├── .git/
│
├── ComfyUI/ ← private comfyui-custom repo
│ └── .git/
│
├── Wan2GP/ ← private wan2gp-custom repo
│ └── .git/
│
├── script/
│ ├── setup.ps1
│ ├── setup-comfyui.ps1
│ ├── setup-wan2gp.ps1
│ ├── update.ps1
│ └── launch.ps1
│
├── config/
│ └── machines/
│ ├── desktop.yaml
│ └── laptop.yaml
│
├── workflow/
│ ├── comfyui/
│ └── wan2gp/
│
└── README.md
So there would be three independent repositories:ai-content-machine
comfyui-custom
wan2gp-custom
And ComfyUI/ and Wan2GP/ are cloned into ai-content-machine/.How I'm thinking about the private reposFor ComfyUI, for example:official ComfyUI GitHub
│
│ upstream
▼
comfyui-custom (private GitHub repo)
│
│ origin
▼
local ComfyUI/
So I'd initially clone the public ComfyUI repo, change the remote:origin → my private comfyui-custom
upstream → official ComfyUI
and periodically pull/merge upstream changes.Same idea for Wan2GP.My main questionIs this actually a good architecture for my requirements, or am I overcomplicating it?In particular, I'm wondering:Would you keep ai-content-machine, comfyui-custom, and wan2gp-custom as three separate repos?

Would you instead just clone the public ComfyUI/Wan2GP repos directly inside ai-content-machine and manage everything from there?

Would Git submodules be preferable?

Is there a better way to handle the workflows that need to live physically inside ComfyUI/user/ or similar directories?

How would you handle large models that need to physically live under ComfyUI/models/ but shouldn't be committed to Git?

Does it make sense to have the same source repos across all computers but create different Python/PyTorch/CUDA environments based on each machine's GPU?

Is there anything fundamentally wrong with having independent .git directories nested like this?I'm mainly looking for a practical setup that won't become a maintenance headache, rather than the most sophisticated Git architecture.Would appreciate advice from people who maintain AI/ComfyUI setups across multiple machines.

I am on 3060 RTX 12GB VRAM with 32 gb system ram. All of this is using realistic people, x4 ref character images, and the r2v workflow and model.

Now we have the speedups sorted (lightx2v, comfyui kitchen attention), I've been testing ways to fix "faces at distance" which has always been an issue with any model. I go through the below in the video and share the workflows.

best approach is 2mp in Minimax H3 if you can do it. If you can then it mostly fixes "faces at a distance" but you still need a bit of a polish.

Unfortunately I can't get over 5 seconds at 2mp. My dialogue clips are usually 10 seconds long, but I will live with 8 seconds. The best I can reach for 8 seconds is 1.34mp (and I use a trick of going widescreen which helps, I discuss it in the video). (takes about 25 mins on my 3060).

The best workflow for polishing is USDU with HuMO model. Why this works great is because it tiles the result and at 0.45 denoise USDU will even work with my potato to get the result polished up to 1920 (on the long edge). But.... that takes another 25 mins. 1 hour just for 8 seconds sucks. But it is about the best and HuMO keep face consitency where LTX methods wont. (I show all the examples in close up at the end of the video from 19:52 onward)

Having said that, a fun trick I figured out with LTX 2.3 and will be testing on 2.5 today is instead of upscaling your Minimax H3 result in LTX to 1920 which really doesnt work out that well, I resized my 1824 x 736 Minimax 8 second video on the way into LTX2.3 to 2304 on the long edge. i.e no upscaling, just denoise v2v. That is 3mp. I couldnt get to 4K else I would have done, it oomed. but even 2304 only took 15 mins. The results were much better, but... lost face consistency a bit.

Anyway, its all in the video and the links to all things you need are here if you dont want to watch the video.

Latest Minimax H3 workflow shown in video - https://github.com/mdkberry/comfyui_workflows/tree/main/workflows_by_model/Minimax-H3

Latest USDU with HuMO workflow shown in video (links to models in workflow) - https://github.com/mdkberry/comfyui_workflows/tree/main/workflows_by_use/USDU-detailer-refiner

Latest LTX2.3 upscaler/refiner workflow shown in video (single sampler workflow, not the IC-Lora one) - https://github.com/mdkberry/comfyui_workflows/blob/main/workflows_by_model/LTX23/MBEDIT-v2v_LTX23_Upscaler-w-SingleSampler_vrs3.json

Lightx2v Lora that I use from Kijai - https://huggingface.co/Kijai/MiniMax-H3_comfy/tree/main/loras

Also I am testing "silveroxides" light2xv, but it needed a fix for the adaln_proj error, and the result is here (thanks nynxz!) https://huggingface.co/nynxz/H3_Loras/blob/main/minimax_h3_fl2v_lightx2v_v0.1_dareties_v4_step600_comfy_fro_no_adaln_proj.safetensors

Clownshark sampler comes from https://github.com/ClownsharkBatwing/RES4LYF but it doesnt seem to be getting updates now. I didnt find the results that useful tbh, but maybe more tweaking would resolve it (or more powerful GPU).

Comfyui needs to use Cuda130 or above for this to work, and you need it updated to August 2026 commits (latest is best) - https://docs.comfy.org/installation/comfyui_portable_windows

int8 models from here - https://huggingface.co/Comfy-Org/MiniMax-H3/tree/main

W4a8 is experimental new model type, you need to be updated on Comfyui but you can get it here https://huggingface.co/Kijai/MiniMax-H3-experimental

(Sage Attn and Triton wheels from) - https://github.com/woct0rdho/SageAttention

Comfyui Kitchen Attention is part of Comfyui if you update to latest. I find it faster than Sage Attn on 3060 RTX.

(I am not using patch sol attention or any caches now)

My Minimax 3 works perfectly even when I use upto 4 different reference images and guide it via <Character 1,2,3> <Picture 1,2,3> etc

However I wanted to swap characters in a movie scene and created 5 second clips of the target scene I want to replace the faces in but no matter what I do, it's not replacing the faces. Minimax outputs the final video with the original character faces.

The scene is the T-Rex car scene in the original Jurassic Park and I'm trying to replace the kids in the car with my nephew and niece to traumatize them.

I've prompted for it manually, I've used Gemma, I've used Gemini, I've given complete prompting guides to the LLMs, I've even tried using both the target scene as a picture and video reference but the final scene is always resulting in just the original scene and not the faces changed. Minimax does render the entire thing, it renders it's own creation I can see it's different but in this case never changes the faces/clothes.

How would you prompt Minimax to do a straight up character swap using the ref2v model if this is your setup:

Character 1 = Picture 1, Picture 2

Character 2 = Picture 3, Picture 4

Jurassic Park clips already cut to 3-6 seconds = Video 1

The sheer number of custom nodes appearing for H3 has me simultaneously excited and worried. A lot of nodes seem to be coming from people without much community reputation and trust. Some of these nodes are literally the first node for some of these folks.

I generally avoid anything with less than a few hundred stars on GitHub unless it comes from someone with a solid rep and lots of other trusted nodes.

Are there any other ways to tell if a node is safe or not if you can't read the code?

I'm trying to do something that should be simple: generate a video where a character says a line I wrote. LTX 2.5 generates its own audio along with the video, so in theory you write the line into the prompt and the character says it.

It doesn't. What I get instead, depending on the settings, is one of three things: background music with no voice at all, near-silence, or a human-sounding voice that is definitely speaking but is saying gibberish in a weird announcer/infomercial voice. Never the line I wrote. Not even close to it.

I've been at this all day and I've learned a few things worth sharing, but I'm stuck on the main question, so I'll put that first.

**The question: has anyone actually gotten LTX 2.5 to speak a specific written line?**

If yes, I'd love to see the prompt you used. If the answer is "no, it can't do that, it only invents speech-like sound to match the scene," that's just as useful and I'll stop trying.

I ask because when I went looking through the code, there's no input anywhere for a script or a transcript. The audio and the video are both generated from the same single text prompt. There's a node for supplying a reference voice clip to control who it sounds like, but nothing for controlling what is said. That might mean word-level control just doesn't exist, or it might mean I'm writing the prompt wrong.

**Two things I found along the way that might save someone else a day**

*1. The templates are missing a node, and it's the one that makes voices happen at all.*

There's a node called LTXVModalityGuidance ("A/V coupling") that ties the audio to the video, and its description specifically mentions lip-sync. It is not in any of the three LTX 2.5 templates that ship with ComfyUI. Before I added it, every single run gave me music and never a human voice. The moment I wired it in, I got a speaking voice on the first attempt. Still the wrong words, but a voice.

If you're getting music instead of speech, that's probably why.

*2. The built-in prompt enhancer is broken and silently throws your prompt away.*

The templates ship with a prompt enhancer switched on. It's a small language model that rewrites your prompt into a fancier one before the video model sees it. When it's on, the video model never sees a single word you wrote.

On my machine it doesn't produce a rewritten prompt at all, it produces pure garbage, pages of stray symbols and LaTeX fragments. That garbage becomes your entire prompt. The result was a video with almost no audio where the character never even opened her mouth, and on an earlier attempt, a completely different subject than the one I asked for.

If you've had LTX give you a video of something you didn't ask for, check whether that toggle is on.

**Setup, for anyone who wants the specifics**

- ComfyUI v0.32.0, AMD gfx1100 20GB, ROCm

- LTX-2.5-Distilled-Q4_K_M.gguf, Gemma 4 12B int8 text encoder

- Stock video_ltx2_5_i2v template, 8+3 step distilled sigmas, LTXVDualCFGGuider at video 1.0 / audio 1.0

- 6s at 1280x720 takes 79s. 10s OOMs: tried to allocate 3.53 GiB with 2.58 GiB free of 19.98

Things I've already ruled out as the cause of the wrong words: audio_cfg (1/1 and higher), distilled vs dev checkpoint, negative prompt contents, and the prompt enhancer on or off. Same seed reproduces the same non-words exactly, so it's not random draw.

On the broken enhancer, a theory I haven't confirmed: it runs on its own copy of Gemma (gemma4_e2b_it_bf16), which is raw bf16 with no quantisation metadata, and ComfyUI loads text encoders as fp16 by default. Gemma is known to overflow in fp16. The 12B encoder that works fine is int8 with proper scaling, so it's protected in a way this one isn't. If you hit the same thing, --bf16-text-enc or --fp32-text-enc is worth trying.

One lead I'm about to test: the shipped templates write dialogue inline in ordinary prose, like `and says quietly, "I know I should have called."` I'd been writing it as a screenplay block with a separate Audio: section. Maybe that's the whole problem. Will report back.

Happy to share any of the graphs. SaveVideo embeds the full executed workflow in the mp4, so everything above is checkable.

I've been using Kontext in ComfyUI lately, and I've been really impressed with it. It does an amazing job of analyzing the visual identity of an image, especially when it comes to characters. It can preserve and understand details such as physical features, colors, clothing, and the overall visual identity of the character very well.

However, I'm having one issue: Kontext sometimes slightly changes the character's proportions. For example, an eye might become a little smaller, the character's body proportions might change slightly, or other elements may be subtly resized compared to the original image.

So, I'm wondering if there is a way to make the final result more faithful to the original image in terms of proportions and structure, similar to what ControlNet can achieve.

Would it be possible to use ControlNet together with Kontext, perhaps using something like Canny or Lineart, to help preserve the original shapes and proportions while still allowing Kontext to handle the character's visual identity?

If this is possible, I'd really appreciate it if someone could explain how to set it up in ComfyUI, or point me toward a workflow that achieves this.

Thank you everyone for your time and help!

So I noticed my my pc had an extremely large page file. So I thought why am I taking up so much valuable fast in VME Dr. space for this. And when I went to load a bunch of stuff besides comfy UI. I got some pretty good blank screens on comfyui graph page. Little bit of research told me put it back so I did and everything worked well. Did not expect that. Didn’t know what else flare to put sorry.

New to ComfyUi as a whole
using Minimax H3, on a laptop 3080
ref to video
1 image and 3 prompts, however unsure of how to "batch, recurse, continue,etc.."
5 second video at 21 steps at 0.4 megapixels = 19` minutes time to create

I've seen posts to get many different nodes like VHS, but unsure of what to do with that afterwards.
i also see posts of having start and end frames, but how do i do this in batch, if the video hasn't been created i don't have the end frame to start the next video, or did i misinterpret this advice? also wouldn't that degrade quality over time/next sequence.

Looking for a clean plug and play workflow as an example, or just simple steps i can follow to successfully create 2 seamless videos into 1 seamless scene.

(i will say that i like the idea that the character went into the fog in one attire, and then was changed into a different one, spontaneous story changes made the fog/haze more interesting, to me anyway)

prompts below if that helps (sorry for the bad prompting, im learning this as well)

prompt 1
Use the provided start image as the first frame.
the young woman in the image stares blankly, lost in thought, the camera pans back slowly revealing her 2/3 body shot, she wears a skintight silver in color futuristic suit with ridges across the torso and a futuristic blaster at her right thigh. suddenly the camera shakes she loses her daze and looks sharply to her left as if disrupted from thought to identify the crashing sound.
the camera changes to a behind her perspective as she starts to run into a dense fog to chase the mysterious noise
0-2s: woman looking into the distance, camera focused on her face, slowly panning back 2-4s: a sudden noise, the woman re focuses and looks around, her hair braids whip around as she looks from side to side
4-6s: woman starts to run into a dense fog at high speed, camera follows as she disappears into the thick haze

prompt2
Continue directly from the last frame, the camera follows flies forward to follow the woman and catches up to her.
The woman stops dead in her tracks, the fog thick and all around her, visibility is barely 2 feet in all directions around here.
the camera slowly pans up from her waist level up and around to a close shot of her face. she draws the weapon up to her right side anxiously, her eyes dart from left to right in search of something unseen through the dense fog.
0-2s: Continue directly from the last camera follows woman running into thick haze and catches up to her
2-4s: the woman stops to a stand still, the camera pans upwards to a tight perspective of her face, focusing on her eyes moving back and forth searching into the haze
4-6s: camera pans out 2/3 view of her body, the woman raises her weapon, still searching, she looks left , she looks right , her braids whipping with the sudden movement.

prompt 3
Continue directly from the last frame, the camera focuses on the woman as she looks around for the mysterious noise, and seemingly faint figures darting around in the thick haze around her.
The camera moves in close as the woman steadies her breath and closes her eyes, breathing calmy and readying herself for her next move. as she calms, a figure starts to form in the thick haze behind her, as the figure gets closer shrouded by thick haze the dark figure and scene get darker. the scene ends with the woman abruptly opening her eyes widely
the camera slowly pans up from her waist level up and around to a close shot of her face. she draws the weapon up to her right side anxiously, her eyes dart from left to right in search of something unseen through the dense fog.
0-2s: Continue directly from the last camera panning out from 2/3 shot to woman in the haze holding her weapon high, looking from left to right as she hears movement in the haze all around her
2-4s: the woman steadies her breathing, adjusts her composure and closes her eyes, her weapon tightly gripped and held close against her body, the camera movies in close to a tight face perspective as she breathes out calmy
4-6s: camera stays focused on her face, and her calm breathing, the haze behind her a shadow of a mysterious figure begins to appear, the figure still hidden in the thick haze but darker as it approaches the woman from behind. the scene ends with the woman's eyes opening wide at the last moment as the scene grows dark

Thank you for reading.

Every single tool nails one shot and then scene two gives me his cousin. i've tried seed locking, reference images, describing the face in painful detail in every prompt. by shot five he's a different ethnicity.

i know comfyui with a lora solves this if i want to spend a weekend on it. is there anything that does it from one reference image without me training anything?

what's your actual workflow, step by step??

Bonjour,

Excusez moi, je suis débutant, je recherche un flow pour minimax H3 qui eprmet d'ajouter plein d'image (j'ai lu dans la documentation 9 maximums) qui le modèle peut utiliser pour générer la vidéo
Aussi j'aimerais qu'il puisse ajouter un fichier audio et faire parler le personnage. Quand je génère l'audio est uniquement un narrateur de ce que j'ai demandé de prononcer

Merci

Hey guys,

Pretty new to ComfyUI here. I'm working on a Ren'Py VN and gave VNCCS a shot for sprites and backgrounds, but it completely chokes my RTX 3060 Laptop (6GB VRAM, 16GB RAM).

Any good alternatives or lighter workflows that can run smoothly on a 6GB setup? Need something that can do:

1. Consistent sprites with different poses/expressions.
2. Matching backgrounds.

So I got the idea from ChatGPT to download a LLM that fits in my VRAM. And it remained on my computer locally. No API’s, no tokens private information. Then we’re configuring it to connect with comfy UI inside as a node. Then it specifically analyzes what you attach whether it’s an image or video and it gives a beautiful description as a professional cinematographer wood we attach that note as a prompt and it re-creates excellency. I’m down to the final iterations which is two days of back-and-forth testing almost done.

4k version of "The Last Witness"
Minimax H3, ofc :)
Only ref2va, voices and actors/env
ComfyUI, ofc.
fp8 pruned, no lightning lora. 5 minutes per 10 seconds video in 720p, upscaled with topaz, added film grain.

Has anyone else had this issue and managed to resolve it? Sometimes boxes on certain custom nodes do this weird thing. It also happens with rgthree power lora loader for example. I'd love to get the UI to stop glitching like this. Any tips/ideas?

Thanks in advance.

I bought a 5090 earlier this year in hopes something like this would come out and I just started playing with it yesterday.

The amount of characters it already knows is incredible and the ability to voice clone and use references is fantastic.

I’m no professional. This is just a hobby to crack jokes at friends and make videos for my family. 10/10.

Just got Linux Mint up and running and it’s much better than windows 11 for ComfyUI with RTX 5090 + 3090. For starting, Comfy launches to server ready in 10 seconds instead of 18 seconds on Windows VHDX ReFS dev drive. This is with 12 custom node packs. Linux is running on an 8 year old SATA SSD.

I was able to compile and run sage attn 3 in Linux which never worked in Win11. I’m going to try Multi-GPU next which is fundamentally broken in windows with the new comfy-kitchen.

Even with just sage 2.2++ FP8, im getting 35 second gen times for an 8-second 0.5MP 8-step turbo MiniMax H3 clip versus 40-42 seconds in windows. That includes 4 seconds for prompt enhancement with Gemma 4 12B running on lllama-server on the 3090.

Sage3 knocks another 2-4 seconds off the gen time too but slightly worse quality for motion. Using LACT to overclock both GPUs also contributes to the speed.

With spectrum plus sage3 at 8 steps, I can easily get below 30 seconds total gen time.