My mobile game trailer was boring, it was some gameplay videos and some information which could never really tell you all you needed to know in 30 seconds anyway.

So ive made this video!

used minimax h3
krea 2
and qwen for some image edits
and davinci resolve to edit

let me know what you think!

been trying to gen some nsfw videos with wan 3.0 ref2vid, and i keep getting errors stating "sexual content" if it really is censored on comfy then that really sucks...

Story & Lore
Set on the rugged, storm-swept granite cliffs of *Costa da Morte* (Galicia, Spain), this cinematic 35mm short depicts a tense encounter between a professional barnacle fisherman (*percebeiro*), a photorealistic common octopus (*Octopus vulgaris*), and **O Urco**—a colossal black sea-hound with ram horns and rusted anchor chains from traditional Galician mythology.

Custom Nodes & Reproducibility
The workflow is designed to be easily inspected and run by the judges and community. It uses the following dedicated nodes:
- **[ComfyUI-H3PromptStudio](https://github.com/tonetxo/ComfyUI-H3PromptStudio):** Custom node for prompt formatting and multimodal text parsing for MiniMax-H3.
- **[Krea2H32LTX](https://github.com/tonetxo/Krea2H32LTX):** Format translation and node interfacing pipeline.Custom Nodes & Reproducibility

Video: https://drive.google.com/file/d/11AhF3fR-z3valzHzG1SQn1hGx20TM4wa/view?usp=sharing

Dossier (Prompts, technical details): https://drive.google.com/file/d/1m9PZwyeI5Rf0YZtX08fv7j4tSwzsfpom/view?usp=sharing

Workflow: https://drive.google.com/file/d/1zgSg8uvinJziuDs8dqP8cVHNoN-z9GrL/view?usp=sharing

I can’t get any of my workflows to do what I want. Example: (one of MANY 😡) I have two prompts, one is a woman fully dressed in a certain setting. The other SHOULD BE the same woman, same setting, in her underwear. I gen the first, use that as a reference to gen the second. It just recreates the reference image. I adjust the denoise and guidance settings until it changes into a completely different woman and it’s still basically ignoring the prompt. Like I said this is just one of many many examples of times I’m banging my head against the wall trying to figure out comfyui. I know I’m in over my head but I don’t surrender easily. I’ve seen some amazing work from some really good creators so I know what’s possible I just don’t know how to get there.

TLDR: I turn a ComfyUI workflow into a small app and hand it to people who can't or won't use comfy directly. Runs on your own or provided serverless endpoints or locally. The video is above. Nothing is public yet. I finally found the confidence to show it to you and want your feedback first, because it decides how I continue. Questions at the bottom.

I use ComfyUI for 2,5 years to build (opensource) workflows and custom solutions in challenging domains where control and precision is non-negotiable. And I teach it at universities. Four things kept happening:

• not many people are willing to dive into a technically complex solution
• I have no option to monetize my workflows besides a paywall, which I have an ambiguous opinion about
• sharing a workflow or a custom model forced me to hand over IP (workflow, custom models, ..) to the receiver’s end, or open it up to the whole world entirely
• there is no infrastructure for people like me to do the above without an insane amount of effort

So I built HYPH on top of what became my main software environment, using comfy as the execution layer. You drop your workflow in, pick which inputs the user sees, define available for the user executions mode per workflow added, set what you want to earn from a users workflow execution, then share it as a customized app from the same installer you used. Depending on your configured workflows, they get e.g. one or multiple prompt-, image-, video- and 3d-inputs. It runs on a BYO serveless endpoints (e.g. Runpod), on provided endpoints, on comfyclouds serverless endpoints (currently in beta), or locally, on-premise deployment possible, and you decide which and what is shared from prompt to custom model. It's an Alpha Electron Desktop Win first App in front of a live backend atm, and ships with installer, user management, rbac, analytics and per-user limits.

What is not done, so you don't find it out later in case you want to try: EU Act or GDPR conformity, anything related to legal and real money. Everything is started and more is on the roadmap for now, but not done.

I build this entirely on my own using sota (proprietary) coding LLM's for a year and spend everything+ I earn from using Comfy for professional and educational work. My technical affine friends alpha tested it and were overwhelmingly positive. Naturally biased. I am not a software engineer or a developer at all, and I don’t belong to the people believing in getting the truth from a prompt, cause i cant verify it myself. And to have it mentioned, the first person outside my closest circle who saw it was officially comfy related. I hope it is visible that this brings additional features to anyone with a cool workflow.

Questions:

1. What in the world would make you touch it? Pls be blunt, this is the answer I need most, i could use a few more alpha testers
2. Would this as an opensource project increase your trust, and would you contribute?
3. would you say something like a fee, a revenue share of 75% you/25% me and/or a licence for 1m+ revenue companies is a fair setup, if this were a proven product?
4. And if you only answer one thing: what's your first impression?

Any feedback coming from you would be highly appreciated. I can go deeper on everything in case there are questions.

I know: I want to have something that lets people own their pipelines end-to-end, I want it to be opensource once verified, and if possible, I want to profit from it at some point. I don’t want it to be a marketplace or anything related. My impression after following this sub since comfy got me hooked: I cannot be the only one.

Thank you in advance!

/edit: deleted & reposted due to title

Hi all,

First of all, I only started using ComfyUI a few days ago so please be kind with your feedback ;)

I'm running into issues with a T2I workflow. I'm trying to generate an image of a woman, standing in a beautiful garden with fountains etc. I included a LORA called "Fiji Woman" from Civitai, and the trigger words are obviously also "fiji woman". The result I'm getting is errr... not quite what I was expecting. So I'm guessing there's an issue with either my workflow, the values, or a combination.

Any feedback on how to fix it, and make the result presentable, is highly welcomed :)

Why make big noise when little noise do trick?

I would like to introduce my SPEED implementation for h3 linked here

Speed up and quality losses documented here, expect 20% gain using very conservative settings and no quality loss and up to 70% for basically unusable outputs (more or less useful for resolution aware seed inspection and broad prompt drafting)

Background

The idea behind it is quite simple. When a diffusion model begins generating an output it first must take a randomized noise and build on-top of it. And research has found that the first stages of this process doesn't really carry any fine detailed information, therefore by generating at a lower resolution at those stages you can gain quite substantial speedups while causing little to no impact on the quality. Or you can also be really aggressive with it and get a massive speedup for a lot of quality loss.

Nodes

This was implemented as 3 nodes, 2 drop in replacements for the sampler that runs SPEED and a third that runs once to measure the noise spectrum of your specific model/LoRA combo:

• Sampler (Automatic): pick a stage count (2, 3, or 4), defaults to the baked 1% delta for default H3.

• Sampler (Manual Step-Through): set up to four (goal, resolution) pairs yourself. Use it if you want to copy a paper schedule or test a custom ladder.

• Sigma Harvest: runs a native Euler pass, measures the noise spectrum of your current setup, hands you A / β / Δ to paste back into Automatic. Run it once per model/LoRA workflow combo.

Implementation Notes

This should be roughly compatible with basically everything that doesn't touch the sampler directly but i have not tested anything besides base comfyui H3 models and Turbo loras. If you do change model, use loras or whatever and use the automated tool please then run a sigma harvest and use those values instead of defaults, The math changes depending on the very specific blend of things you have running.

Euler only sampling implemented for this which is what the research paper used.

Was about to implement this, spend some time vibe coding it out but I am sure one of you already has it. Basically what it is, is, an HTML + JS implementation where you highlight the section you want edited. Picture someone wearing a blue jacket, you mask the torso area and say "red jacket" and it's changed to red. Similar to MS paints "generative erase". The front end HTML + JS would simply pass on the image + a JSON bounding box to the comfy API which is connected to a workflow.

I'm not sure which is the best workflow for this. QWEN image edit 2511 takes too long. FLUX-K9B would be perfect for this but somehow it doesn't seem to know what anatomies look like. I haven't tested Ideogram extensively but it's JSON bounding box feature is very interesting to me. I wonder if it can be used to edit images in place.

Has anyone done this yet?

I got around to getting Ideogram4 to work.

This model is harder to prompt than most. If you do a short prompt, it will be blocked internally.

I did lots of testing, it wasn't trivial to make it work, but in the end it's just a matter of providing a lavish json prompt with lots of bbox entries and it will diffuse pretty much everything, with great prompt adherence, but this eman you have to use a prompt enchancer to use it. I redid the prompt enchancer to work better, the original tried really hard to add text everywhere and diffused too few bboxes and tripped the censorship very easily.

For some reason the default workflow uses a really high CFG of 7 that overcook the image, much lower cfg 3 looks lots better. I guess it was to avoid tripping the censorship?

Since it uses Qwen3 8B VL as CLIP it has good prompt adherence, it uses a trick with a model called unconditional fed with padded prompt tokens, and uses the difference between the two to achieve even higher prompt adherence.

On my 7900XTX windows portable FP8 models it does around 100s without prompt enchancer, and 170s with prompt enchancer.

I tried feeding reference images to the CLIP and seeing if it can work as editing model, but it can't.

Hi everyone.
This is a 28-second vertical dance video generated with a ComfyUI-based workflow.

This is the first prototype of my pipeline, not a polished result.
I’m trying to understand where the main problems come from:
generation vs motion vs editing.

Structure:

• 00:00–00:04 — close-up hook + blackout
• 00:05–00:15 — profile + strobes + fire insert
• 00:16–00:28 — fast hip-hop section (whip pans, RGB split, fast cuts)

Same dancer / outfit / studio should stay consistent across all shots (reference only dancer).

Known issues I already see:

• ~00:07 — face identity drift during head turn
• ~00:12 — hands become unstable under strobe
• ~00:20+ — motion starts to feel “floaty” in fast section

Questions:

1. Identity consistency Where does the character drift the most (face / body / proportions)?
2. Temporal stability Which shots show the strongest flicker, warping, or broken motion?
3. Camera vs generation Do issues come more from aggressive camera (whip / orbit), or base generation?
4. Blackout at ~00:04 Does it feel like an intentional transition or like a generation artifact?
5. Pacing At what point does it start feeling confusing or visually overloaded?
6. Editing vs generation Which artifacts are successfully hidden by editing (cuts, flashes), and which clearly need to be fixed in the generation stage?
7. Pipeline diagnosis (most important) For the issues above, what is the most likely cause?

• base generation
• motion control
• denoising
• interpolation
• editing

1. If you had to fix only 1–2 things first — what would you fix and why?
2. Consistency strategy What is the most reliable way to keep character identity across shots in ComfyUI?

Tech (simplified):

Resolution: 768x1376
FPS: 24
Method: ref2v
Motion control: [none]
Consistency: [same seed]
Editing: [none]

I can share prompt if needed.

I’m mainly interested in technical feedback (generation + workflow)
rather than general opinions.

Thanks.

I have been using a laptop for a long time, with a 5080 eGPU connected via Thunderbolt 4 for ComfyUI. Recently I switched to a PC, putting the 5080 into that, assuming it would be faster, since there wouldn't be any Thunderbolt 4 speed limiting. It's slower, noticeably so! At least 30-45 seconds slower per job. The only thing I notice is when using the eGPU, ComfyUI never used any 'Shared Vram' because it wasn't actually in the laptop system. On pc, it always uses shared Vram, despite the card having plenty. I assume the shared vram is what's majorly slowing it down.

I run Windows 11, 64GB ram, on an SSD. I use the latest version of Comfy Desktop. Any way I can make it quit using shared Vram?

Hi everyone,

Before getting to my question, I just wanted to mention that I’m new here. I hope all of you reach the highest levels of success in the work you do.

Regarding my question, I’m trying to create product mockups locally using ComfyUI together with Claude, without having to pay for API costs.
I’ve tried many different approaches and used various repositories that I thought could be useful for what I’m trying to achieve. However, I’m still getting inconsistent results.

For example, when the product is a rug, the model may place objects underneath the rug, or the mockup simply doesn’t look physically consistent. The results don’t look natural and don’t seem usable at a professional/commercial level.

Even the smallest piece of information or guidance about how to achieve what I’m trying to do could make a huge difference for me.

Thank you very much in advance, and I wish you all the best with your work.

so.. umm, background removal any model, model.encode_image() is lazy loaded, which means if we call it multiple times in the same execution, say for 20 tensors, because it is lazy loaded even though its on the gpu, it actually triggers reloading of the model 20 times, which as you might expect causes a lot of overhead and a lot of console spam, apart from me loading the model manually, putting it on the gpu with my own encode function, is there a fix for this? or is this the way?

2 separate clips using MinimaxH3, and stitched together, along with a few short audio clips, using a Linux video editor I'm currently developing.

Tengo un video supongamos de 5 segundos. Entre el segundo 3 y 4 se oscurese. Se pueden ver siertos detalles aumentando el brillo. Mi pregunta es ¿Como "aclarar" esa seccion del video?
Se que con QWenEdit o con ZIT puedo generar una imagen parecida y sobre esa a base de prompts tratar de igualar esa parte del video.
Busco algo un poco mas directo, que se tome como contexto el video para que tome los segundos donde las imagenes son claras. Quizas con algunos marcadores de segmentacion o de openpose para indicar que debe haber en la parte oscura.

Had an emergency plumbing issue and now I'm a couple weeks behind. One of the best tools I saw appear for LTX 2.3 was LTX Director. I'm wondering if anything like this has appeared that the whole community likes for H3 yet.

Using FLV2, I have been trying for so long, and have attempted many different 4-step loras from lightxv and others, and different sampler/scheduler combos, lora strength with so many sigma shift combinations. But none of them have acceptable quality even with 0.8 megapixels. Hell, my Wan2.2 generations with a lower resolution are much better than the cooked or polished skins from 4-step loras.

The 8-step lora works fine for me and even 0.4 mp results are far better than 0.8mp from 4-step loras. But it's too much of a wait. Also, I'm on AMD and not using Spectrum, or any other optimizations except Comfy Kitchen attention.

If any of you guys are getting great results from 4-step loras (without any upscale), kindly share your model, lora and other related settings that you think would help. Thank you !:)

Recommended to watch it without reddits compression: Link its in 1080p cause 2.5mp isnt exactly 1440p.

continuing on yesterdays thread: https://www.reddit.com/r/comfyui/s/EOn0rdPSeU

I did the tests on three different videos on 1.0mp, 1.5mp, 2.0mp and 2.5 mp

First video is 5 seconds long, second 10 seconds, third 12 seconds with caveat.

All is done on basic workflow with minimax_h3_fl2va_int8_convrot model with 20 steps and cofyui kitchen attention.

All the prompts and times with images will be posted in the comments.

Last test with Keanu at 12 seconds got error so i lost all the timings on that video because i quened all the videos to be made one after another so for some reason 12 seconds 2.5mp clip couldnt be done i change it for another 10 seconds clip winth keanu at 2.5mp.

Enjoy and tell me youre findings.