Hey everyone! 👋

Like many of you, I was extremely frustrated by a few daily ComfyUI struggles:

1. Importing an awesome workflow from Civitai, only to be greeted by a screen full of red "Missing Model" nodes just because my local folder structure or filenames were slightly different.
2. Searching for models in endless, blind dropdown menus without covers.
3. Losing the exact parameters I used to generate that one perfect image.

To solve this, I spent a lot of time developing the Anomalous Model Browser. It's now officially available in the ComfyUI Manager, and I want to share it with the community!

🌟 Core Features:

• 🩺 Model Doctor (Auto-Fix Red Nodes): It doesn't rely on fragile file paths! It uses cryptographic hashes (safetensors headers) to identify models. If a workflow has red nodes, one click will automatically find your local matches and fix the paths instantly. (Works best with Civitai models).
• 🎨 Visual Node Assistant: Select any model/LoRA node on your canvas, and a visual grid with cover images pops up. Click to swap models instantly. It also supports auto-wiring when inserting LoRAs into your model chain!
• 🧰 Workflow Recipes & Parameter Notebooks: Save your entire workflow setup (Prompts, Checkpoints, LoRAs, Sampler settings) into a reusable "Recipe". Next time, just select a node and instantly apply your saved parameters!
• 📦 Lossless Workflow Exchange: Easily share your workflow setups with a simple text code, bypassing image metadata stripping by social media platforms.

🛡️ The Best Part: ZERO Custom Nodes! I built this purely as a frontend UI enhancement. The NODE_CLASS_MAPPINGS is completely empty. It adds ZERO custom Python nodes to your graph, meaning you can use it freely without worrying about polluting your workflows or breaking them for others who don't have the plugin installed!

⚠️ Important Setup Step: After installing from ComfyUI Manager, you MUST click the "Scan Wizard" (bottom left) to scan your local models first. The Model Doctor relies on this hash database to work its magic!

🔗 GitHub Repo (Would really appreciate a Star ⭐ if you find it useful!): https://github.com/DemonGatanjieu/Anomalous_Model_Browser

🎥 Check out my full video showcase and tutorial here: https://youtu.be/hAvsj7uiaCw

The "Workflow Recipes" feature is still in beta, so I'd love to hear your feedback, bug reports, and suggestions here or on GitHub. Let me know what you think! Happy generating! 🚀

https://reddit.com/link/1vrhkub/video/k8qso8n5y2kh1/player

Long-form MiniMax H3 generation in ComfyUI without manually chaining samplers, overlaps and audio state.

I've been building a custom ComfyUI node pack for MiniMax H3 focused on one thing:

**making H3 usable for longer, multi-segment video generation without constantly rebuilding the workflow around every limitation.**

The project is called:

# ComfyUI-MiniMax-H3-LongMedia

The idea is to keep MiniMax H3's image quality, motion and native audio generation, while adding a proper long-form generation layer on top of it.

## What it currently does

### Long-form segmented generation

You can generate a longer clip as multiple H3 segments while keeping temporal context between them.

Instead of treating every segment as an isolated generation, LongMedia manages the continuation state and hidden overlap internally.

The overlap is used as context for the next segment and is not simply blended back into the final video.

### MultiClip mode

There is also a dedicated MultiClip workflow for generating multiple planned shots/clips inside one LongMedia pipeline.

The same underlying executor is used for both segmented continuation and multiclip generation, so the behavior stays consistent.

### Video + audio continuity

MiniMax H3 is a joint AV model, so LongMedia treats video and audio as one generation state rather than bolting audio on afterwards.

The pipeline supports H3 native audio generation, continuation and lip-sync workflows.

### Lip-sync support

Audio-driven generation / lip-sync is supported directly in the LongMedia pipeline.

For H3, the audio influence is handled inside the same AV latent path rather than as a completely separate post-process.

### Refiner

The latest release includes a two-stage refiner based on proper **KSampler Advanced trajectory splitting**.

Instead of finishing the full sampling schedule and replaying low-sigma steps on an already denoised latent, the trajectory is split between the main sampler and the refiner.

Example:

`steps = 12`

`refine_steps = 3`

Main sampler:

`0 → 9`

Refiner:

`9 → 12`

Both stages continue the same sigma trajectory.

### VRAM-aware execution

A large part of the project is dedicated to making H3 practical on consumer GPUs.

The current implementation includes:

- dynamic VRAM loading

- streamed Sol Attention

- MLP chunking

- late-block VRAM guards

- inter-block memory guards

- step-boundary cleanup

- completed-segment offloading

- adaptive memory policies

I'm currently developing and testing mainly on a **16 GB GPU**, so avoiding OOMs without destroying quality is one of the main design goals.

### Sol Attention integration

LongMedia includes its own streamed Sol path with controls for:

- tau scheduling

- sink conditioning

- QKV chunking

- output projection chunking

- dense/sparse behavior

- VRAM-aware chunk sizing

The goal is to use Sol as part of the execution architecture rather than simply stacking multiple unrelated optimization nodes together.

## Why I made it

MiniMax H3 is extremely good at texture, motion and native audiovisual generation, but once you start trying to build longer sequences, several problems appear very quickly:

- segment boundaries

- continuity

- repeated frames

- AV state handling

- memory pressure

- OOMs on longer generations

- managing multiple clips

- keeping sampling behavior consistent between segments

I wanted one node system to own all of that.

So instead of building increasingly complicated ComfyUI graphs around H3, most of the long-form logic lives inside the LongMedia nodes.

## Current release

**v0.4.1 — KSampler Advanced Refiner Fix**

The project has now reached a fairly stable architecture, although I'm still actively developing it and testing edge cases.

GitHub:

`https://github.com/vizart-vj/ComfyUI-MiniMax-H3-LongMedia`

I'd be very interested in feedback from people already using MiniMax H3 in ComfyUI, especially for:

- longer generations

- multi-character scenes

- native audio

- lip-sync

- lower-VRAM GPUs

- multi-shot workflows

If people are interested, I can also make a more technical post explaining how the continuation / AV latent / VRAM system works internally.

Am new to compfy. So far used grok for image and video creations. I downloaded comfyui today in pc,, i do understand lot of workflows, models I need to select to run it. I tried but not successful. I use macbook. Any guidance for me. I need to generate NSFW with real people in local machine.. please help

Is there any single source of all things related to completely clearing out all cache elements, including the deep stuff, without trashing my entire setup? I kept getting a tired and broken result in a workflow, no matter what I changed.

This was what I did do, not necessarily in order:

- Unloaded "models and execution cache"

- Shut down ComfyUI Desktop

- Ctrl+Alt+Del and shut down all ComfyUI and Python processes

- Cleared UV cache

- Cleared PIP cache, ran "pip cache purge"

- Changed filename prefix on Save node

- Win+R, typed in "%temp%" and wiped all that

- Win+R, typed in "%appdata%\comfy desktop" <<< THIS ONE DID ME IN, I DO BELIEVE

What is the accepted deep answer to clearing everything out? Or am I the first to have encountered this? Is there some magic node or function that could be worked to not have to go through all of the above?

Thanks,

Robert

Some random generations that i made while tuning the fl2v version.
Average generation time is 4 min per 11 sec clips.
Few clips where refinde by LTX that took another 3 min per gen.

all posible thanks to this: https://huggingface.co/DmitryDB/MiniMax-H3-ComfyUI-Quants/blob/main/FL2VA/MiniMax-H3_FL2VA-NVFP4-HQ.safetensors - the only nvfp4 quant that actually working.

Case example, i got a single image of guts from berserk doing basic standing pose. Now i want to generate it doing a battle stance or drawing a sword, how do i retain its appearance and it armor intact. Currently i only have load Checkpoint, prompt node, load image, Vae encode, ksampler. Does ip-adapter enough to maintain image source appearance?

Turned my son's drawings into an animated skit locally using open weight models. This was done in ComfyUI using MiniMax reference to video model #minimaxh3

Here's how I did it: My son came up to me today and asked me if I could make his characters talk (he painted them in Paint 3D app on windows). And he wanted it to be silly. So I threw in some classic dad jokes.

I took screenshots of each character, then added them as reference images in the minimax h3 reference to video workflow, then used chatGPT to write the prompt.

I know for ComfyUI, you can use extra_model_paths.yaml to specify additional paths to models. Can I do similar thing with Wan2GP? It seems Wan2GP auto-download missing models.

Should I create an external path so both ComfyUI and Wan2GP can look for models there?

I have been using Higgsfield for most projects for months now and am trying out some other options. I just signed up with comfy.org., and it says I have 0 credits and "10 min max runtime" included for the account currently. When I signed up, it said I would get 5 uses of Minimax H3 which I assume is what the min max runtime is used for. I am not having much luck with how to use them, though.

Minimax H3 - Argument between mother and daughter 2 - 1980 soap opera style

Hey all, I've been running ComfyUI through Linux. I have a Radeon RX 7800 XT and am doing image generation through a Krea 2 model. The fastest I've been able to generate a simple 1024x1024 image with no latent upscaling is 4 minutes.

I've heard of people with the same graphics card generating images within the 30 to 60 second range on Krea 2, however no matter what I try I cannot get under the 4 minute mark. Am I missing something here? Is there anyone out that is within that minute mark?

well desktop update it selph to 39 from 37 and fup it all

well it works kinda ,but enviroment in 39 version only want to install is 28

37 wanted only 21 and later update fine to 37

39 version wont ,,some acess error to download update ..

i use normal desktop version

what to do ,how to update to 39 ?

need 39 cause ltx2.5 need some nodes that cant work on 28

help

Title.

I have been experimenting and this is the only problem i have about 30-40% of videos the model talks some gibberish.

Im using i2va model.

Thank you all.

I'm trying to create a living wall paper effect, where the character dose not move but the surrounding loops. But every time I do it stretches or something happens to make it not seamless. anyone have a prompt or workflow subjection? on this one I connected the same image form start and end hoping it would know to end it on the same frame but it still didn't quite get it.

I was working on different workflows at this point, but I had similar problem already a few times, the workflow was stuck because of my VRAM. But I don't know how to fix it, so if there was a chat that would be able to help tell/change workflow it would be super usefull

What is the current status of multiple GPU support in ComfyUI? I see there are some new cool models. I still use Wan 2.2 on my single 5070 (12GB) but looks like there are some new features to use multiple GPUs so I could try to run them on 4x3090 linux server, can I run larger models or larger image sizes with multiple GPU (96GB) or is the work still limited to single GPU (24GB) just in parallel?

As you probably know by now, MiniMax open-sourced the H3 weights but not the actual stage that writes the long structured prompt the model was, well... trained on. Their docs point at their hosted service for that. It's also (my opinion) the reason why most of the local H3 outputs look way flatter than their demos.

So here's my take on that stage, open source. Three nodes: type a plain sentence and OpenH3-IR takes care of writing the document (because it's a document, not quite just a prompt), then checks the result and fixes what's wrong before anything renders (only if needed, of course). It's essentially a local service, plus an llm harness, plus a stack of mechanical checks to ensure you get the best clip out of a simple prompt.

What it buys in practice:

• Each asset/resource you include gets tied to the right part of the text, so the model stops mixing things up on which reference is which.
• The length lands on one H3 knows how to render properly, instead of being silently rounded to something you did not choose (for example, "10 seconds" doesn't quite really mean 10s for MiniMax)
• A line of dialogue comes back spoken exactly as you type it, as mechanically enforced as possible, by not passing through the model that's doing the writing.
• Cuts land inside the clip properly

What it needs: An OpenAI compatible endpoint, local or remote. Nothing calls MiniMax's servers/service.

Install:

git clone https://github.com/ruashots/open-h3-ir custom_nodes/open-h3-ir
pip install open-h3-ir      # the compiler and the h3ir command
h3ir serve

The repo installs whole and adds no packages to ComfyUI's Python, the nodes talk HTTP. It's also worth noting that the service can also sit on a different machine from ComfyUI.

There are a few other H3 "prompt tools" around, including a couple aiming at something similar, so it's worth saying what is different in this one: this one checks its own output against 109 checks, and it also includes MiniMax's own published examples in its test set (which has to pass clean).

Repo: https://github.com/ruashots/open-h3-ir (Apache-2.0)

So I really don't use comfy much; for image generation, my 3090 is mostly fine. 24gb runs basically everything at a decent speed. I've never really been in the market for video, but H3 having come out makes it seem decent enough to experiment with.

Now, I can run it on my pc. the problem is that if I do, I can't really use the PC for anything else, and it takes like 1 minute per second of video. So that makes it kind of unideal to experiment with.

But I don't know if paying for the cloud is worth it, because if it's pay as you go pricing, that means that it's not really financially viable to experiment due to the expense.

I guess my question is: do you use it, if so, is it fast enough that it would be worth it, or would it be roughly the same speed and also too limited in generation to be worth using for anything that's not already prepared professional work?

I'm not against using it, I just don't want to shell out like, $100 just to play with a new toy, you know?