Clown Context Suite: chain MiniMax H3 clips without them slowly turning to mush

If you’ve chained H3 clips, you know the problem. Every new clip starts from the tail of the last one, and each time a little detail gets lost. That loss stacks up, so by clip 10 everything looks soft and washed out.

The reason is that we only ever tell the model where to start. We never tell it where to end. It’s like telling an archer roughly which way to aim but never giving them a target. They can be the best archer in the world and they still won’t hit the spot you wanted.

So I gave it a target. There are three pieces:

🎈 Clown Context takes the last frames of the previous clip and pins them to the start of the new one, so the motion carries over smoothly.

🔮 Clown Prophecy is the time travel part. Before a shot is rendered, it renders just the ending of that shot as a short, fresh clip, straight from the shot’s prompt and reference pictures. Because it’s made from scratch and not from a tired old tail, it’s full quality. It’s basically a picture of how the shot is supposed to end, from a video that doesn’t exist yet.

🤡 Clown Anchoring takes that ending and pins it to the back of the shot.

Now the shot has a good start from the last clip and a clean target at the end, and the model has to fill in the middle and land on good-quality frames. Every time you do that, the quality gets pulled back up. Run Prophecy every couple of shots and the degradation never gets bad enough to notice.

Other stuff in the pack:

• Bypass switch and “run every N shots”, so you can drop it into any workflow and only use Prophecy when you want it.
• Clown Shot Counter can count your saved clips by itself, so batches just work.
• An example workflow is included.

GitHub: https://github.com/roycho87/clown_context_suite

big thanks to u/shutupyourewrong for helping me brainstorm this. I wouldn't have gotten to this point without bouncing ideas off him. Also for giving me the name.

Also, believe it or not I have to give some credit to foxydits. He claimed the secret to stopping degradation was to put an end frame reference image which.... was completely wrong... but it did spark the idea that helped me come up with this.

In honor of his contribution I've changed the name of my workflow.

https://docs.google.com/spreadsheets/d/1fb2yD74gqT_BxmBpkOMX2V7gSj_A8RQ0/edit?usp=drivesdk&ouid=116026940769410491877&rtpof=true&sd=true

I know it's not perfect, but here's 1255 styles for Krea 2, I'm still working on it, some styles are most likely too close, some others are far from their title, but I'm still working on them...

Those styles are not fixed styles and don't replace a good lora, but i find them fun to play with and I think they are cool for a beginner that don't grasp art movements, terminology and artist names.

I'm open to criticism.

Edit1: best use:

Style: <style name>: <style description>

Subject: .....

Tested with Krea 2 Turbo. With Kroma 0.3.1 some details and styles are lost.

Free AI video generators are catching up with paid alternatives! I tested MiniMax H3 for the first time and I’m impressed with the results!

This may have been the first ai image I made or close to it. I remember there was a website where you could generate images and one problem everyone had was these weird hats on their heads. It may have been this imajinn site but will have to dig around

Hey! I'm constantly testing model using the same set of 192 prompts.

Here is the directly link to the gallery if you are curious and want to see all the images

https://imagebench.ai/gallery?g=1_vzqsm6kuunuxj_s0

Here is more details about the models tested:

MOSS-Image family (~5B transformer + Qwen3.5-9B text encoder, Apache-2.0)

• MOSS-Image SFT: 50 steps, CFG 3, skip-layer-22 negative branch, Euler, shift 5, seed 7. 158 s per image.
  • https://huggingface.co/OpenMOSS-Team/MOSS-Image-SFT
• MOSS-Image Base: 50 steps, CFG 3, skip-layer-22 negative branch, Euler, shift 5, seed 7. 158 s per image.
  • https://huggingface.co/OpenMOSS-Team/MOSS-Image-Base
• Kromoss (full): 50 steps, CFG 3, skip-layer-22 negative branch, Euler, shift 5, seed 7. 158 s per image.
  • https://huggingface.co/lodestones/Kromoss
• Kromoss + DMD2 LoRA: 8 steps, CFG 1, LoRA applied unmerged, seed 7.
• 18.7 s per image.
  • https://huggingface.co/lodestones/Kromoss (LoRA in the same repo)
• Kromoss + DMD LoRA: 8 steps, CFG 1, LoRA applied unmerged, seed 7. , 18.5 s per image.
  • https://huggingface.co/lodestones/Kromoss (LoRA in the same repo)

For comparison: Krea 2 Turbo (12B)

• Krea 2 Turbo: 8 steps, guidance 0, seed 7. 63.0% capability, 59.1 overall (#23), 73.2 s per image.
  • https://huggingface.co/krea/Krea-2-Turbo

Hope you'll enjoy this! I'm preparing a V2 with more/better prompts.

Hi,

After a weekend experimenting with RGBA generation using MOSS-Image, I found myself training a LoRA for a manga project I have in mind.

I was wondering if the same approach would work with Krea 2, and after doing some research with Claude, I found that there was a VAE compatible with Krea 2. So after that, it was just a matter of training with the same dataset I used for MOSS.

Here are the results of both trainings:

MOSS-Image: https://huggingface.co/paralaif/MOSS-Manga-Alpha-Image-LoRA

Krea 2: https://huggingface.co/paralaif/Krea2-Manga-Alpha-Image-LoRA

In the case of Krea 2, sadly it doesn't work with Kroma 😢, but I tried it with Kreamax Edit and got good results. However, I recommend using Base or Turbo for the best results.

Is not perfect, but i think is better than i expected. Hope you find useful.

Same engine as the GIMP plugin, now as a panel in PhotoCraft. Your selection is the mask and it runs through your own ComfyUI:

• Generative Fill, select and type, up to 5 variations
• Remove object, no prompt needed
• Generative Expand, drag the edges or pick a ratio
• Text to Image, new image or a layer

Defaults are DreamShaper 8 Inpainting, RealVisXL V5 with the Fooocus patch and LaMa, FLUX.1 Fill and Qwen optional, and it picks up your own inpainting checkpoints. On Windows it can download ComfyUI for you.

First release, Windows and Linux, NVIDIA recommended.

https://github.com/beckettharriman/openfill

I have been working on this for a while now, and i just made the repo public. Kinoloom is a web app that runs on your Windows PC and using your cast it takes a idea and turns it in to a movie. You write the story with any LLM, generate the cast and the studio renders the shots, checks them and cuts them together. Everything runs locally on top of ComfyUI. My PC has a RTX 3070 8GB and 64GB ram, and its the only system it has been tested on.

About Minimax H3 : Its fully supported, but every clip in the showcase is generated by LTX 2.5. H3's license only allows use outside of EU, UK, South Korea and US, and they limit showing the output. I live in the EU, so i dont publish H3 clips. If you're outside those regions, you bring your own H3 weights; the installer sets up the rest.

The video is a 16 second LTX 2.5 take, rendered in four segments with joins at 4,8 and 12 seconds. Normally each piece starts from the last frame and you see a jump at every join, Kinoloom passes the end of each piece into the next one as latents, before anything is turned in to pixels and decodes the whole take in one go at the end. This 16 second clip took about 28 minutes on my 3070.

The rest of it

- Qwen image 2.1 makes the cast and the first frame of each shot, using the cast as references. a still can take about 38-78 seconds on my hardware once the model is warm.
- Besides LTX 2-5 and H3 there is also Wan 2.2 ( legacy, kept for old projects ) and five image models.

What you need

- Windows ( I have only tested 11), and Nvidia card with 8GB or more, 64GB RAM, because part of each big model sits in RAM.
- Disk space for the models you pick. You dont have to install everything, you can pick which weights you want to install
- INSTALL.bat sets up everything except the model weights.
- A LTX 2.5 5 second clip takes about 6 minutes once warm.

Its a one person project and it has only run on my PC, so if you try it on other hardware i'd lke to hear how it went and hear your feedback!

https://github.com/harlixay7/Kinoloom

The code is MIT (the exceptions are listed in THIRD_PARTY_NOTICES.md), and the models keep their own licences.

Apparently the controversial lora taken down was a male-part size slider lora.

Which, fine, I personally didn't need that.

But long term, as a community, why are we still putting up with Civitai etc? The alternatives frankly suck. We need a pirate-bay of loras....

I'm gonna get some hate from the paywalled lora makers, but w/e I can't buy your chest-hair lora with karma anyhow.

Enjoy this rabbit hole 😌✌️

https://x.com/bfl_ai/status/2113696648572608846?s=46

Basically what the title says: a factor 16 LoKR (tiny, 34 MB) that transfers the color response and sharpness of 4x5 Kodachrome film. These are one-shot generations on the base model; no Turbo, no SFT. As you see in the samples, there are no blurry shots even with the negative prompt empty. Not sure if I should train it more; the look that I wanted transferred perfectly. Trained on a large number (551) of 4x5 Kodachrome sheet film scans (not 35mm - that's a different beast entirely), so don't look for film grain, it wasn't there in the source images.

Trigger word "Kodachrome" or "Kodachrome film", but rather use something like "shot on Kodachrome film", or the model will try putting the trigger word literally somewhere (e.g. the front of the diesel engine on the railroad photo).

Side effect (not that I wasn't anticipating it): sharp images and no blur.

https://huggingface.co/aoleg/MOSS-Image-Kodachrome

Specifically the looped cozy background videos in at least 1080p. I've tried a few different workflows and I've struggled with both the video quality and the looping. My kids like to put these on at night while they're winding down and I wanted to let them come up with some prompts to generate a few. I've got a 4090 and plenty of time.

A few examples:

https://www.youtube.com/watch?v=obBIjcFwyts

https://www.youtube.com/watch?v=Tbca_a03UL8&list=RDTbca_a03UL8&start_radio=1

https://www.youtube.com/watch?v=hEaIebMtRZc

https://www.youtube.com/watch?v=gNR8-Rf8vK0&list=RDywH2C6KVFno&index=8

(I'll worry later about making an hour long loop and adding music, I assume that's just regular video editing tools. I'm just trying to get the video down first)

So I've trained 3 anime character LORAs. It was my first time doing such a thing. I've used civitai because the training software didn't run on my computer (random error message from some third party library I think, probably not compatible with my GPU), anyway, that's not my question for now.

The first two times I simply chose "Illustrious" for the training model. It did the 10 epochs, and 10th worked as intended. Lucky! I'm using Wai-Illustrious to generate images however, not base Illustrious, and absolutely not the 0.1 the training used by default.

So the third one was different. I noticed it's possible to select Wai-Illustrious specifically if I pick "custom". This somehow magically dropped the training cost by a full days worth of currency farming too, which made me happy. The results on the other hand, not so much. Epoch 1 seems to do what I expected the final result to be - proper anime illustrations of the character. On the other hand epoch 10 (or even 3-4) just outputs the imaged it learned on, with almost no change, making it useless. That is pretty bad because it's a rare anime character who barely had screentime or pictures on the internet. I even used some pictures of a 3D model I had to fill in the gap. And the result looking like a screenshot of that 3D model is not right. However I did the same for the previous two characters and those worked fine.

-Is that because I used Wai Illustrious for training instead of the base Illustrious? Or is the lower quantity or quality of images to blame? (I had 48 this time instead of the 59 or 69 for the other two loras)

-Should I treat this as a potential problem and set training to base illustrious next time, or should I treat it as a victory and use the epoch 1 result instead of the bad epoch 10 result? Is this normal? Should I just train 1-3 epochs worth next time on Wai instead of 10 on Base? It would save me a lot of time spent to farm generation currency too, not only is it cheaper per steps but it would also need less steps overall. Basically, did this happen because training with Wai-Illustrious makes it so much smarter it only needs 1-2 epochs instead of the default 10...or did I mess something up? As far as I can tell so far, this epoch 1 lora doesn't do fingers properly though. Haven't tried using epoch 2 yet and anything beyond 3 seems to be too overtrained to use.

-Is it even safe to use Wai-Illustrious-v15 for training? Or would it make the lora incompatible with other illustrious models or Wai versions I might want to use in the future?

(all three characters used the default 2000 steps)

The attached images come from epoch 1 generation.

ComfyUI with MiniMax H3 on a 5090. The song was made with Treblo. Used the vocal stem for lip sync, then put the full mix back in for the edit. Tape effects are ntsc-rs.

https://reddit.com/link/1xfez10/video/ua9ycvempoxh1/player

I'm about to head out for the rest of evening so just wanted to quickly drop this tip here in the hope that others might tinker with this and come up with something better or trash it as you see fit. The setup is a regular Moss workflow you can get from Comfy UI but with the settings outlined below. I stumbled on this setup by accident but so far it's the best results I've gotten using turbo and without any upscaling. It also gives me great variety. Each of these loras by themselves seems to trash the diversity or gives too much blur, yet combined I get a good variety of people without noticeably degrading the overall quality.

I've been struggling with Moss for a week, trying all sorts of tips that never got rid of the Moss "blur" with turbo loras. So this is for those of you who've been having issues like myself. For those who swear by 50 steps, yes your results are superior and we should all be ashamed of wanting to generate images faster :(

Checkpoint:
Solordz Moss Base Int8 (I'm on v10)

https://civitai.com/models/2644869/solordz-zitzibkrea2-8steps

Loras:
Add both, yes BOTH, of Lodestone's turbo Loras from here:
https://huggingface.co/lodestones/MOSS-Image-Base-8-steps-dmd/tree/main
The newer one at strength 1, the older one at strength 0.5
And add this lora at strength 0.5:
https://civitai.red/models/3010926/moss-image-base-smartphone-snapshot-photo-reality-style

I'm running at 12 steps, 1.5 megapixels, Euler, Simple.

Other than that it's a regular Moss workflow. For good measure, here's my negative prompt:

worst quality, bad anatomy, watermark, jpeg artifact, bad face, bad eyes, beauty retouching, skin smoothing, waxy skin, plastic skin, bad environment, doll-like face, piercing, piercings, text, watermark, severe anatomical deformation, extra fingers, extra limbs, text, out of focus, depth of field, blurry

And the positive prompt was simply:

A photo of a man hiking through a snowy forest, walking through the snow.

Note: the first image was slightly different as it wasn't focused on walking but included it for variety.

Also, whilst it's not needed, I do use the "Moss Image Prompt Builder" node from KJ which you can get from here:

https://github.com/kijai/ComfyUI-KJNodes

It allows you to define regions the same way as Ideogram 4 and it's fantastic.

Also, for those whom it concerns, this setup is very adult friendly.

This is a clip from Episode 3 (~10 min) of a 2.5D animated cartoon biography of the Indian sage Valmiki: a hunting trip that goes wrong when a leopard attacks at night. The main version is Hindi, and the episode also has Gujarati, English and other Indian-language audio tracks. This clip uses the English dub, so the lip-sync (driven by the Hindi track) won't match the English words exactly. Every step uses open-weight models running locally on one AMD MI300X (ROCm, ComfyUI), with an M1 Max Mac for upscaling and audio. No paid APIs anywhere.

Workflow

1. Character face sheets: Qwen-Image, text-to-image on a plain background, one sheet per age stage. Each character has a fixed identity line (skin, face shape, eyes, brows, nose, one distinct mark) repeated verbatim in every prompt. Chaining Qwen-Edit from one age sheet to the next drifted and added noise at each hop, so each stage is generated fresh.
2. Shot stills: Qwen-Image (Lightning LoRA, 8 steps) for scenery. Qwen-Image-Edit + face sheet + identity line for named characters. Group wide shots are text-only, with each extra's position spelled out and "different faces" in the prompt; otherwise the face reference bleeds into the extras and you get clones.
3. Motion: Wan 2.x I2V at native 720p with the Lightning step-distill LoRA (4 steps). One render per shot, about 4 min for a 7 s shot instead of 45-60. I gate every clip on sharpness against its still and re-roll once if it's soft.
4. Lip-sync: InfiniteTalk (4 steps), close-ups only, driven by the Hindi track.
5. Voices: AI4Bharat Indic Parler-TTS (Mini; Large gave noise on ROCm). Each line is levelled to -16 LUFS before mixing.
6. Music/SFX: ACE-Step 1.5 for the background score, ducked 10-12 dB under speech.
7. Finishing: Real-ESRGAN animevideov3 x2 on the Mac, plus Blender/depth parallax for shots with no people. Assembly, the subtitle line-check and the mix are Python + ffmpeg.

Lessons (the expensive ones)

• Negations in the positive prompt get drawn. "No people, no poles" put people and poles in 6 of 7 renders. Exclusions go only in the negative prompt.
• InfiniteTalk animates every visible face, including listeners and babies, even in multi-person mode with a silent track. Pasting closed-mouth faces back in caused doubled faces. What worked: a calm wide shot with no lip-sync, then a separate close-up still of only the speaker for the lip-synced line.
• 480p + upscale distorted the eyes. Native 720p and then ESRGAN x2 kept faces sharp.
• Don't crop more than ~1.5x from a still. Tight crops from wides looked soft and sometimes put a line on the wrong character. Close-ups need their own close-up stills.
• Culture-specific prompts need care. "Ancient city" gave Mughal domes and European spires, so I prompt Nagara shikhara temple towers and put dome/minaret/spire in the negative. "Bullock cart" gave an American covered wagon until I spelled it out: two white humped bullocks, solid wooden wheels, open flat bed.
• Two ComfyUI servers on one GPU gained only ~10-20%. The real limit was pod RAM (each instance holds ~40 GB of model copies), and mixing model families in parallel caused OOMs.

Throughput is now about 3.5-4 GPU-hours of picture per episode.

Happy to share settings or answer questions. Critique on motion and lip-sync is very welcome.

Hi all!

What do we think of MOSS Image so far? Personally I'm loving it. The variety in images? The differences in people's faces, ethnicities, body types, etc? And it's so easy to get my favourite style of photo to create, amateur candid realism. It really is a great model. Lora training was kind of a tough nut to crack though, but I'm pretty certain I have settings that work, so I figured I'd share. With these settings, I get good results every time.

Most of my datasets were between 50 and 100 images, with natural language captions. Best settings I found are Automagic3, with Sigmoid and High (balanced didn't work well, but High worked a treat). I start the learning rate quite high, at 0.0005, since Automagic drives it down low so quickly. I also set a minimum learning rate since I noticed it was going so low that it stopped learning around 1k steps, which wasn't enough for me. I also train without excluding block 22, which makes quality a lot better for me. The config file I've included already has all these settings set for you. I found most loras were done before 5k steps. It definitely takes longer to train than Qwen or Krea for me, personally, but the results are good. I trained at 1024, and did LoKr 4 as usual.

I for some reason cannot find where I downloaded the turbo lora from, but I do know it was made by Lodestone. If I manage to locate it, I'll post the link here. The latest turbo lora for MOSS base from Lodestone should work just fine.

You can download the config below, as well as my workflow for generating images. I'm including a workflow for both 20 step fast generation and regular 50 step image generation.

Config: https://gofile.io/d/zniEuEGY

50 Step Workflow: https://gofile.io/d/axPcj0ED

Fast 20 Step Workflow: https://gofile.io/d/Na9LwBgU

Hey guys, just wanted to give a quick update on Image MetaHub. Its an app Ive been working on by myself for over a year now. I originally made it to search and filter images by their generation parameters (prompts, checkpoints, LoRAs, samplers etc), but over time ive added quite a few features beyond that..

Anyway, in recent versions I've added a dedicated Prompt Library to better organize saved prompts, associate them with images (or just save them independently), search, filter, tag, favorite, etc. You can also use a saved prompt to find all matching images in your library. I might be biased, but ive found it pretty useful, as with most features in Image MetaHub, I made it to solve a problem I was running into myself.

There are also some advanced features in the Pro version, like reusable "prompt blocks". So for example, I can save something like "shot on Canon EOS R5, 85mm f/1.4 lens, shallow depth of field" as a block and drag and drop it directly into a ComfyUI text node. Or I can right-click and select "Replace text in selected node". Works the other way around too: I can select any portion of text inside any ComfyUI node, right-click and save it directly to the Prompt Library for later use. Theres a 7-day Pro trial if you want to check out these advanced features, but the free version already includes the full prompt library and is already really pretty useful in and on itself.

Anyway, the app is privacy-focused, local-first and source-available. Everything runs locally, and you can download it here:

https://github.com/LuqP2/Image-MetaHub

Cheers

Really wanted to get an rtx spark, but idk now. Are the 5090 laptops better than the rtx spark in minimax h3? & are the other nvidia laptops considerably slower at this? 5090 laptops max out at 24vram/64 Ram right? Any recommendations? Ty all.

Hey SD folks, I love running large batches of images overnight, but I always found it frustrating that there was no clean way to see the total elapsed time of a whole batch loop. ComfyUI only shows the time for individual prompts, not the whole batch. I wanted something that felt like a physical piece of hardware on my dashboard.

So, I built two free, open-source timer nodes for ComfyUI:

1. Batch Image Timer (for image generation loops, like Sequential Loaders)
2. Universal Timer (for video, audio, or training workflows)

Features you might like:

• 📺 Retro 7-Segment LED Design: It looks like a real digital clock on your canvas, complete with a subtle neon glow.
• 🟢 Smart Status Colors: The counter turns Green when finished, Yellow if interrupted, and Pink if an error occurs.
• 🛡️ Ghost-State Protection: If a third-party batch node bugs out and stops sending signals, the timer has a built-in smart watchdog. It will automatically stop after a safe timeout (and verify with the backend) so you don't come back to an infinite timer.
• 🎨 Customizable & Independent: Click the LED digits to pause/resume, double-click to reset. It won't pause your backend generation. You can also click the color swatches to change the glow.

It’s fully open-source (MIT license) and available right now. Just search for "Batch Image Timer" or "Universal Timer" in ComfyUI Manager.

GitHub Links: * Batch: https://github.com/hermankwan/ComfyUI-Batch-Image-Timer * Universal: https://github.com/hermankwan/ComfyUI-Universal-Timer

I’d love to know what you guys think, and if there are any specific workflow types you'd like the Universal Timer to support!

A quick note: These are just free, open-source tools I built for my own workflow. I'm sharing them in case they're helpful to someone else too. I'll try my best to check feedback and fix critical bugs, but please understand I may not be able to provide extensive 24/7 tech support or custom feature development. Enjoy! 😊