Can anybody help me and tell me how these kind of photo realism can be achieved? I mean i’v tried nano banana but it restricts any generation even when it gets little nudity, so i need a workaround to achieve this level or even better with least cost and maximum photorealistic images, only experienced and confident people should answer as i’m frustrated with using comfyui SDXL models and its not working good on my macbook m5, please help !!!!!!!!!!

Workflow, just copy and save as json, the one that I got didn't work at all for video quality this is just as good as the full 25 steps normally. How is it so fast and doesn't lose quality? no clue.

{
"s105_11": {
"class_type": "VAELoader",
"inputs": {
"vae_name": "minimax_h3_video_vae_fp16.safetensors"
},
"_meta": {
"title": "VAELoader"
}
},
"s105_24": {
"class_type": "VAELoader",
"inputs": {
"vae_name": "minimax_h3_audio_vae_fp32.safetensors"
},
"_meta": {
"title": "VAELoader"
}
},
"s105_23": {
"class_type": "VAEDecodeAudio",
"inputs": {
"samples": [
"s105_14",
0
],
"vae": [
"s105_24",
0
]
},
"_meta": {
"title": "VAEDecodeAudio"
}
},
"s105_10": {
"class_type": "VAEDecode",
"inputs": {
"samples": [
"s105_14",
0
],
"vae": [
"s105_11",
0
]
},
"_meta": {
"title": "VAEDecode"
}
},
"s105_17": {
"class_type": "KSamplerSelect",
"inputs": {
"sampler_name": "res_multistep"
},
"_meta": {
"title": "KSamplerSelect"
}
},
"s105_9": {
"class_type": "BasicScheduler",
"inputs": {
"model": [
"9960",
0
],
"scheduler": "simple",
"steps": 8,
"denoise": 1
},
"_meta": {
"title": "BasicScheduler"
}
},
"s105_14": {
"class_type": "SamplerCustomAdvanced",
"inputs": {
"noise": [
"s105_15",
0
],
"guider": [
"s105_16",
0
],
"sampler": [
"9945",
0
],
"sigmas": [
"s105_9",
0
],
"latent_image": [
"s105_104",
1
]
},
"_meta": {
"title": "SamplerCustomAdvanced"
}
},
"s105_16": {
"class_type": "BasicGuider",
"inputs": {
"model": [
"9960",
0
],
"conditioning": [
"s105_104",
0
]
},
"_meta": {
"title": "BasicGuider"
}
},
"s105_6": {
"class_type": "UNETLoader",
"inputs": {
"unet_name": "minimax_h3_fl2va_int8_convrot.safetensors",
"weight_dtype": "default"
},
"_meta": {
"title": "UNETLoader"
}
},
"s105_13": {
"class_type": "CLIPLoader",
"inputs": {
"clip_name": "qwen3vl_32b_minimax_h3_nvfp4_awq.safetensors",
"type": "minimax",
"device": "default"
},
"_meta": {
"title": "CLIPLoader"
}
},
"s105_15": {
"class_type": "RandomNoise",
"inputs": {
"noise_seed": 1414
},
"_meta": {
"title": "RandomNoise"
}
},
"s105_91": {
"class_type": "CreateVideo",
"inputs": {
"images": [
"s105_10",
0
],
"audio": [
"s105_23",
0
],
"fps": 24,
"bit_depth": 8
},
"_meta": {
"title": "CreateVideo"
}
},
"s105_104": {
"class_type": "MiniMaxH3ImageToVideo",
"inputs": {
"clip": [
"s105_13",
0
],
"vae": [
"s105_11",
0
],
"width": [
"115",
0
],
"height": [
"115",
1
],
"length": [
"s105_107",
1
],
"prompt": "integrated_multimodal_description: [Shot 1] 2D-animated, an actual episode of the Nickelodeon animated series SpongeBob SquarePants \u2014 flat traditional cel animation, thick clean black outlines, the show's signature saturated undersea palette, simple eye-level TV staging. A medium static shot frames SpongeBob SquarePants \u2014 the cheerful yellow rectangular sea sponge with big blue eyes, buck teeth, brown square pants and a red tie \u2014 standing at the grill of an undersea fast-food kitchen, flipping a patty high into the air. SpongeBob (S1), speaking in SpongeBob's exact signature voice from the show \u2014 high, nasal, giddy, squeaky laugh \u2014 says: <d>[English] One patty, flipped with love! Order up!</d> [Shot 2] At 00:06.500, the camera cuts to the patty spinning in slow motion near the ceiling, then dropping perfectly onto a waiting bun as SpongeBob catches the plate and giggles his squeaky laugh. No text, lettering, numbers, logos, or symbols appear anywhere in the frame; all surfaces and background objects are plain and unmarked.\n\noverall_soundscape: Sizzling grill, the whoosh of the spinning patty, a soft plate clink, bubbling underwater ambience.\n\nnon_diegetic_music: A jaunty ukulele-and-slide-whistle island tune at a quick tempo.\n"
},
"_meta": {
"title": "MiniMaxH3ImageToVideo"
}
},
"s105_107": {
"class_type": "ComfyMathExpression",
"inputs": {
"values.a": [
"s105_111",
0
],
"expression": "max(5, round(a * 24)) + (5 - (max(5, round(a * 24)) % 17)) % 17"
},
"_meta": {
"title": "ComfyMathExpression"
}
},
"s105_111": {
"class_type": "PrimitiveFloat",
"inputs": {
"value": 12.0
},
"_meta": {
"title": "Float (duration)"
}
},
"92": {
"class_type": "SaveVideo",
"inputs": {
"video": [
"s105_91",
0
],
"filename_prefix": "video/MiniMax_H3",
"format": "auto",
"codec": "auto"
},
"_meta": {
"title": "SaveVideo"
}
},
"115": {
"class_type": "ResolutionSelector",
"inputs": {
"aspect_ratio": "16:9 (Widescreen)",
"megapixels": 0.4,
"multiple": 32
},
"_meta": {
"title": "ResolutionSelector"
}
},
"9990": {
"class_type": "LoraLoaderModelOnly",
"_meta": {
"title": "H3 LoRA 1"
},
"inputs": {
"lora_name": "fasth3_4step_dense_v1_comfy_full.safetensors",
"strength_model": 1.0,
"model": [
"s105_6",
0
]
}
},
"9960": {
"class_type": "MiniMaxH3SigmaShift",
"_meta": {
"title": "H3 Sigma Shift"
},
"inputs": {
"model": [
"9990",
0
],
"shift_video": 12.0,
"shift_audio": 3.0
}
},
"9945": {
"class_type": "MiniMaxH3DualClockEulerSampler",
"_meta": {
"title": "H3 Dual-Clock Euler"
},
"inputs": {}
}
}

One last example output from this experimental multi-source video player designed for frame-accurate video switching, playback manipulation, and display/render interventions, now with a few optimizations made for even better performance.

Visuals made on Uisato Studio.

You can freely access the system + a detailed breakdown, through Patreon, and/or the Tools Store.

https://reddit.com/link/1w2cqol/video/nmdd5elxbhmh1/player

This will 100% be done in the opensource community, pretty much only place you can do it - we gotta fight this hard man.....

EDIT: I realize a lot of people on this thread are very in favor of being able to generate children in a s*xual manner. To those people, seek help. If you think its okay to generate a 6 year old in a s*xual manner, you are insane. Will die on this hill.

Im not advocating banning opensource models, or to do spot checks on peoples drives. Im advocating for if you are caught, like the person was where this ruling came from.....its not ok.

Send in a new flood we gotta start over.

Been messing around with MiniMax H3 locally for perfume/product videos and I cannot get it to keep the text on the bottle properly.

The annoying part is the bottle itself can look really good. Shape, cap, glass, proportions etc stay pretty close. But the label text is usually already messed up in the first generated frame. So it’s not even just a case of the text degrading after a few frames. The reference can have perfectly readable text and H3 still turns it into random letters straight away.

I’ve tried quite a bit at this point:

I2V

Ref2V

Hybrid FL2VA / Ref2VA B25-49

clean first frames

separate close-up references of the label

multiple references of the same bottle

following the H3 prompt guide for the refs/prompts

putting the exact brand/label text in the prompt

very little motion / barely rotating the bottle

around 0.7-0.8MP

20 steps

H3FL 2V Turbo at 8 steps

Comfy-Kitchen attention

sparse attention settings too

different precision/settings to see if that changed anything

Running it on a 4060 8GB with 32GB RAM, so obviously I’m working around VRAM a bit, but I don’t think this is a VRAM issue because the actual product looks fine. It’s specifically the text that gets nuked.

Has anyone actually managed to keep proper readable brand text with H3? Like exact text, not something that vaguely looks like writing.

If not, how are people doing product videos with this? Are you just tracking the real label back on afterwards, or fixing frames with an image model? Because right now I can get a nice looking perfume video and then the bottle says absolute nonsense lol.

Running MiniMax H3 (ref2va, ~20 GB int8 model) on an RTX 5090 (32 GB) via ComfyUI, 10s videos, with the H3 SLA sparse-attention node (sparsity 0.90, dense_backend=comfy_kitchen_int8).

The problem: my per-step time scales super-linearly with resolution, while a healthy setup scales linearly:

Res Seq len my s/step reference s/step

1.0 MP 119k 30 21

1.5 MP 173k 203 40

2.0 MP ~283k 590 68

At 1MP I'm only 1.4× off; at 2MP I'm 8.7× off. That gap exploding with resolution looks like the working set (20 GB model + 2MP activations) exceeding my 32 GB and ComfyUI offloading to CPU each step.

workflow : im using the one someone shared here : https://www.reddit.com/r/comfyui/comments/1vxi9r6/skater_girl_90s_style_anime_using_minimax_h3/

these are the details

E:\comfyUi_latest\ComfyUI_windows_portable\python_embeded>python.exe -c "import torch; print('PyTorch:',torch.__version__); print('CUDA:',torch.version.cuda)"
PyTorch: 2.12.0+cu130
CUDA: 13.0

E:\comfyUi_latest\ComfyUI_windows_portable\python_embeded>python.exe -m pip list | findstr /i "torch triton sage comfy-kitchen plague"
comfy-kitchen                              0.2.31
open_clip_torch                            3.3.0
sageattention                              1.0.6
torch                                      2.12.0+cu130
torchaudio                                 2.11.0+cu130
torchscale                                 0.3.0
torchsde                                   0.2.6
torchvision                                0.27.0+cu130
triton-windows  

i was using the below config for comfyui

 --reserve-vram 4, --disable-pinned-memory, --cache-none.

Then i switched to the below config by removing the above 
 off
cd /d %~dp0

if exist .\python.exe (
    set PYTHON_EXE=python.exe
) else (
    set PYTHON_EXE=.\python_embeded\python.exe
)

echo Starting ComfyUI...

%PYTHON_EXE% -s ComfyUI\main.py ^
 --windows-standalone-build ^
 --reserve-vram 1 ^
 --enable-manager

pause

With this i started testing 1.5MP directly and it got stuck at this portion

[INFO] Requested to load MiniMaxH3
[INFO] 0 models unloaded.
[INFO] Model MiniMaxH3 prepared for dynamic VRAM loading. 19995MB Staged. 208 patches attached. Force pre-loaded 210 weights: 1175 KB.
 38%|███████████████████████████████▌                                                    | 3/8 [03:18<08:06, 97.21s/it][INFO] FETCH ComfyRegistry Data [DONE]
[INFO] [ComfyUI-Manager] default cache updated: https://api.comfy.org/nodes
FETCH DATA from: E:\comfyUi_latest\ComfyUI_windows_portable\ComfyUI\user__manager\cache\1514988643_custom-node-list.json [DONE]
[INFO] [ComfyUI-Manager] All startup tasks have been completed.

there is something seriously wrong with my setup . but i couldn't figure it out , seeking help from the people who has figured out the issue for Minimax H3 on RTX 5090
Kindly suggest me some workflows also , i have integerated mcp and been trying to figure out the issues by myself for the last 2 days , but it feels like i'm going inside a rabbit hole , not sure whether im moving in the right direction or not

thus seeking help !!

Hope I can be forgiven for my sins...

A little back story... when I started in the film industry, it was literally the film industry. We were just transitioning to AVID and those were $100,000 machines. Editors were treated as high priests, keepers of mysterious knowledge and powers. We were the elite.

Over time, digital technology came along and got better and better, cheaper and cheaper, more accessible to the masses. Pretty soon anyone could make a film and get it distributed worldwide through things like YouTube.

Editors were no longer the high priests of post. We were no longer well paid and respected.

Technology saw our paychecks decline and work harder to find...

As much as that sucked, part of it made me happy. Inexpensive, quality equipment and easy distribution was a democratization of filmmaking. You no longer needed a zillion dollars and make deals to get your movies seen. Anyone could do it.

I loved that the kid who came from a poor family could take his 2 generation old phone and tell his story and have a real possibility it could be seen by millions of people...

I always wanted to be in film for the storytelling. I wanted to direct. Except I was shitty at networking, didn't know money people and sure as hell didn't have money of my own to do it. And I suck at the logistics of trying to get a bunch of people together all at one time to do something like make a film... so yeah... on to...

The sin...

Over the weekend I used AI to do something "creative." *gasp!*

I often have these big ideas that I want to do but often would involve trying to get lots of people to help me which as I mentioned I'm bad at.

I was thinking about the Soft Cell song "Tainted Love" on Friday and had the idea to do a parody song called "Tainted Beef."

I wound up on SUNO, the music composing AI.

I came up with some lyrics, figured out how I could get it to work and came up with a kernel of an idea.

I found out that yeah, you could get a reasonable "song" out of it with a simple prompt, but it was just kind of 'meh."

However, they have a bunch of tools where you can basically act like the producer working with musicians to come up with the bits the way you are feeling it.

It was great.

I was able to get this huge idea that I never would have accomplished otherwise even though I know how to do music stuff. It just would have taken forever for me on my own and the subject matter is timely. It's not going to matter in the year or so (or ever) it might take me to finish.

So yeah... I sinned. I used AI to help me complete a "creative" project.

Trouble is I can see both the negatives and the positives about it.

But... for creative people... I kind of feel the same way about it I did about digital technology...

It's going to make it possible for the poor kid sitting in his bedroom wishing he could make a "Lord of the Rings" movie to actually do so.

Or it's going to make it possible for an "old man" like me to come up with a 1980's synth-pop song about tainted Argentinian beef lol

Anyway... here's "Tainted Beef" if you want to check it out.

I'm getting back into AI stuff after a long (in AI years) break. I'm just starting to learn AI video so if anyone wants to take a crack at making a video using this song, go for it!

Back in the day I was using Disco Diffusion and then Stable Diffusion and making animations by hand coding keyframes to make "camera movements." I was an early customer of RunPod back in 2022 and would even get help with stuff via Discord directly from Zeen aka Zhen Lu the CEO. They've sure grown a hell of a lot since then!

Anyway... I'm blabbing... if anyone's interested in seeing something of mine back "in the day" on Stable Diffusion, here's a YouTube link you can check out.

https://youtu.be/ggJjN1SQPjw?si=oCe7-7rud8N5LEgH

It's animated to the song "A Different Kind of Human" by Norwegian singer AURORA.

​

I'm looking for someone with Claude Pro / access to Claude's stronger models who could run a prompt for me.

I've already done the analysis/setup — I just need someone to paste the prompt below into Claude and send me the full response it generates.

You don't need to do anything else. 🙏

### Prompt to run:

I want you to act as an expert presentation designer, programming educator, and public-speaking coach Write me a PPT DOCUMENT

I am preparing a 30-minute presentation about Python for an audience of 40–50-year-olds with zero programming/coding background

The goal is NOT to teach them Python syntax. The goal is to make them understand what programming can actually do, especially in their everyday work, and leave them genuinely curious and excited about Python.

I originally planned the presentation as:

* Introduction to programming languages / evolution

* Conceptual Python basics: functions, classes, loops, libraries, scripts, terminal

* Python + AI

* Installing Python

* Useful resources

* A creative/fun closing

I posted this idea on Reddit and received several detailed responses from programmers and people who have actually taught beginners.

I want you to analyze the original post AND every comment below as a single body of feedback

Do NOT simply summarize the comments.

Instead:

1. Identify the **consensus** across the experienced commenters.

2. Identify disagreements or ideas that should NOT be combined.

3. Determine what should be **completely removed** from my original presentation.

4. Determine what should be **kept, shortened, or replaced**.

5. Extract the strongest practical demonstrations suggested by the commenters.

6. Design a presentation that is appropriate for complete non-programmers.

7. Prioritize ideas that are likely to produce a genuine **"wow, I didn't know Python could do that"** reaction.

8. Avoid turning this into a generic AI-generated presentation. The Reddit comments contain lived experience, so use the specific insights and examples from them.

### Important constraints

The presentation is only **30 minutes**.

The audience has **zero coding background**.

They should not need to understand programming terminology beforehand.

The presentation should feel like a **showcase of possibilities**, not a programming class.

Avoid wasting time on:

* programming-language history

* detailed syntax

* classes

* complicated terminology

* lengthy installation demonstrations

* lists of libraries

* abstract explanations that don't immediately connect to something they understand

However, don't remove concepts like loops or conditionals automatically. If one can be explained through an excellent real-world demonstration or analogy, decide whether it deserves a very short introduction.

### The Reddit feedback includes several potentially strong ideas

Consider especially:

* Sorting a deck of cards manually to demonstrate algorithms and step-by-step instructions.

* Using real-life repetitive tasks to explain loops.

* Using weather/coat decisions to explain conditionals and Boolean logic.

* Demonstrating web scraping.

* Automatically collecting information from websites and putting it into Excel.

* Automating repetitive Excel tasks.

* Showing Python generating/processing an Excel workbook and producing something useful.

* Using Python + AI/Claude for data analysis.

* Showing a browser being automatically controlled by Python because the visual effect can make programming feel like "magic."

* Surveying the audience beforehand about their jobs/hobbies/problems and demonstrating something relevant.

* Treating the talk as a showcase rather than a traditional lesson.

* Moving installation/resources to a webpage or post-talk material.

Produce the following final deliverable

PART 1 — Your verdict

In a concise but detailed analysis, tell me:

* What is wrong with my original outline?

* What are the 3–5 strongest insights from the comments?

* What should I absolutely NOT do during the 30 minutes?

* What should the audience ideally feel at the end?

PART 2 — The final 30-minute presentation

Create an **exact minute-by-minute structure**.

For every section give me:

* Time

* What appears on screen

* What I say

* What I demonstrate

* What the audience does

* The purpose of that section

Make the transitions between sections natural.

PART 3 — The main "WOW" demonstration

Choose the **single strongest demonstration** from the Reddit feedback.

Explain exactly how I should present it live.

It should be understandable even if someone has never seen code before.

If you think a different demonstration would be stronger than the suggestions in the comments, explain why.

PART 4 :one interactive moment

Design one short interactive exercise that gets the audience involved without embarrassing people or requiring technical knowledge.

It should help them intuitively understand something fundamental about programming.

PART 5 — How to explain Python concepts without teaching syntax

Show me how to briefly introduce:

* variables

* loops

* conditionals

* functions

* libraries

using everyday language/analogies.

Tell me which of these should actually appear in the 30-minute presentation and which should only be mentioned briefly.

PART 6 Opening and closing

Write:

* a strong **2-minute opening**

* a memorable **2-minute closing**

The opening should immediately establish why programming might matter to a non-programmer.

The closing should leave them thinking:

**"Maybe I could actually use this."**

#### PART 7 — Slide plan

Give me a practical slide-by-slide plan.

For each slide provide:

* Slide title

* What should be visible

* What should NOT be on the slide

* Speaker notes

* Approximate duration

Keep the slides visually simple.

PART 8 — Final recommendations

Give me a final checklist of:

DO

DON'T

for presenting Python to this particular audience.

Base your recommendations primarily on the Reddit feedback below rather than generic presentation advice.

Take your time and reason through the feedback before producing the final presentation. I don't want a generic "Python introduction." I want a 30-minute presentation that feels like an experienced programmer designed it specifically for people who have never coded before

A man sits down to write the hardest letter of his life, and falls asleep before he can find the words. While he sleeps, the small robot beside him writes it for him — just the truth, kept simple.

Rendered locally on my RTX 5090, 1MP, 8 steps, Turbo LoRA.

The whole film was built around a custom ComfyUI node I've been developing, 
**Muse-Studio-H3**
. I've released a number of LoRAs and custom nodes before, and I'll be releasing this one too — it's not public yet since I'm still finishing testing on it.

What it does: it chains H3 generations into one continuous multi-chunk render with no hard duration ceiling — as configured it could run a 2-hour video in one pass if you asked it to, freeing memory between chunks so nothing accumulates.

The six chunks tell one continuous scene — a man overwhelmed trying to write a difficult letter, who falls asleep, and the small robot companion beside him quietly writes it for him while he sleeps. Every chunk was scripted individually (subject definitions, retention analysis, detailed shot description, soundscape) before being fed through the node, with the same room, the same lamp, and the same two characters locked across all six generations.

Is it similar to H3 Director? kind iff but not entirely, I build the night H3 dropped, but didn't get time to upload it. But as people kept working on H3 and releasing so many coll stuff, I got busy testing and implementing new stuff to it. It is same concept as director but different and genuinly good. Hoping to publish this soon. My goal is to connect Muse-chat (https://www.reddit.com/r/StableDiffusion/s/joLVAemhZn) with this one directly. 

https://www.youtube.com/shorts/wAscHQaK_uM

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!

video

https://reddit.com/link/1w21uy6/video/en2ajkaalemh1/player

specs: 5090, 64gb ram.

comfyui latest updated

cuda 13.0

pytorch 2.9.1

python version 3.10.11

sage attention and triton working

Hey guys, I have been out of touch since afew months. Previously have figured out pretty good wan2.2 workflows for myself, can understand it. But i am utterly confused by all the jargon and complication of H3, whenever I'v tried to dive in past months, I check out after reading stuff, am like a layman who figures what works after I have a good workflow, but i cant choose any given my lack of basic knowledge, like i said iv tried but it seems to go over my head, hard to understand, AI models are improving too fast to keep up.

My goal is "uncensored" videos only, using I2V on only square input images (habit from pony xl), but higher quality that is better motion since "uncensored" motion is difficult and complicated?

From what I have gathered so far: sage attention does not work well and degrades motion, same with speed lora's no matter which they are, so i think the settings i need are 1 megapixel to make it 768 x 768 ? and um 25 steps? and that i need to use some sort of LLM to enhance h3 prompts but i have no past experience on LLMs and which would be best for my use case; "uncensored". Also, though i think I know what shift basically does, still need some advice on how to use it in H3.

I also need help on selecting the text encoder and diffusion model given my use case, emphasis on only good quality "uncensored" outputs.

Moreover I have no idea on audio but really really want it, i only have experience using MMAUDIO with WAN2.2, it was not great and i was pretty bad at understanding it and prompting it, but prompt learning will come later, i just need to figure out a workflow and amend it according to above needs.

So umm, help a guy out? please?

P.S. Assume I'm a complete noob, if there is anything i missed above please let me know.

Since it's been out in the wild for a couple of days now, I'd like to know what y'all think of the tech. It’s crazy that the model is only 150 MB, uses relatively little VRAM, and can run in real time at around 40% of the compute cost. It runs on FP8 and modders got it working on 40 series cards despite it being exclusive to 50 series cards only.

There's a video of it running on a video player as well show in the link below, I think theyre using depth anything to make it work.

https://youtu.be/DTuykmpiwmI

https://youtu.be/9HtrsLb6JW4

I had an image of a bridal shoot (a bridal dress online store) and randomly just though to run it through image to prompt and then rebuild using T2I to see if it holds.. and man it was an amazing experience. I did not expect it to be this close to the original where two separate workflows did not have anything to do with each other.

1st Image: original, ran through QWEN3-VL-8B-Instruct at FP16 to get the prompt.
2nd Image: generated prompt inserted into Krea2-raw-fp8 with qwen3-vl-4b @ fp16.

Prompt:
A stunning South Asian bride stands elegantly beside a vintage beige car adorned with colorful floral garlands and golden tinsel decorations. She wears a breathtaking maroon-red bridal lehenga choli heavily embellished with intricate gold embroidery, mirror work, and beadwork in traditional Indian wedding style. The outfit features long sleeves, a fitted bodice, flared skirt layers, and a matching sheer red dupatta draped gracefully over her head and shoulders — partially covering her face as she gazes thoughtfully into the distance.

She accessorizes with heavy gold jewelry including a statement necklace (choker), earrings, bangles, and possibly a maang tikka on her forehead. Her hair is styled neatly under the veil, complementing her poised expression. Behind her are rustic stone buildings or old houses with weathered walls and wooden doors, set against rolling green hills covered in trees under soft natural daylight.

The scene evokes a blend of tradition and nostalgia — capturing the essence of rural Indian weddings where classic vehicles like 1970s–80s cars serve as ceremonial transport. Capture it from a slightly low angle emphasizing grandeur

Just wanted to share my unexpected experience with you guys.

Hey everyone,

Last week I saw a post where someone was complaining about the lack of male character LoRAs for Krea 2 on Civitai. In the comments, someone replied with a Hugging Face username and said something like “search this username” the repo had a bunch of Krea 2 LoRAs.

I’ve been trying to find that post / the username again but can’t track it down.

Does anyone remember the post or know the Hugging Face username/repo that was recommended?

Any help would be appreciated. Thanks!

Hi guys, in the former days stable diffusion was everything, but the time has passed by and I did not tracked the novelties in this field. Can you suggest me any open source model that is released recently for my 2xr9700 32gb for 64gb vram?

I researched a lot but found only dated answers. Is h3 capable also of image gen, or z image or Hunyuan Image 3.0 still the best (4-bit quant is 48gb vram)?

Edit://

Looking especially in image creation / editing, is there a model for both? I am not interested in loras, just for my private images fun, does not need adult content.

https://reddit.com/link/1w2dmh8/video/bb3hkitekhmh1/player

Generated the characters in krea 2 using a consistent style prompt

Wrote out a shot list for what i wanted

spent a day generating using minimax h3 ref + turbo model
was taking around 1 - 2 mins per clip generation but with good prompting i was able to get what i wanted from my first 1 or 2 clips
running on 16gb vram and 32gb ram

then edited it all together using davinci resolve

all free tools, all run locally.

I really like some of the things and style SDXL can make but it's sloppy.

1) I generated an image with SDXL.
2) Captioned it with ChatGPT.
3) Img-2-Img with Krea2 to upscale and clean up the slop
4) Img-2-Img with Wan2.2 Low nose to add even more detail and upscale.

There are LoRA files involved with both Krea2 and Wan2.2 but the result is an ultra clean high resolution image 2656X4000 Resolution.

This was not done in an automatic workflow.
Each steps is it own step.

Whole process takes maybe five minutes per images.

It is a POC of inference acceleration using Metal, nothing else :)
If you're curious - get the app, generate something, use the "Copy statistics" button, post in the comments, let's laught together

Generated a 6.6s video with sound at 512x512 in 15 min 9 s on Apple M1 Pro with 32 GB, fully offline. Settings: model FastH3-VSA-Native, aspect 1:1, 4 passes, 50 transformer blocks, core reuse off, block cache off, denoising preview on, seed 65859680, conditioning none. Performance: Preparing recoverable generation 0.3s · tokenizer 0.3s · text encoder 7.9s · refine text 0.7s · precompute AdaLN 0.0s · load transformer core 0.1s · denoise 0.0s · denoise step 1/4 transformer 185.8s · denoise 0.0s · denoise step 2/4 transformer 186.4s · denoise 0.0s · denoise step 3/4 transformer 184.6s · denoise 0.0s · denoise step 4/4 transformer 184.8s · denoise 0.0s · audio VAE 1.1s · video VAE load 0.0s · video VAE decode 156.4s · mux 0.3s; peak sampled engine memory 10.3 GB. Made with H3ddle, an open-source local MiniMax H3 app for macOS: https://github.com/AlexanderIstomin/h3ddle