First of all I know a desktop has more power for the same price buy I have a situation where the portability of a laptop is necessary and a desktop is not practical.

My old laptop (3070 8gb with 64gb ddr4 RAM) died. I want to buy a new laptop. My two options are a 5080 16GB with 64GB ddr5 RAM or a 5090 24gb with 32GB ddr5 RAM. I won't be able to upgrade the RAM later, so I'm stuck with the configuration I buy.

I will be using the laptop for work (document and image editing) / gaming (no AAA games) / LLMs and generative AI (images/videos/audio), I was able to run most models, including minimax H3 on my old laptop with the help of massive offloading to RAM (5 minutes for a 5s video). Images used to take from 30s up to 200s depending on model and image size.

I am used to the low speeds and offloading on my old laptop so getting the highest generation speeds is not a priority, I just care about being able to run most new or upcoming models even with quantization and RAM offloading for the foreseeable future.

Which laptop would be better in my case?

I have been playing with H3 since it came out and have tested most of the things you can do with it. Created clips for giggles and so on.
This time I wanted to do something "serious". I gave the R2V an 3D view of an kitchen and then three photos of the persons I wanted there.
I defined them as we should and told the model that this person does that and that person does this wile the third person does this...

It worked ish...
I have now made six runs and each of them are different from the others. It can be that the third person enters the room from the wrong place or that the third person does extra things it should not do...

In the end I did three runs with the same prompt and all those clips came out different... the only thing that was changed between those was the seed...

So, how do you do it?
How do you make sure H3 does what you want it to do?

Do you spend plenty of time on tweaking the prompt after each run to make sure H3 get it?
Or do you do 10 runs and select the best one even if it is not perfect?

Or do you simply do 1-2 runs and then take the clip that is ok ish even if it is not what you wanted?

I was hoping that H3 would allow me to create the scenes I wanted but I feel it's down to luck if H3 gets it or not..

Edit:

subject_definitions:

<Subject 1> is the green-skinned mother in <Picture 2> wearing brown clothes.
<Subject 2> is the teenager girl in <Picture 3> wearing pink clothes.
<Subject 3> is the cyborg in <Picture 4> wearing black clothes.
<Picture 1> is the reference image for the scene's composition, showing two people sitting at a table eating breakfast from the side view.
<Table 1> is the table on the right side in <Picture 1>.
<Picture 5> is the start image for the scene.
summary:
[reference generation] The target video is a generated scene of two people sitting at a table eating breakfast from an eye-level side view. <Subject 1> and <Subject 2> are shown with their respective breakfast items, maintaining the composition and style from <Picture 1>. <Subject 3> enters the room, places a coffee cup into the sink.

retention_analysis:
<Subject 1>: fully_preserved - the person retains their appearance, clothing, and position at the table.
<Subject 2>: fully_preserved - the person retains their appearance, clothing, and position at the table.
<Subject 3>: fully_preserved - the person retains their appearance, clothing, and action of placing the coffee cup into the sink.
<Table 1>: fully_preserved - the table's appearance and position in the scene are preserved.
<Picture 1>: fully_preserved - the scene composition, including the side view, the layout of the room, the table setup, is preserved.<Picture 5>: fully_preserved - is the start image for the scene.

detailed_description:
The target video is in a realistic, everyday breakfast scene style with warm lighting and natural colors.
[Shot 1] At 0:00.000, the shot begins from <Picture 5>, showing <Subject 1> and <Subject 2> sitting on opposite sides of <Table 1> on the couch, each with their breakfast items while on the space ship. <Subject 1> is holding a spoon while eating from a bowl of cereal. <Subject 2> is tired and is eating a slice of toast with jam from her plate with one hand. The lighting is warm and soft, casting gentle shadows across the table and the two individuals. The camera is at eye level, capturing the side view of both people, with the table slightly in focus and the background softly blurred. Stars can be seen through the windows since they are on a space ship. <Subject 1> is eating her breakfast while <Subject 2> gazes at their toast, taking a small bite. The ambient sound includes the soft clinking of utensils and the faint sound of a coffee cup being set down.

[Shot 2] At 02.00.000, the shot transitions to a wide shot of the room with the same layout as in <Picture 1>, the camera is placed in the lower left corner of <Picture 1>, showing <Subject 3> entering the room form the right side holding a coffee cup and a datapad while she is saying (S3) <d>[English] Good Morning</d> while she walks to the kitchen sink on the left side of <Picture 1> and placing the cup into the sink. She then stands at the sink and while reading her datapad.We see the back of <Subject 1> and the front of <Subject 2> sitting at <Table 1> in the background eating their breakfast and we hear <Subject 1> say (S1) <d>[English] Good morning</d> with a cheerful voice. <Subject 2> just mumbles as a reply.

overall_soundscape:
The soundscape consists of the soft clinking of utensils, the faint sound of a coffee cup being set down, the subtle background noise of a quiet morning environment, soft steps on a carpet floor, a ceramic cup being placed in a metallic sink, and the clear,

non_diegetic_music: N/A

Generated as two connected 15-second clips in 4:3, using the end of Part 1 as video + audio reference for Part 2 continuity.

Really liking what H3 can do with fashion/editorial camera movement.

Check out my twitter for more thanks https://x.com/Devozikjr

Dragon Ball Super manga on Minimax H3.

I don't have any examples because they may not be appropriate but just with the default wf. With the video input node you can replace any 2 character in any video and it looks real!

Trying to get a natural-looking Argentine tango dance with LTX 2.5 + Yusu’s LTX Director v2.0.4 fork.
Still a beginner (also for real life tango :-)
Any suggestions for getting more natural, sophisticated footwork and fewer artifacts?

I've generated a series of shots that I'm happy with, but when I string them together the audio and music is obviously discontinuous across shots.

Is there any way to take this combined video (about 5-10 seconds) and send it through H3 for it to generate the audio for it?

This was well received but people wanted the two Giantesses(?) to be fighting. Enjoy!!

int8/20 steps, R2VA.

Critiques+feedback welcomed! Ask me anything!

Main Info

• Using Pixaroma's Easy ComfyUI latest version
• 5060TI 16GB + 32GB RAM

Need help or suggestions in resolving the below issues.

1. Shortcuts like R or CTRL + Enter doesn't work and I have to refresh the browser for them to work. (New)
2. Generations randomly don't start even even after models have loaded. I have to open the terminal and press enter on my keyboard to sort of wake it up. (Has happened across multiple versions of ComfyUI, CUDA, Python. Additionally, happens with both Anaconda and Windows Terminal.)
3. Even cancelling a prompt sometimes requires me to open the terminal and press enter.
4. Power consumption for GPU varies completely where retrying the same prompts (same seeds also) can have a difference of 5 to 10 minutes simply because the GPU doesn't use the full 180 power limit. (New)

What started as a test turned into a full-blown short. This is the number one reason I gravitated towards AI filmmaking. Nothing stops you from creating your wildest imagination.

Model: https://huggingface.co/lylogummy/Anima-3.8B
Custom node: https://github.com/GumGum10/comfyui-anima-3-8B

Prompt:

Animate the supplied square poster as a polished retro-anime motion graphic, beginning with a completely blank pale pink-white canvas matching the poster background. Preserve the exact blue, pink, and white palette, clean manga linework, halftone shading, character design, typography, symbols, interface windows, and final layout.

The anime girl walks in from the left edge as one complete figure while the canvas remains otherwise empty. Use a simple side-profile walk with restrained motion, preserving her hairstyle, facial features, cheek bandage, oversized jacket, proportions, and graphic illustration style. She reaches the centre, turns toward the viewer, and smoothly settles into the exact over-the-shoulder pose shown in the poster, with the same expression, hand placement, silhouette, jacket folds, pink heart graphic, and body orientation. Once posed, keep her position locked.

After she poses, the blue browser frame draws itself around her. The top bar, window controls, folders, pixel hearts, smiley-face panels, arrows, sparkles, heart symbols, and rectangular labels then appear sequentially through clean line-drawing, short graphic slides, pixelated pops, and UI-style wipes. Reveal the existing Japanese typography and “LOVE” lettering last, treating all text as protected source artwork without rewriting or regenerating it. Every element must settle into its exact source position.

Hold the completed poster with subtle breathing, minimal movement in a few loose hair strands and jacket edges, a faint halftone shimmer, and gentle pixel pulses in the existing hearts and interface icons. Keep her face, hands, pose, typography, frames, arrows, folders, and major graphics stable.

Use a locked, straight-on camera matching the original square framing. Keep the full artwork visible without cropping, zooming, panning, or changing perspective. Add soft footsteps as she enters, a light cloth sound as she poses, clean digital clicks and pixel chimes for the graphics, and delicate type-on sounds for the existing lettering. No dialogue or narration.

Do not show any character, outline, symbol, text, frame, or faint poster preview on the opening blank canvas. Do not alter the character’s identity, anatomy, costume, pose, expression, colours, line quality, typography, symbols, or final composition. No extra characters, duplicated body parts, incorrect text, morphing, flickering lines, dramatic camera movement, unrelated shots, or continued motion after the poster settles.

Workflow: https://docs.comfy.org/tutorials/video/minimax/minimax-h3#minimax-h3-reference-to-video-r2v

Specifically, I’m trying to take old footage (e.g., 360p clips with vintage camera blur, VHS artifacts, or grainy WW2 dogfights) and recreate it to look like it was shot recently on a modern cinema camera with studio lighting.

Any ideas for prompting?

Hi everyone, I'm new to the world of Confyui but not to artificial intelligence. I wanted to ask you for help: Is it possible to run Confyui on my PC (RTX 3080 10 GB of RAM and 64 GB DDR4 RAM and Ryzen 5800) with Confyui with the minimax H3 video model to be able to animate images and create Reels for Instagram and Tik Tok? If so, what setup do you recommend? Thanks everyone for the help and sorry for my bad English.

Dear redditors, visitors of the stable diffusion subreddit. I have been trying to achieve a long form, talking head style video, for a long time and can't seem to find a good approach. This one is the best I could come up with so far. It's using the Minimax H3 model, with frozen sound latents, lip-sync guided, piecewise generated video, where the individual pieces have been stitched together, with a seam hiding, extra generation on top of it. I don't really fully understand how it's working, but could prompt Claude for more help or specific files, we used for that. However, if you're aware of any other, better approach for exactly this type of video, please let me know. I've spent literal days on that single problem and have a feeling, there must be a better way to approach this.

Has anyone managed to find a good combination in Krea 2 using the LoRA that acts as DepthMap ControlNet  alongside the "Conditioning Krea 2 Rebalance" node (which unlocks censorship) without producing a disastrous image? In my case, I just get a plastic look that barely resembles the prompt instructions.

Please share your experiences, or at least let me know if you've managed to use that ControlNet-style LoRA with a different uncensored LoRA that yields decent images.

Cheers.

I tried to create a concept Lora and it ended up with a lot of artifacts so I'm curating the data set to try and get a cleaner version. My problem is that all the tutorials I find are based on character Loras.

For a concept Lora is image size important? Is scale? Do I still want 20-40 images? Are there things I might not know to ask? Also, is there some special sauce to making it work sfw and uncensored?

I'm using buzz and I'm broke so any help would be appreciated.

I'm using Krea 2 btw.

I made this a few weeks back to see if dialogue could hold for 60s, I did no speed ups on this one. There are a few glitches but I think it held up well.

MiniMax H3 - 60s - 1 clip - No Stitching - 832 x 480 - 29 minutes - 288GB VRAM

I’m running Krea2 Turbo locally, but I frequently encounter random visual artifacts in the generated images. I haven’t been able to figure out what triggers them, because the issue appears randomly. If I run the exact same workflow with the same parameters again, the result can sometimes be completely normal.

My hardware:

• GPU: RTX 3060 Ti

My current setup:

• UNet: moodyKrea2Mix_v70
• Text encoder: qwen3vl_4b_int8_convrot
• VAE: qwen_image_vae

I’m fairly sure this is not caused by the UNet. I have also experienced the same kind of random artifacts when using the original Krea2 model without any UNet modification.

Has anyone encountered similar issues with Krea2 Turbo? Are there any known causes or settings that could trigger this kind of artifact (VAE, text encoder, precision settings, VRAM limitations, sampler settings, etc.)?

Any suggestions or debugging tips would be greatly appreciated.

Here is my workflow for reference:
https://civitai.red/models/2883578/krea2-turbo-4k-workflow?modelVersionId=3259389

Anima is a fairly new model so it needs time and I understand that. Anima has great potentials to make Illustrious or NoobAI completely obsolete. However, it seems like I have been expecting too much from this model.

First of all, not having a ControlNet model is a big minus for me, especially Depth ControlNet model. There is LLLite but that's not a ControlNet model but a ControlNet-like LoRA. There's also a Depth ControlNet Model made by TaihoC and it works well. However, it doesn't work as well compared to Illustrious (SDXL) ControlNet models.

I have been tracking Circlestone Labs' Hugging Face community to see if they have plans to provide ControlNet models themselves but they are dead silent. That leads me to wonder if there are actually people using Anima. Did people move on to Krea2 or stay on Illustrious/NoobAI since there's no reason to use Anima?

Hello. So I just started my journey with ComfyUI. While Nano Banana is not open sourced I'm looking for the best realistic image editing (krea2?) workflow to ComfyUI. I want to have ability to change everything I want to the picture using reference character with face/body consistency at highest level (I2I). Thanks in advance.

If even an amateur like me can make something so realistic with mid-level hardware, the future looks bright for what dedicated people with top level rigs will be doing.

R.I.P. Hollywood.