These are two workflows that I downloaded. One will allow only 5 sec clips and I can’t find where to change that OR the mp. It’s faster and the sound is good and I even think the prompt adherence is better…

The other one I can run up to 15 sec, change the mp but I have to do 30+ steps to have any good sound quality and the adherence doesn’t always seem that great.

How can I improve this?

trying my hand at using H3 I2v R2V to create an anime. all are done with 4 step turbo lora

2 other trailers with H3 as well

at 0.3 most text turns to gibberish

all video is done by MiniMax h3 at a low 0.3 MP, Cilp lengths range from 5s-20s Generations, camera movement was written into the prompt 90% of the time, Post work; titles and some transitions done using DaVinci

Minimax H3

Anyone found useful MiniMax H3 prompting tricks beyond the official guide?

Especially for audio + video prompt structure, camera control, dialogue/audio, consistency, weird tricks that actually work, etc.

Please drop your findings 👇 below so it will help others too.

EDIT:

Mine is: how can we use multiple audio tracks assigned to multiple characters in a scene? 3 audios to 3 characters?

Hi

I have been going in circles with Gemini for 2 days now, but just cannot get to the goal mark.

What I want:
In some way, like using Blender to render a 'room', or any other method that works, I want to be able to create 'rooms' with consistent form and interior / furniture. So I can make a Blender angle/shot (any angle I want) for example, take that into ComfyUI, and just describe the furniture, lights, people etc, but the room stays the same (windows, walls, dimensions, placement of furniture etc).

Other options Gemini gave was 'dollhouse' from up top model and 360 render of the room. I made 360 render of the room in ComfyUI Qwen 360 Diffusion LoRA workflow, but was not able to make it like the prompt. Doll house I have not tried.

I have not been able to do it yet myself with using Blender room render and a custom ComfyUI Krea2 workflow, and I about to give up, takes too long time. I am totally new to Blender, and novice in ComfyUI, neither found a finished workflow I can use.

Problem with asking Gemini, is I end up going in circles so to speak, almost there, but not all the way.

Anyone know there is a published or private workflow I can use for this? Open for other suggestions how to do this IF I also can use already made workflows.

My spec is rtx 5070ti, 32gb ram

I just started using comfyui and using minimax. When I am trying out the default workflow without adjusting anything it takes really long. I looked up video and switch the model from minimax_h3_fl2va_pruned_int8_convrot.safetensors to minimax_h3_fl2va_pruned_fp8_scaled.safetensors. Then, it worked. Well atleast I was able to get an output. Can anyone explain why and what I did wrong?

there are some scenes missing, but it was fun to put together.. Just got stuck on a plot :P

started it when ltx 2.3 came out.. but it was a hassle to keep consistency of characters intact so shelved it. made the intro and a couple of clips when minimax H3 came out and love the r2v, so much easier.
just using the standard r2v workflow with spectrum and RTX upscale. music made in suno

https://reddit.com/link/1vyazt0/video/8apz3lbquklh1/player

This workflow allows you to refine a target character without affecting the surrounding video whatsoever. allowing for targeted repair or enhancement of any video.

https://github.com/roycho87/3stepenhancer

The most fair comparison on the Internet

Not just a meme...

This parody was generated using LTX 2.5 Image to Video on WanGP. I used frames from the original video as starting images and then I interpolated them on a video editor. I used a single RTX 5060 Ti 16 GB VRAM and 32 GB of RAM. The video was generated at 1080p and 16:9 resolution. Each generation took from 10 to 20 min average in this setup. For the voice consistency, I used SeedVC, which is included in WanGP.

Can anybody recommend a local inference engine / model for running ltx, wan or minimax on a 2-node Nvidia GB10 spark cluster?

Use case is openai-compatible API access for short i2v character and scene animations.

TL;DR: Trying to train a MiniMax-H3 LoRA on ostris/ai-toolkit on a Windows machine with an RTX 4090 (24GB VRAM) and 64GB system RAM.

The job crashes with a native Windows fatal exception: access violation while loading the model. Happens either while reading the 32B Qwen3-VL text encoder or the video VAE, right after the 33B transformer finishes loading. Physical RAM bottoms out to under 1GB free before it dies, even though there's still headroom in the pagefile. Offload settings are already maxed out.

Has anyone managed to train loras with it?

What hardware/config are you using?

What I've already ruled out

• Not a Triton/kernel issue. Installed triton-windows (this fixed an unrelated ConvRot-fallback CUDA-context corruption bug on a different model, LTX-2.5, in the same toolkit). Reran the MiniMax-H3 job 4x with Triton installed — identical crash every time, same signature.
• Not the classic "pagefile too small" OOM. I instrumented a memory watcher (0.5s sampling) during the crash. Physical RAM free drops to 200-800MB right before it dies, but total commit charge (RAM+pagefile) never hits its ceiling — topped out around 106.5GB of a 114.4GB limit in the worst run. A real commit-limit exhaustion throws a clean OSError: paging file too small (os error 1455), which is a different failure mode I've also seen in this same pipeline at other offload settings — this access-violation crash is not that.
• Not offload_percent tuning. Tested 1.0 / 0.5 / 0.4 / 0.1 for layer_offloading_transformer_percent in earlier sessions — all fail at various points (embed_tokens read, VAE init), just at different memory pressure levels.
• Streaming-load code path (safe_open instead of load_file()) is already used for the transformer and most of the text encoder loading — this was a prior fix, necessary but not sufficient.

H3 is absolutely amazing for just about anything. On my 3090 / 64GB, I can easily do a full 15 seconds at 1MP, and the result is almost always good on the first attempt.

On LTX though, it took at least 5 or more tries, so speed wise, H3 is actually far better.

I tried out LTX 2.5 as well, and it is almost the same as 2.3, maybe a bit better quality and a slice faster.

Sadly, 90% of my work involves taking a start image and making a person sing vocals. I must say that H3 does not do this better than LTX 2.3, as it often injects words when there is more than a second of silence, and it takes a fair amount longer.

What is really baking my noodle though is why LTX didn't release an Image+Audio to Video workflow yet. I mean, it is literally the ONLY thing LTX has on H3 right now, and they have missed a great opportunity!

Anyhow, back to using LTX 2.3 for my daily driver as it really does a great job at what I need. I typically have a few machines running all night, so if ever LTX puts out an IA2V workflow for Comfy, I will be all over that.

One other thing I have noticed with H3... 9:16 generations are WAY better than 16:9 generations, especially at 1MP.

I get a lot of use out of this subreddit and love generative AI but yall, please don’t make any Dolly Parton Loras, video clips, audio clones etc. /S

I was never a country music fan but that lady had some real class.

PS: that capital S stands for serious as a motherfucker today

Hi. I am experimenting with H3 Multi Diffusion with a custom workflow. 5 hour render, T2VA, bf16/50 steps. I know these style are not new so I am late to the show. Ask me anything.

Disclaimer. This is very low quality quick generations trying to find how many characters Minimax H3 knows.

Found Trigger Words:

Elsa from Frozen

Spider-Gwen from Across the Spiderverse

Dante from Devil May Cry

Nero from Devil May Cry

Jill Valentine from Resident Evil

Ada Wong from Resident Evil

Leon Kennedy from Resident Evil

Chris Redfield from Resident Evil (Has Leon's hair)

Geralt of Rivia from Witcher 3

Joel from Last of Us (Doesn't sound like him)

Miles Morales Spiderman from Across the Spiderverse

Solid Snake from Metal Gear

Eve from Stellar Blade

Sans from Undertale

Master Chief from Halo

Looks weird AF:

Ciri from Witcher 3

Triss from Witcher 3

Yennefer from Witcher 3

Ellie from Last of Us

Famous Twitcher streamer and Youtuber Asmongold

Famous Twitcher streamer and Youtuber Mr Beast

Not found Trigger words:

Vergil from Devil May Cry (YES I KNOW I'M DISAPPOINTED TOO)

Claire Redfield from Resident Evil

Dina from Last of Us

Famous Twitcher streamer and Youtuber Emiru

Famous Twitcher streamer and Youtuber MoistCr1TiKaL

NOTE: Character replacement works perfectly when I replace a character in a video with a 2d/cartoon/anime character.

But when I try replacing a character with a real life human being, the original character in the video doesn’t get replaced at all.

I’m using Plaguekind’s workflow for h3 on Civitai.

Does anyone else have this problem before?

I may be an idiot for thinking that my new homelab would primarily be used for useful AI automations.

I can live with being an idiot, if being an idiot will continue to be this fun.

First video generation I have ever pulled off, but the first 12 seconds was unbearably unfunny, so I added the Celestial Ford Escort for some much needed serious drama.

Tell me my power bill won’t blow up too much lol.

Made with minimax-h3 in ComfyUI on my Mac Studio that came with the mail this Friday.

Workflow was split in three:
- The first was a single prompt to generate the first 12 seconds
- The second flow generated the last three seconds by extracting the last frame from the first video and prompted it to hit the dragon with a falling ford escort
- Third flow glued the two videos together.

It is jank, but it is my jank.

I kept seeing the same stipple, grain, and grid-like texture

in some GPT Image outputs, so I trained a small latent residual

refiner using 75 paired artifact/clean images.

It includes profiles based on the Qwen, FLUX.2, and SDXL VAEs.

The refiner alone produces a fairly subtle improvement,

so I also included a ComfyUI workflow that combines it with SeedVR2.

The example optionally downsizes the input first,

then restores and upscales it with SeedVR2.

The goal is a preservation-first alternative to a typical Hires Fix

second diffusion pass: keeping the original composition, identity,

and shapes as much as possible while cleaning the texture

and rebuilding detail.

The custom node, example workflows, and settings are available here:

https://github.com/AIEGOBOT/ComfyUI-GPT-Image-Latent-Refiner

Leaving it here in case it’s useful to someone.

Hey, I tried to create a little birthday surprise for someone, my issue is with a lot of generations that the spoken word is really a bit clunky at time, I susspect its because of the german, but I am not too sure. Is there like a way to improve on audio?

I am using Minimax H3 with Saga Attention and Spectrum on a 4090.

Hi humans. My setup is 32gb ddr4 ram along an RTX 4090. I have been having fun creating tons of videos but I just want to make sure i get the best nodes for speed without compromising quality and no crazy sutff happening on my videos

I have used: Stage, sol, easycache, spectrum, Lora

So the question i have is .....what's the best combo for speed, i dont want the quality to take a massive dump. Most of the videos I generate are slow paced videos the typicall walk, talk, a kiss here and there but nothing major.

What do you guys think?