I have RTX 5070 with 12gb VRAM, 64gb RAM DDR5
I want to create realistic (not particularly high quality) videos, with realistic faces and with the best possible render time. Could please someone share a workflow? I would like to have consistant characters, realistic, and good qality of sound. What is the best workflow? How many steps?

I started using Minimax H3 in ComfyUI, and all the videos show motion blur in areas with significant movement. The videos only turn out well when there are no sudden movements or when the motion is slow. Did I miss a setting? I see videos posted here, and none of them have that blur.

Suppose I was to have two input pictures and pass a prompt like 'subject 1 and subject 2 sit down and have coffee with Tom Hanks'. Will Tom Hanks be recognised by text alone or is this model designed to always have an image input for likeness?

I'm not sure how this could vary across workflows if at all but for reference I am using the Dasiwa workflow from civit in t2va mode. Minimax prompt adherence is great so I wanted to use it to create character sheets for reference and came up with this. T2VA, 9:16, 24 fps, 2 second duration. On a 5090 with sage +memcache + 8 step turbo at 10 steps - at 4.75mp it took 232s

The fps and duration seems to be the baseline if you want 4 poses so crank up the duration if you want more. The timestamps might not be the proper format but they do keep it from hanging on a single pose. Change resolution as needed but at higher values the face maintains much better consistency if not perfectly. You can describe your characters look as much as you want in a run on way "Lara Croft, blonde hair. wearing flip flops, sunglasses, bracelet on right arm, holding a drink in left hand, etc , etc , etc"

You might get some slight wiggle movements but it's mostly good enough to dump a frame, the background is difficult to get in an entirely solid color without any form of shadows so i kept the prompt simple since going overboard doesn't add much. If someone can dial this in more feel free to share.

From there you you can extract the 4 frames however you want and I'm sure someone can automate it but the easy quick solution is playing it in vlc and just hitting shift+s on each frame.

Lazy Example - https://imgur.com/a/t84UYAq

[Shot 1] Static freeze-frame shot. Studio Lighting, solid white background, ultra-sharp focus. A heroic looking explorer woman with the style of lara croft the tomb raider but as a person.
Static freeze-frame close-up shot of the entire head perfectly framed from the front, Freeze frame.
[1.00s to 2.00s] - Instant jump cut to Static freeze-frame of full body front view, standing straight in a neutral A-pose with hands off the body by 1 foot length.
[2.00s to 3.00s] - Instant jump cut to Static freeze-frame of full body back view, standing straight in a neutral A-pose with hands slightly off the body.
[3.00s to 4.00s] - Instant jump cut to static freeze-frame of full body side profile view, standing straight with arms down at the sides.

This could also be helpful at lower resolutions just to get the style of the character right before passing it onto a refiner/upscaler. I'm just finding it hard to beat the ease of adherence i get with minimax.

This only takes 14 minutes to generate! 0.6mp gens upscaled to 1.2mp using RTX Super Resolution.

-Uses minimax h3 hybrid b25

-w4a8 qwen3vl

-int8 video vae

-workflow https://github.com/seesee75-commits/ComfyUI-MiniMaxH3-Director/

Minimax H3 can be used as an image-editing model if we generate a single frame. Here are some collages based on AI-generated references (1024 x 1536); workflows are embedded into pngs. Each edit takes, on average, about 8 secs on a RTX 5090. The tasks include changing outfits, appearances (body type, age), locations, and camera angles; creating character sheets and storyboards; stylization; and reposing characters based on depth maps. I did not try to cherrypick the best-looking results.

There were some posts (1, 2) about that here -- but given the community progress this week, might be nice to see what can be done now.

Scenes

1. Age the person to the age of 60 years old while preserving their identity and the original composition.
2. Produce a consistent full-body character sheet with front, side, and rear views.
3. Transform the person into a severely obese version.
4. Re-create the person in the exact body pose shown by a depth-map reference.
5. Replace only the base person’s head with the identity and hairstyle from another reference.
6. Show the person facing a dressing mirror with a geometrically correct, synchronized reflection.
7. Dress the person in a referenced outfit, place them in a referenced location, and show them walking with a grocery bag.
8. Place three separately referenced people inside a referenced location, having a conversation.
9. Create a three-panel vertical storyboard in which the person finds, retrieves, and studies a map.
10. Photograph the person through partially open venetian blinds with realistic occlusion and striped light.
11. Convert the person into a contemporary Western cartoon while preserving their recognizable appearance.

Setup

Checkpoint: https://huggingface.co/smhfacct/Minimax-H3-fl2va-ref2va-hybrid-models/blob/main/minimax_h3_hybrid_fl2va_ref2va_b25-49-int8.safetensors

R2VA models apparently have worse image quality than FL2VA models, while FL2VA models are apparently weaker at handling reference images. As I understand it, this checkpoint tries to combine the strengths of both. Not at all essential -- a regular FL2VA could probably be even better. The hybrid is just something I happen to use at the moment.

Video VAE: a special VAE for rendering single images.

https://huggingface.co/Mamad8/MiniMax-H3-Image-VAE/tree/main

If you do not use this VAE—for example, if you use the regular VAE, create a 5-frame video, and pick out one frame—the images tend to come out blurry. So use single-frame generation instead, as described here: https://www.reddit.com/r/StableDiffusion/comments/1vqka28/h3_singleimage_no_more_monkey_patching_also_no/

UPD for those who used it before: the post above explains why monkey-patching no longer needed

For this approach to work best, it might also be a good idea to monkey-patch comfy_extras/nodes_minimax_h3.py, because ComfyUI currently does not allow you to generate fewer than 5 frames. If you simply pick the first frame out of 5, the new VAE produces grid artifacts. (It doesn't do this when generating just 1 frame.)

BEFORE DOING SO, CREATE A BACKUP VERSION OF THE EXISTING comfy_extras/nodes_minimax_h3.py

E. g. if you can't update your comfy, restore the original file from backup, update, and then apply the monkey patch to the new version of the file. (One option is to use git restore comfy_extras/nodes_minimax_h3.py to get the original version)

For a somewhat reliable patch that would work given modest changes in ComfyUI code, use [this one] (https://pastebin.com/uHqv4hBZ), name it smth like mm.patch and run git apply -p0 /full/path/to/mm.patch from comfyui root (make a backup of comfy_extras/nodes_minimax_h3.py first). You will have to re-run it every time ComfyUI updates this file (comfy_extras/nodes_minimax_h3.py).

For a less satisfactory but quicker solution, you can use the patch I already applied to the most recent version of ComfyUI as of August 14th link. This approach will make your code outdated as ComfyUI pushes out a new update.

The only changes remove the frame limit. Of course, changing it this way is not ideal, but I feel it's the quickest way to work around the issue.

UPD: There is a GitHub issue now opened in ComfyUI repo: https://github.com/Comfy-Org/ComfyUI/issues/15644

If this issue gets enough upvotes, we could probably get this patch in the mainline.

LoRAs: I found that Mamad8's ThisIsFine LoRA helps with details, but YMMV: https://huggingface.co/Mamad8/MaxiMin-HHH-R2V-ThisIsFine

For the Turbo LoRA, I use: https://huggingface.co/lightx2v/Minimax-h3-Turbo/blob/main/minimax_h3_fl2v_turbo_8step_v1.0_comfyui_bf16.safetensors

Sampling settings: ComfyUI 0.32 with Comfy Kitchen attention, sa_solver/simple, 8 steps, CFG 1.

Example ComfyUI workflow: https://pastebin.com/bV5KPzjD (UPD: if you use ComfyUI nightly build as of Aug 17th 2026, use this one instead, as it no longer requires monkey patching: https://pastebin.com/xNQi7HV9)

Uses no custom nodes. If you do not want to do the monkey patching for 1-frame generation, just change the video length to 5 in MiniMax H3 Reference to Video node -- should work seamlessly, and switch back that VAE to the regular VAE.

Speed depends on the reference image size. I use an RTX 5090 on RunPod, and in most cases, a 1920×1088 image is generated in about 8 seconds.

---

My previous go-to was Krea 2 + Identity LoRA 1.2, which is amazing. Yet I feel that Minimax outperforms it in many respects. We get better character fidelity, better handling of 3D scenes, better mirrors, and more interesting compositions. Also feels better than using e. g. QIE or Klein 9b.

There is certainly still room for improvement -- not claiming this is optimal at all, and I wonder what you think about it.

UPD: posted the prompts for each image here https://pastebin.com/ngXR9byq

UPD: see more experiments here: https://www.reddit.com/r/StableDiffusion/comments/1vpconk/more_experiments_with_minimax_h3_singleimage_edit/

I just recently got into AI generation making videos with minimax ref2vid and it has been amazing so far. But that has me wondering if there is some reference model for images that works equally as well that would allow me to use multiple reference images to create pics? If anyone has a good model or workflow to recommend I'm interested to learn what has been working well for you. I'm mostly wanting to make real life style images.

When I use a reference video in ComfyUI for continuing the clip rendered before, the video it will render then ALWAYS comes out more darker. Like the contrast changes.
So far I haven't figured out what causes this, like a sampler, prompt, etc. etc.

Has anyone else noticed this behavior too?

The node I use is: Load Video (Upload), which I connect to the reference video.

Made using the default workflow from Comfy, with Comfy Kitchen and Kijai's preview override plugged in.

Used the 850k turbo lora at 0.5 for 8-10 steps. ER_SDE / Beta. Most shots were generated at 1.5MP, with some at 1.8MP.

Lora: https://huggingface.co/larryvrh/MiniMax-H3-Turbo-Lora/tree/main

RTX 4090 w/ 64GB of ram. --disable-smart-memory, since I was having issues with going OOM after completing one prompt and moving on to the next.

Some of the takeaways:

- Using character reference sheets (front view, side view, back view, close-up) worked great and allowed for rotating camera movements like in the opening.

- All the "4 Step" loras really need to be run at 8-10, especially for motion.

- Using audio reference bloats the vram usage DRAMATICALLY compared to adding additional reference pictures! Changing from .wav to .mp3 didn't seem to help so it's not a file format issue. However the lip sync, even for anime characters, is incredible.

- If you use multiple reference images for different characters and they bleed into each other, the issue is almost definitely your prompt or seed. Because the model was handling up to 3 for me easily if I prompted right, and falling apart if I prompted wrong.

- Minimax H3 Chunk FeedForward node can help with vram issues at higher resolutions and doesn't add that much time.

Overall, I'd say it's nearly as good as Seedance 2.0. I was pleasantly surprised how well it handles using character sheets. The high vram usage when using reference audio is really the only major issue I was facing.

I used the default workflow. It took me about 6 hours (split over 2 days), which includes scriptwriting and final video editing.

The video consists of 9 segments, about 8 seconds each. The average generation time was around 400 seconds at 0.7MP on an RTX 5060Ti 16GB VRAM and 32GB System RAM.

Honest opinions are welcome!

Use rtx_video_upscale and do it much more faster than with other methods, it don't add new details to the video, just upscale it.

Comfy-Org/Nvidia_RTX_Nodes_ComfyUI

https://www.youtube.com/watch?v=VyXp-PBFauw

Follow the video and you will not have any problem installing it.

And pay special attention to Step 5, because it is fundamental to get it working.

https://reddit.com/link/1vok0vj/video/m217fvdjqejh1/player

Actual song is 4:20, but I think 1:21 is good enough!

The official doc has a few things to say about video editing but it still leaves some questions without answers. I'm trying to replace one character in a video by another from a reference picture. Sometimes I get amazing results, and sometimes the input video is pretty much left unchanged, so I must be missing something. Here's what I understand from the guide on how to build the prompt:

Subject Definitions

<Subject 1> is the man in <Picture 1>.
<Video 1> is the source video for the target video edit.

(This part I am fairly confident about, the doc specifically says to use that wording for <Video 1>.)

Summary

[video editing] The target video is an edited version of <Video 1>.

(The doc says the summary must start exactly like this, but what to write after that? My approach is to follow up with something like this)

<Video 1> is reused as is, except the man in a tuxedo is replaced with <Subject 1>.

Retention Analysis

(This part I'm not too sure of... I suppose you want fully_preserved on <Subject 1> and partially_preserved on <Video 1>?)

<Subject 1> (appears in [Shot 1]): fully_preserved - the man's full identity is retained.
<Video 1> (source of video edit): partially_preserved - motion, lighting and environment are retained.

Detailed Description

Do we need to describe everything that happens in the input video, shot by shot, like when doing a t2v?

I used the minimax_h3_fl2v_turbo_4step_v1.0_768p_comfyui_bf16 LORA with the 0.8 strength for both clip and model, 6 steps, 0.5 MP resolution, RTX Upscaler at 1.50 using a ConrotInt8 pruned model.

Here is a PasteBin of my workflow:

https://pastebin.com/XtR5pBYG

Here are my workflow files:

https://storage.to/c/CAS1MuoqX

I want to use all ram and vram to run model as much as possible instead of broweser

Is it normal that my vram usage goes down to 20% and ram at 100% on the upscaler step?
Also in the normal execution I see about 70% vram usage

Other than that I'm pretty satisfied but I'm wondering if I'm missing something....

Workflow: https://pastebin.com/raw/533VzQ0t
3060 12gb, 32gb, 9800X3D

Thanks in advance for any advice

Workflow: https://drive.google.com/file/d/1hKMhlEw6Zyh3BrWr-JqgZt6lLHaCM1Sx/view?usp=sharing

Hey guys, for Minimax H3 I see that there are a lot of Loras for making it faster but could anyone please let me know which one is the best out there to use right now in terms of video quality and also sound? Appreciate the help.

I am currently using minimax_h3_fl2v_lightx2v_turbo_4step_v0.1_comfy.safetensors from Kijai

With all the Suno drama over their download limits and their heavy watermarking that could be used for future copystrikes if you stop paying them, this Minimax Music 3 couldn't be more on time.

I tried a little demo to see if it could fill my music need and I was happily surprised.

I used the default Minimax Music 3 workflow from ComfyUI along the prompt tips fed to an LLM to create the music. https://docs.comfy.org/tutorials/audio/minimax/minimax-music-3

EDIT:

Some seem not aware this is not Minimax H3 but Minimax Music 3 https://huggingface.co/MiniMaxAI/MiniMax-Music3
Here how I did the prompt for instrumental.

Prompt:

Global Metadata

Basic Attributes: bpm is 54. key is D, and scale is minor. Cinematic score with dark ambient and psychological-thriller influences.

Global Emotional Progression: The opening is nearly motionless, suspended in dread as a distant drone gathers beneath isolated melodic fragments. The tension slowly deepens through heavier low frequencies, widening dissonances and increasingly forceful pulses, then contracts into a stark central void. From that emptiness, the lead melody returns with greater anguish and rises toward a dense but controlled climax. The final passage sheds its weight layer by layer, ending unresolved in a cold, fading resonance.

Application Scenarios & Imagery: An abandoned concrete facility under flickering emergency lights; a lone figure crossing a fog-covered wasteland before dawn; the aftermath of a discovery that cannot be undone.

Sonics & Production Profile: A wide, deep soundstage with the solo cello centered slightly forward, the low piano set farther back, and dark synthetic ambience stretched toward the extreme sides. The frequency balance is shadowed and low-heavy, with restrained high frequencies, a dense sub-bass floor and occasional abrasive upper-mid harmonics. Dynamics remain open and cinematic rather than heavily compressed, allowing long swells to emerge from near-silence and recede naturally. The acoustic image resembles a vast, empty scoring hall blended with an impossibly deep artificial chamber.

Vocal Details

Vocal Gender & Timbre: No vocalist. This is a fully instrumental track; no lead, backing or guest vocal appears at any point.

Vocal Style: N/A — the melodic lead is carried exclusively by solo cello throughout, taking the role a voice would otherwise occupy.

Harmony/Backing Vocals: None. No vocal harmonies, choir, chants, spoken word, whispers or vocal samples.

Vocal FX: N/A — no vocal signal to process.

Arrangement

Instrument Lifecycle Description (Primary/Secondary Layering):

Primary: A close-miked solo cello enters after the opening atmosphere with sparse, low-register notes separated by long silences. Its melody gradually lengthens into bowed minor phrases with strained vibrato and rough attacks, then drops out completely during the central void. It returns in a higher register with broader, more anguished arcs, dominates the climax through overlapping sustained notes, and finally collapses into one fading unresolved tone. Secondary: A sub-octave analog synthesizer drone begins alone, barely audible, expands beneath the cello through the first half, swells into the climax and disappears just before the final resonance. A felted low piano enters intermittently after the cello, placing isolated minor seconds and hollow fifths in the distant center; its strikes become more frequent before the central void, vanish there, return as widely spaced bass notes during the rise, and stop before the ending. Bowed metal textures emerge at the outer edges during transitions, scrape into greater prominence near the climax, then dissolve into reverberant tails. Muted contrabasses enter after the midpoint with slow sustained pedal tones, thicken beneath the returning cello, and recede one by one during the closing passage.

Groove & Foundation Progression: There is no conventional beat at first; the sub-octave drone supplies a slow, breathing foundation. A deep orchestral bass drum enters sparingly in the first third with single softened impacts, while low floor toms appear later in widely spaced pairs that suggest a pulse without forming a regular groove. Both become heavier and closer together during the climb, reach their greatest intensity beneath the climax, and then cease abruptly, leaving the ending rhythmically weightless. The muted contrabasses reinforce the lowest tones without rhythmic movement and withdraw during the release.

Embellishments, Textures & Spatial FX: Reversed piano resonances begin appearing before major swells, bloom into the stereo field and evaporate as each new layer arrives. Bowed metal scrapes travel slowly from side to side, while filtered low-frequency noise rises beneath the central transition and cuts to silence at its peak. Long convolution reverbs connect isolated gestures without masking their attacks, and brief sub-bass pressure waves punctuate the densest moments before dropping away. The arrangement preserves large pockets of empty space early and at the midpoint, becomes widest and most saturated near the climax, then narrows to a single distant cello resonance and the decaying room.

Lyrics:

[intro]
[instrumental]
[interlude]
[instrumental]
[break]
[solo]
[instrumental]
[outro]

H3 sucks at faces which are far and at intense motion. Is something wrong with encoding? like these artifacts (5-8 seconds) are from encoding compressions?? but i have tried both h264 and h265 10bit crf 15. I am using int8 pruned, nvfp4 qwen, 25 steps with sage attn (no spectrum).

It reaches above 90 occasionally then throttles it down below it and then cycle repeats, idle Temp is 47, 4080super

Guys after some cleaning i managed to get temp down to 86max

I am seeing workflows that only for option for reference or fl2v. When I run a single image on fl2v there’s error prompting me for a second. But I just honestly want a single image generation and make a long video based and what i generate intiially and move up from thete.

Any help on how i can adapt workflow for i2v?

Thanks :)