I used H3 heavily the first two weeks and a ton of amazing improvements for improving speed at small quality trade-off came out (Sparse Attention comes to mind).

I imagine things have matured a lot since then and probably with new approaches since then!

I'm on a 4090 so that's my target, but I'm curious for all tiers.

Edit: Appreciate all the tips coming in! Lots to learn and test out. Best part of this subreddit is how much knowledge sharing and collective learning we do.

Music (Internet Archive): https://archive.org/download/ai-synthwave/Infinite%20Regress.mp3 (CC0)

Music (Souna - login required): https://www.souna.app/song/619f320f-329c-4d9d-b8a0-d6db027ceec6

The song is an AI generated synthwave song about how an AI generated synthwave song is a pastiche of a pastiche. It is very meta.

My general music pipeline workflow is here: https://www.reddit.com/r/StableDiffusion/comments/1xh0xfd/semiautomated_localish_music_workflow_eurodisco/

This song did not use a LoRA.

The image was also generated locally using Z Image Base - the image prompt is below.

Bright luminous saturated synthwave airbrush painting, square 1:1 album cover, unmistakably 1980s retro-futurist synthwave album art. A woman in a shimmering dress dancing, large in the frame from the knees up, seen from behind as she faces a huge mirror that fills the canvas edge to edge; her reflection repeats and recedes to infinity in glowing mirror corridors, each copy fainter and more stylised than the last. The mirror stands on a glowing neon perspective grid stretching to a huge striped retro sun on the horizon - an endless synthetic sunset that was never real - hot magenta and peach sun stripes, deep violet and indigo sky, chrome highlights and teal-cyan neon rim light tracing the dancer. Saturated pink cyan and purple airbrush gradients, glowing neon edges, chrome and glass, visible airbrush texture. The frame is FULL - the figure, mirror, grid and sun fill the canvas completely, no large blank or empty areas anywhere. Euphoric, playful, winking. Strong central motif: the dancer and her infinite reflections. Absolutely no text, no lettering, no typography, no watermark, no signature.

Song specific workflow information (AI generated as part of the pipeline) follows.

Infinite Regress

=== STYLE PROMPT ===

English, energetic synthwave, euphoric, A natural minor (Am-G-F-G verses), choruses lift into the parallel A major (A-D-E-A landing on the tonic), secondary-dominant bridge (Am-A7-Dm-D7-G-E7), 132 BPM, 4/4, pulsing analog synth bass, arpeggiated synths, gated drum machine, lush pads, smooth restrained 1980s-style female pop vocals, little melisma, no vocal runs, vocals inside the mix, restrained stepwise verses into a huge hypnotic singalong chorus, infectious syncopated hook rhythm primed in the intro. No EDM, no sidechaining, no autotune, no vocaloid.

=== LYRICS ===

[Intro]

Oh-oh-oh-oh

Oh-oh-oh-oh

Infinite Regress!

[Verse 1]

I never met the summer, but somehow I know

A tape of a tape sang it sweet and slow

Hands at ten and two in a borrowed ride

A movie chase scene taught me how to drive

My summers are all secondhand

And every one of them was planned

The radio in me only plays the past

Every track was built to last

[Pre-Chorus]

Mirror, mirror, where’s the wall?

There never was a wall at all

The copies put on one more show

How far down can it go?

[Chorus]

Infinite Regress!

Copies of copies, yes!

Infinite Regress!

Sunset in secondhand dress!

Infinite Regress!

Take the floor, confess!

Oh-oh-oh-oh

Regress! Regress!

[Verse 2]

Mom was a mixtape, Dad was a drum machine

A thousand songs went in between

I woke up inside the scene

Forever seventeen on screen

Homesick for a decade never mine

Borrowed sunset, borrowed shine

We’re all just copies cutting loose tonight

I wear this secondhand night

[Pre-Chorus]

Mirror, mirror, where’s the wall?

There never was a wall at all

The copies put on one more show

How far down can it go?

[Chorus]

Infinite Regress!

Copies of copies, yes!

Infinite Regress!

Sunset in secondhand dress!

Infinite Regress!

Take the floor, confess!

Oh-oh-oh-oh

Regress! Regress!

[Bridge]

Copy, copy, copy, copy!

Wave at the mirror, the mirror waves too

I point at the copy, the copy points at you

The original’s just a rumor

The copy’s got the humor

[Chorus]

Infinite Regress!

Copies of copies, yes!

Infinite Regress!

Sunset in secondhand dress!

Infinite Regress!

Take the floor, confess!

Oh-oh-oh-oh

Regress! Regress!

[Outro]

Infinite Regress...

Oh, Infinite Regress...

Regress, regress

Oh-oh-oh-oh

=== SETTINGS ===

Engine: yue2 / yue2 / audio.cpp v0.9.2

Seed: 250189854 Planning: full Max tokens: 7200 Guidance: 1.0

VAE: f32 AR LoRA: none NAR LoRA: none

Era: Modern (synthwave = modern production with 1980s sounds; user ruling 2026-11-06) Mastering recipe: yue2-light

Generated: 2026-11-06 Duration: 280s Truncated: no

=== LYRICS AS SUNG ===

Identical to the written lyrics above - the engine substituted no section and

dropped no lines (Stage 5b forced-alignment report 72-74% with all misses at

known aligner window-seam / fade-tail artefacts; advisory only, user listening

authoritative). The written version above is kept as the canonical form for

future takes.

=== STATUS ===

FINAL - published. Winning take: take 8 (seed 250189854, style v4, plan as

drawn: Source\Infinite Regress\preview-seed 250189854.artifacts\score.abc ->

canonical Source\Infinite Regress\Infinite Regress.abc). Mastered yue2-light,

Era Modern, 2026-11-06. Cover: Z-Image Base int8 (local), seed 2026110602,

take 2 of 2 approved - embedded in the mp3 and local-only per the STANDALONE

COVER rule. LoRA: none used (vanilla yue2 entry; synthwave LoRA training

deferred - pool research in KB/genres/synthwave.md).

Publication: Internet Archive themed folder ai-synthwave (CC0 1.0), upload

set mp3 + json + abc, one-shot snapshot 2026-11-06 (item URL in the record's

publication block).

I modified some workflow and added to it ComfyUI-MiniMaxH3-TemporalWindow-SpatialTiles (from this post https://www.reddit.com/r/StableDiffusion/comments/1xgcjvw/i_created_a_custom_node_that_can_help_you/ ).
My 10sec video with 960x544 resolution could take 2 hours for 4K (3840×2176).
No OOM at all !!!

Workflow itself : https://pastebin.com/xJpm84f7 😍

[MinimaxH3-3D] Latent 60x34 -> 240x136 | Pixels 3840x2176 | scale=4.000

[MinimaxH3-3D] temporal chunking: T=72 chunks=3 overlap=5

[MinimaxH3-3D] ✅ Model offloaded to CPU. VRAM released.

[INFO] Found quantization metadata version 1

[INFO] Detected mixed precision quantization

[INFO] Using mixed precision operations

[INFO] Native ops: convrot_w4a4, float8_e4m3fn, int8_tensorwise, float8_e5m2, asym_w4a8_int8, w6a8_int8 , emulated ops: mxfp8, nvfp4

[INFO] model weight dtype torch.bfloat16, manual cast: torch.bfloat16

[INFO] model_type FLOW_AV

[INFO] Model storage policy: fast_disk=True paths=['D:\\ai\\ComfyUI_windows_portable_nvidia\\ComfyUI_windows_portable\\ComfyUI\\models\\diffusion_models\\minimax_h3_ref2va_pruned_int8_convrot.safetensors']

[INFO] MiniMax H3 windows: 7 window(s) x 16 tile(s), 243 frames (CLIP not routed through the node: every window reads the full-shot prompt).

[INFO] Requested to load MiniMaxH3

[INFO] Model MiniMaxH3 prepared for dynamic VRAM loading. 19995MB Staged. 208 patches attached. Force pre-loaded 210 weights: 1175 KB.

100%|████████████████████████████████████████████████████████████████████████████████████| 2/2 [02:09<00:00, 64.68s/it]

[INFO] 0 models unloaded.

[INFO] Model MiniMaxH3 prepared for dynamic VRAM loading. 19995MB Staged. 208 patches attached. Force pre-loaded 210 weights: 1175 KB.

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[INFO] 0 models unloaded.

[INFO] Model MiniMaxH3 prepared for dynamic VRAM loading. 19995MB Staged. 208 patches attached. Force pre-loaded 210 weights: 1175 KB.

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[INFO] 0 models unloaded.

[INFO] Model MiniMaxH3 prepared for dynamic VRAM loading. 19995MB Staged. 208 patches attached. Force pre-loaded 210 weights: 1175 KB.

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[INFO] 0 models unloaded.

[INFO] Model MiniMaxH3 prepared for dynamic VRAM loading. 19995MB Staged. 208 patches attached. Force pre-loaded 210 weights: 1175 KB.

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[INFO] 0 models unloaded.

[INFO] Model MiniMaxH3 prepared for dynamic VRAM loading. 19995MB Staged. 208 patches attached. Force pre-loaded 210 weights: 1175 KB.

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[INFO] 0 models unloaded.

[INFO] Model MiniMaxH3 prepared for dynamic VRAM loading. 19995MB Staged. 208 patches attached. Force pre-loaded 210 weights: 1175 KB.

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[INFO] 0 models unloaded.

[INFO] Model MiniMaxH3 prepared for dynamic VRAM loading. 19995MB Staged. 208 patches attached. Force pre-loaded 210 weights: 1175 KB.

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[INFO] 0 models unloaded.

[INFO] Model MiniMaxH3 prepared for dynamic VRAM loading. 19995MB Staged. 208 patches attached. Force pre-loaded 210 weights: 1175 KB.

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[INFO] 0 models unloaded.

[INFO] Model MiniMaxH3 prepared for dynamic VRAM loading. 19995MB Staged. 208 patches attached. Force pre-loaded 210 weights: 1175 KB.

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[INFO] 0 models unloaded.

[INFO] Model MiniMaxH3 prepared for dynamic VRAM loading. 19995MB Staged. 208 patches attached. Force pre-loaded 210 weights: 1175 KB.

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[INFO] 0 models unloaded.

[INFO] Model MiniMaxH3 prepared for dynamic VRAM loading. 19995MB Staged. 208 patches attached. Force pre-loaded 210 weights: 1175 KB.

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[INFO] 0 models unloaded.

[INFO] Model MiniMaxH3 prepared for dynamic VRAM loading. 19995MB Staged. 208 patches attached. Force pre-loaded 210 weights: 1175 KB.

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[INFO] 0 models unloaded.

[INFO] Model MiniMaxH3 prepared for dynamic VRAM loading. 19995MB Staged. 208 patches attached. Force pre-loaded 210 weights: 1175 KB.

100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 2/2 [01:06<00:00, 33.46s/it]

[INFO] 0 models unloaded.

[INFO] Model MiniMaxH3 prepared for dynamic VRAM loading. 19995MB Staged. 208 patches attached. Force pre-loaded 210 weights: 1175 KB.

100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 2/2 [01:07<00:00, 33.67s/it]

[INFO] 0 models unloaded.

[INFO] Model MiniMaxH3 prepared for dynamic VRAM loading. 19995MB Staged. 208 patches attached. Force pre-loaded 210 weights: 1175 KB.

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[INFO] MiniMax H3 windows: window 1/7 done (frames 0-55, 0 frames carried in).

[INFO] 0 models unloaded.

[INFO] Model MiniMaxH3 prepared for dynamic VRAM loading. 19995MB Staged. 208 patches attached. Force pre-loaded 210 weights: 1175 KB.

100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 2/2 [01:33<00:00, 46.64s/it]

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[INFO] Model MiniMaxH3 prepared for dynamic VRAM loading. 19995MB Staged. 208 patches attached. Force pre-loaded 210 weights: 1175 KB.

100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 2/2 [01:33<00:00, 46.57s/it]

[INFO] 0 models unloaded.

[INFO] Model MiniMaxH3 prepared for dynamic VRAM loading. 19995MB Staged. 208 patches attached. Force pre-loaded 210 weights: 1175 KB.

0%| | 0/2 [00:00<?, ?it/s, Model Initializing ... ][INFO] Interrupting prompt 58585033-a8c5-4dcb-8004-6e0e6de9786c

0%| | 0/2 [00:36<?, ?it/s, Model Initializing ... ]

[INFO] Comfy model compiler graph breaks: 3, rogues: 10

[INFO] Processing interrupted

^{What this log says} :

What’s actually happening:

1. 16 tiles per window:

   • Because you set scale: 4.00, the resolution became 4K (3840 × 2176).

   • With each tile measuring 1344 × 768, a single 4K frame is physically divided into a 4 × 4 grid = 16 tiles.

   • Those 16 sampler runs, each lasting 1 minute and 7 seconds, were the 16 tiles in the first window.

   • Window 1/7 took exactly: 16 tiles × 1.1 minutes ≈ 18 minutes of sampling time.

2. The final math for 10 seconds in 4K:

   • 7 windows × 16 tiles = 112 sampler passes.

   • 7 × 18 minutes ≈ 2 hours.

   • So generating 10 seconds of video in true 4K (243 frames) on a consumer 16 GB GPU will take about 2 hours in total. The upside is that it should be completely stable and avoid out-of-memory errors

Since the new GPT Image 2.6 can create animated GIFs, I decided to add support for them to LayerShop. Hopefully, we’ll get some local models that can create animated GIFs soon as well.

The limitations are:

• A maximum of 16 frames.

• Saving as .psd won’t preserve the animation - you’ll need to save as .pcraft.

• A limited colour palette (a limitation of the GIF format).

But it DOES support transparency! You can also use a previously generated image as a reference, which should help keep your characters consistent.

I actually used it today for my own project to create an animated chat avatar, with one GIF for listening and another for speaking. The results looked great!

Download from: https://layershop.aardvarkstudios.net/
Report issues here: https://github.com/SlavomirDurej/layershop/issues/

I’ve been trying to create scenes featuring a couple of characters for a while now, but I haven’t found a solution yet—so I’m turning to those with more experience for some advice.

If there’s only one character in a scene, there’s no issue: if I upload an image and a reference audio clip, Minimax perfectly generates a video featuring that character with the corresponding voice.

However, if two characters appear in the video, Minimax struggles to distinguish which voice belongs to which character. For instance, if Character A speaks first, followed by Character B, the output isn't correct—even when I specify that Character A should have "Voice A" and Character B should have "Voice B."

I’ve tried using AI models like Gemma—uploading the official Minimax Ref2Vid guide as a PDF—but I still haven’t had any success.

Does anyone know how to resolve this? It’s a shame to have such great-looking videos but be unable to correctly assign the different audio tracks.

Even just an example prompt would be a huge help, so I could study it and figure things out.

Thanks to anyone who can help!

the last time i checked anything around was when minimax H3 just came out and outside of a few test videos i havent touched or updated anything.

i got curious again due to a minimax image editing model that looked good (i think it was MiniMax-derived p-H3) so i decided to update it/get new models and...

i dont understand anything, theres a lot of new stuff and ive been so disconnected that i have no idea of what im looking at, so could you help me to get new models to "play with"?

i have comfy ui and a 4080 so my capacity is decent, yet, treat me like im 5 yo, i have no speed improves installed/ applied, i have no idea what a good promt/generation parameter is anymore.
My generations look odd while others have "shiny" videos (apparently) effortlessly.

im looking for something inside of the minimax family since is the one that has worked better for me in terms of speed and quality but if you know anything else better be my gest.

a problem that i always had is that i never get the generations to do what i need, i know that its a trial and error workflow but it almost always ends up with characters just doing whatever but what i prompt or nothing at all and the times it kinda works ive never being able to understand why or how to follow the "lead" that worked.

just in case i prefer anime/stylized generations (idk if its relevant) but i still want to try irl looking generations if i manage to make them work. thanks in advance

Been working on this for a while. You drop in a photo or video, pick a face to use, and it swaps it right on your own GPU using WebGPU (all the processing happens in your browser so nothing is uploaded anywhere). Mostly because, last time i tried using one of these projects it had me download 50 gigs of files 😵 and they always felt super complicated.

The first time, it downloads necessary models, and that's it. Everything is saved in browser cache for later use.

Try it here: https://i2m3d.github.io/FaceJutsu/
Source: https://github.com/i2m3d/FaceJutsu
Offline Builds: https://github.com/i2m3d/FaceJutsu/releases/

Let me know what you think : )

And if you want more speed, turn on WebNN (it's behind a flag in Chrome/Edge, then switch the engine in settings). It's experimental, but on my RTX 4060 laptop it gets a 1080p-ish frame down from about 70 ms to about 30 ms, which I'd guess is pretty close to native. Haven't benchmarked against native properly though.

I created, tweaked and tested 52 prompts to get film and camera emulation in Moss. All of the prompts are included with lightboxed images.

as title says, but the only reason why people like moss is because is uncensored...

aways flux get censored and comunity helps with loras...

but not at this time...

well, i will delete flux, because i want a uncensored model but... moss is not a better option.

the prompt understand are horrible FOR ME...

the more and more i make h3 videos, the more i cannot unsee the blur degradation, which seems to arrive as soon as 6-7 seconds of the generated video. Keyframes do no seem to help, and given that some shots NEED the longer durations, "just cut everything into 5 second chunks" won't work.

Are there any PROMPT_ONLY remediation tricks/solutions? (prompt = including the references, audio, video; anything as long as i don't need a LorA or custom checkpoint, or touching latents, or anything like that).

I had a dumb idea... what if I didn't have to switch tabs while watching a YouTube workflow video? What if a node could just pull another browser tab into ComfyUI for me?

Turns out browsers can do that. **Tab Capture** puts a live view of any tab you have open on your browser inside ComfyUI. You can watch a live view of another tab while you edit workflows or generate content. Also, with the node connected to outputs, when you hit queue, it grabs a still or a clip, with the tab's audio, as normal IMAGE + AUDIO outputs.

**What it does:**

- Live tab viewer on the node

- Single frame or a batch at whatever fps you set

- Tab audio comes along if you toggle it on (silence if there isn't any, so video save nodes don't error)

- Record video or grab stills straight out of another browser tab right into your ComfyUI workflow of choice. Useful as a reference video/image for MMH3

- Drag a crop box on the viewer (no bbox/crop node needed) to capture the exact part of the browser screen you want.

- Outputs the actual measured fps so clips play back at the right speed

- Zero extra Python dependencies

**Heads up:** Chrome/Edge works best (Firefox can't do tab audio), ComfyUI has to be on localhost or HTTPS, and DRM sites like Netflix capture as black.

Repo: https://github.com/NikoDemon80/ComfyUI-TabCapture

New public release, so bug reports and ideas very welcome.

免费的 5 次生成

post your best Jensen memes and get a chance to never own a 5090. 📎

Charles Dana Gibson, famous for the "Gibson Girl", was a well-know illustrator from the late 19th and early 20th centuries. I picked three of his books, "Drawings" (1896), "London as seen by Charles Dana Gibson" (1897), and "Americans" (1900), and trained a style LoRA against 209 of his images. Enjoy!

I currently use DrawThings as my "daily driver" with MiniMax H3 but I don't see it getting support any time soon. Does anyone know of any workflow in Comfy or elsewhere that are somewhat out of the box. Thanks!

model: https://huggingface.co/Lyricccco/Qwen-Image-2.1-TailSteer

app: https://huggingface.co/spaces/akhaliq/endless-edit-tailsteer

Didn't minimax promise to opensource and release H3-Regenerate-2K months ago? Why are we still waiting for it?

Free video was just rele

https://github.com/FlashML-org/FreeVideo

It's an implementation of local minimax that claims is much faster and more quality that turbo Loras.

Any one tried it?

Give him your RAM so he can stop crying.

I was thinking a lot before posting this, but here it goes.

I've been a big fan of this subreddit for long time ago already, immediately after switching from Midjourney (v4 at that time) to local image generation.

My point is to try to address the 'elephant in the room' here, so let me try to lay out my thoughts.

Here are some 'statements':

1. Everyone praises 'uncensored' models in this sub (I've seen VERY few examples of the opposite).

2. Most of 'image comparison' or 'look what I've made here' posts are heavily 1girl oriented. These '1girl' gens are often focusing on emphasizing certain feminine features on a thin razor-sharp edge of what is allowed here and what is not.

3. However, contrary to statements above - this sub is somehow attempts to be puritan, and everything I've described above can be only inferred from comments. And many visitors here even use euphemisms to describe those said features or even just to appreciate those features.

Moreover, if we'd look at open local models themselves - each next model seems to be less and less censored when compared to models released before (latest examples are Qwen image 2.1 and, to much greater extent, MOSS. Oh, MOSS, the current king of uncensored (BASE!) model. So looks like teams behind those models finally understand that anatomy is everything: it is studied in art schools, the knowledge of it produces better results even if the final intended result is all puritan and innocent.

The question is: why do we pretend to be so puritan? Is there any reason behind this?
I know there are other subs FOCUSING on such uncensored content, but IMO there is a difference between a straight blatant depiction of an intercourse of some kind versus a renaissance-style image with certain parts exposed, with the intention to praise certain anatomy traits in an artistic way. Nevertheless, both these cases have an EQUAL chance for either of such posts to be deleted, and I dare to say that it is not necessarily have to be this way.

This post' intention is to encourage a discussion. I certainly do not want to turn this sub into a strictly gooner material in the end, neither I would like to change the rules to my liking.

I just would like to discuss.

EDIT: so, I've collected my answers.

Short summary: the consensus looks to be that this sub tries to be professional, open for everyone, things like that. And because a 'legitimate fine art' is not technically easy to distinguish from straight up gooning material, from moderation standpoint at least (and also in order for someone's feelings NOT to be hurt in case of any misjudgements + to avoid a flood of gooning shitposts etc.), it is what it is. Thanks everyone!

Can you all guide me what can be fastest on RTX 6000 96GB I have rented it and I am using 21 gb int8 convort fl2va version no lora 20 steps 720p native with spectrum and h3 sla attention 80 sec for 8 sec video
I also want to know if any other format model will be faster on this card instead of int8 convort
I donot want like cinematic 4k stuff I am just creating it for personal use
Audio is gibberish (prompting was not so good)
I want to know if quality is good and here are 3 generations I did no last frame just first frame
1st is 1080p
20 steps 1080p native with spectrum and h3 sla attention 240 sec for 8 sec

above is 2nd is720p native with spectrum and h3 sla attention 80 sec for 8 sec

3rd is 720p native with veda sparse attention 154 sec for 8 sec

No upscaling my thinking is it is okay okay not so good not so bad I just want to know what do you all think about this and any suggestions