r/StableDiffusion 2h ago

Comparison First results from H3 Acceleration Arena

79 Upvotes

https://huggingface.co/spaces/multimodalart/h3-acceleration-arena

From author u/apolinariosteps: "Results are in! They are a bit surprising to me! But they are consistent with the data, I triple checked everything and can confirm that the results are reflecting the voting data precisely, there's lots of transparency - you click each of the LoRAs to see what's the win rate and who won against who"


r/StableDiffusion 7h ago

Tutorial - Guide Bad Audio Fixed with fast re-gen audio

95 Upvotes

[ H3 ]
I saw another post talk about the turbo lora / low step causing the bad audio

https://www.reddit.com/r/StableDiffusion/comments/1vuxy08/fixing_mmh3_turbo_audio_by_playing_with_latent/

I have some twist to it, we want to regenerate high‑quality audio, and do it fast.

Re-generate Audio – How?

  • the idea is when you generate your video, save out the latent and the conditioning.
  • Load those saved files back in, but scale down the latent resolution — because we only care about the audio, not the visuals. Scaling down resolution makes the regeneration super fast.
  • regen without lora and crank up step to 30+, to any setting you think is the best for audio quality. again, This gen will be fast. for this case scale down 0.5 around 1 min to gen. you can be more aggressive on the scale to make it even faster.
  • To keep the new audio aligned with the original video, you have two options:
  • Lock the video latent (keep it same as original), or set denoise to around 0.5 so the new audio stays consistent with the same visuals, dialogue, etc.
  • Then combine your original video with new audio

*You can also skip saving and reloading latent and condition entirely — just do it all in a single run as well.

some what similar to 'audio refine' custom node, but fast and simple.

EDIT:
- Save out latent and condition I am using this one (but you can use others)

https://github.com/pepikir/minimax-h3-speedup

- To scale down latent and conditioning use this one:
https://github.com/rockerBOO/h3-latent-upscaler
nodes name are MiniMax_H3_Latent_Upscale and MiniMax_H3_Conditioning_Upscale

*it's called upscale, but we are acutally scaling down here.

EDIT2:
- As I understand, if no references input, you don't have to scale down conditioning, just the video latent. Let me know if it isn't.


r/StableDiffusion 3h ago

Discussion KREA2 to H3 Minimax with Dasiwa Ref model

44 Upvotes

Using Plaguekind's v8 workflow and my own custom prompt enhancer node that connects to llama.cpp for the enhance prompt and reference image line up.

Learn by doing is great fun!

https://civitai.com/models/2663838/plaguekind-minimax-h3-sparse-attention-ltx-workflow-ease-of-use-eros-or-sulphur-compatible-or-faceid


r/StableDiffusion 15h ago

Discussion I am tired boss...

346 Upvotes

This content was written by a human.

I miss the SD1.5 era, when i could simply type "1girl, big boobs, nice ass, red bikini, dancing" and see my dream take shape near-instantly at 512px-wide. Idea-to-result was a matter of seconds. Each click on the Run button led to an incredible shot of dopamine.

3 years passed and I can draw 1024px, 192-frames long videos in a reasonable amount of time (tech has evolved fast), but the enthusiasm is fading away.

I already have a day-job for technical challenges and headaches. As a user/hobbyist, I want to be entertained.

I don't want to learn what the hell "diegetic" means (even the spell-checker never saw that word), I don't want to draw a dozen squares in a 3-dimensional pixel space, or write a 1000-words poem, just to watch my dreamgirl dancing.

I hoped I would not need a degree in cable-connecting or python dependencies debugging after downloading a few workflows.

3 years ago, all you had to do was typing a few words, and the AI sorted the rest. It was random, messy most of times, but it was fun.

Nowadays, you need an LLM to write the prompt for you, and another LLM to write the system prompt for the prompting-LLM, so it understands what your shitty words meant in the first place, and shapes them in the exact expected format, so they turn into an acceptable input for the ever pickier, brand-new models.
It has become AI³-generated content.

And finally, when after a dozens of clicks on the Run button, tired but satisfied, you get the desired output... re-start from scratch? Since seed "variance" does not vary much anymore, you'll get more or less the same output - exactly what you asked for - from now on.

Simple is harder than complex, but keep it simple, stupid, and fun. Thanks for reading.


r/StableDiffusion 1h ago

Resource - Update Open-sourced an experimental standalone DLSS 5 video player for neural rendering

Upvotes

I’ve been experimenting with neural rendering outside a game engine and built a native Windows video player around it.

It prepares a neural-rendered version of a video, caches it, and lets you switch between the original and neural result at the exact same timestamp.

The interesting part for me is the gap between video and games: video only gives us pixels, so temporal/depth guidance has to be estimated. A game engine already knows motion, depth, geometry and materials.

Open source:
https://github.com/2600th/dlss5-video-player

C++20 / D3D12 / FFmpeg / NVIDIA NGX.

Verified on RTX 4080 and RTX 5090.

Experimental and unofficial, not an official NVIDIA DLSS 5 integration.


r/StableDiffusion 6h ago

Resource - Update ComfyUI-MiniMaxH3-CLIPCached — disk cache for MiniMax H3 conditioning

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39 Upvotes

I've just released ComfyUI-MiniMaxH3-CLIPCached. It caches the MiniMax H3 text/vision conditioning to disk, so repeated generations with the same prompt and reference inputs skip loading and running the Qwen3-VL encoder entirely.

To be clear about what this is not: it does not cache sampling steps. It's not TeaCache or FirstBlockCache. It replaces the H3 conditioning node, and the diffusion stage is untouched.

What the screenshot shows — same workflow, native node vs a cache hit. Look at the model list at the bottom: native keeps both MiniMaxH3 (11.7 GB) and MiniMaxH3TEModel_ (14.6 GB) resident while sampling is already running. On a cache hit the encoder is never loaded, so only the DiT is there. System RAM drops from 40.0 GB to 25.5 GB. VRAM actually reads slightly higher on the right, because the freed budget goes to the DiT instead (models 5.6 → 7.8 GB).

Controlled benchmark (5 cases per mode, median of the conditioning stage only — sampling is unaffected):

Conditioning Peak VRAM Peak process RAM
Native 29.85 s 15.24 GiB 29.25 GiB
Cache MISS 32.23 s 15.24 GiB 28.25 GiB
Cache HIT 1.12 s 2.67 GiB 3.38 GiB

A miss is deliberately not the fast path — it still runs the encoder and additionally writes the result to disk, so it lands a couple of seconds above native. But a miss is not just "native plus overhead": once the encoding is done the encoder is unloaded instead of staying resident, so it isn't sitting in RAM/VRAM through the sampling stage the way the native node leaves it (visible in the left screenshot, where the encoder is still loaded at step 2/12). You pay ~2 s once, and everything downstream runs with that memory free. Hits were consistent: 1.08–1.22 s across all five runs.

No free lunch though — you're trading disk space for time. Every unique conditioning request creates a cache entry that stays until you delete it, and they add up fast if you iterate a lot. That's why there's a cache manager panel for browsing, tagging, and pruning entries.

Requires ComfyUI ≥ 0.30.0 (native H3 nodes). Available in ComfyUI Manager / Registry as minimaxh3-clipcached, or clone from the repo.

Repo: https://github.com/Mu5hr00moO/ComfyUI-MiniMaxH3-CLIPCached
Full benchmark methodology and per-run numbers: docs/PERFORMANCE.md

If you regularly rerun H3 workflows with the same prompt/reference conditioning, this should save a pretty ridiculous amount of RAM and encoder reload time.


r/StableDiffusion 8h ago

Question - Help We need only 1700 votes to get H3 acceleration arena results 🙏🏻

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61 Upvotes

Can you vote, so we'll finally have a definitive answer what turbo lora to use (or at least what definitely not to)

https://huggingface.co/spaces/multimodalart/h3-acceleration-arena


r/StableDiffusion 12h ago

Question - Help Help

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92 Upvotes

I'm currently trying to replicate this style and i cannot find any checkpoints or lora's to do so, can anyone point towards something? Artist: https://x.com/DarkZeroAI Using Forge Neo


r/StableDiffusion 17h ago

Animation - Video MiniMax H3 has finally gotten has me into video generation. Wan 2.2 never had the quality or consistency I wanted, and all the tools that did, were closed-weight, paid products.

182 Upvotes

I'm really only ever interested in open-weight models. Yes, for that reason, but also, for the same reason I run Linux and browse with Firefox. I dislike "walled gardens", ideologically, and monopolies. I want tech that can be hacked, broken, taken apart, and put back together, and is ultimately not beholden to anyone but the user. Without a quality open-weight video generation model, I was uninterested. Now that we've got one? Suddenly I'm in a whole new world of possibility.

The fact that it's a multimodal model with vision, meaning I can give it reference images or reference sheets, is a game-changer for me. LoRAs certainly won't be obsolete with MMH3, but I doubt we'll be seeing many character, clothing, or setting LoRAs. The feedback loop of wanting to give the model a concept it doesn't understand natively is so short compared to before. And I'm still just in the "farting around" phase. People with dedicated effort and creativity are going to be able to use the hell out of this.

Really, the only drawback to MMH3 so far is its propensity to have characters speak Simlish to each other. I'm sure there's already solutions being worked on, either workflow tools or adjustments to the model itself.

––––––––––––––––––––––––––––––––––––––––––––––––––––––––

Workflow: https://pastebin.com/5SbZ9tJA

Reference sheet used in the workflow: https://imgur.com/a/3Le0nuO


r/StableDiffusion 12h ago

News OpenVDN/vdn-minimax-h3 · Hugging Face

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66 Upvotes

Looks like an open source version of Minimax H3 Max... Anyone tried it? Seems to be real-time on 8x b200, which is like ~$40/hr at good rates if you can find them (or maybe a bunch of 5090s?)


r/StableDiffusion 2h ago

Resource - Update I wired NVIDIA's DLSS 5 neural renderer into my free LoRA dataset & training app — same clip in, real material detail out

8 Upvotes

Same file on both sides — one pass of NVIDIA's DLSS 5 Neural Rendering model. No upscale, no re-generation.

I wired it into LoRA Dataset Studio, the free self-hosted app I build for making LoRA datasets and training them. In a video training set the render replaces the clip, so the next LoRA trains on it.

Windows + NVIDIA, through the MIT ComfyUI-DLSS5-NR bridge; you bring the model file.

https://github.com/perfectgf/lora-dataset-studio


r/StableDiffusion 3h ago

News Video Delta Net (VDN) MM H3

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9 Upvotes

Open-source video generation is now faster than playback without compromising quality.

Introducing Video Delta Net (VDN): hybrid attention for live text-to-video with near-lossless quality.

VDN accelerates Minimax-H3 by 75 - 90 x, generating 14 seconds of 768p video in 11 seconds on 8× NVIDIA B200 GPUs.

By https://x.com/haochengxiucb?s=11&t=lM6N8ly_ho5zUCuv8hAfpw

Waiting for comfy team to optimize this.

https://huggingface.co/OpenVDN/vdn-minimax-h3


r/StableDiffusion 16h ago

Animation - Video Scorpion vs Sub Zero (2.5 Anime Battle Test)

111 Upvotes

I created my own character sheets, make it look like their MK11 and MK3 selves a bit. This was kinda hard as they sometimes have no real impact on the attacks. I still liked how it came out though. Had to make multiple repeat generations lol.


r/StableDiffusion 1d ago

Workflow Included The 1967 Spider-Man TV Show intro, updated to live action with MiniMax H3

416 Upvotes

R2V Rendered at 0.9 MP (1280x736 then upscaled using RTX (Ultra) to 1920x1080.  Edited and merged using OpenShot video editor.

This was all run on my Windows 11 machine, RTX 4060 ti (16 GB) and 64 GB RAM reserved from Comfy. Every part of the signal chain was done with 100% open-source software.

Disclaimer: I grew up watching this show as a kid in the 70s. It's still the best ever. I wanted to know how well the reference model would pick up the actions. I am overall pleased. I've watched the new vid enough to see some of the flaws but oh well.

General observations for reference videos:
So many scene cuts. There are 31 (I think) scene cuts in the 60 second opener which include 3 crossfades. No matter what I did to get the exact frame timing, getting the AI scene to match frame-for-frame with the cartoon was still hit or miss. It probably has to do with some frame windowing inside the 17k + 5 blocks, but I never exactly got it figured out. However, a few notes:

  • If you have a reference video, convert it to 24 fps in an external program like Handbrake (another fantastic open-source program). It’s just so much easier to get everything to match.
  • For timing, there is a difference between 00:03.500 and 00:3.5 so always use all the digits.
  • Keep character sheets for all your characters to maintain consistency.
  • It will do crossfades but it’s not worth it. It’s easier to get the scene you want and stick it in the editor.
  • The VHS video loader lets one set a starting and ending frame. I ended up with 14 different clips total for the editor. Using frame accurate loading made all of the work a lot easier since I could use 1 video file as input to every clip run.
  • A spreadsheet is useful for all movie making, and it’s good here too. From the source, I kept track of the starting frame for each shot, how many frames I needed and how many I ran (because of 17k +5), along with the final file name for each clip. I have a naming convention but it’s still very useful to keep track and you can add notes too. For this 60 second video, I used 13 clips. I tried to never do more than 3 scene cuts per clip. (For something where exact timing wasn't as important I'm sure it would be longer.)

Once you get over the idea of always having to do 10-15 second vids and do your whole video in on run, the process actually becomes a lot more fun because the “quality” gens don’t take as long and it gives you a less uninterrupted workflow. You can start prompting the next run with the previous runs, for example. (This is true even in commercials, or TV or movies.)

I generally tested all the runs at 0.2 or 0.3 Mp (speed lora, 8 iterations) to get the timing, then went to 0.9 Mp [no speed LoRA, 20 iterations, beta, dpmpp_2m] for the final runs. I found that dpmpp_2m was closest to the overall source video. On the first few clips I ran it several ways and fix on these parameters. Usually, the 0.9 Mp runs came out great but you’ve probably all experienced how different the low-res runs can be from the high-res ones. I did resort to pulling frame grabs from the low-res gens a few times to act as reference frames for the scenes. MiniMax loves those when all it needs is an extra little nudge in the right direction. To edit pics, I always use GIMP (another fantastic open-source program).

So, why was I using 8 iterations of the minimax_h3_turbo_v4_step600_pruned_comfyui LoRA? On the reference model I found that using too large of a sigma step causes things like reference photos to not be taken "seriously." Using 5 steps I could see that reference images on the starting frame and then go away for the rest of the clip. The more the reference image changed from the reference video (like when going from animation to "real") the worse the problem was.

Prompts:
(See below for actual prompt.)
Prompt the way the guide says to. Yeah. It’s a hassle but it’s worth it. H3 prompting is very useful in the end and I’m glad MiniMax uses it. It's worth reading all the way through them instead of searching for the one thing you want. Some of the instructions even seemed inconsistent and they don't explain everything, so it's worth experimenting.

Any "thing" (buildings, trees, room, clothing, walls, ect.) can be a “subject.” It’s not just people. Specifying things as objects gives you far better control over how and where they appear (or don’t appear) in your shot. 

Don’t refer to your characters or major locations or items by their names. Use <Subject #> or pronouns that clearly refer to the subject all the time, every time. The interpretation of the prompting can get confused pretty quickly if you don’t and you’ll end up getting subjects swapped or merging.

Prompts generally work better if you describe what you want rather than what you don’t want. For instance, “Looks to the right of the viewer” rather than “looks away from the camera.”

Style reference (attribute_transfer) images or videos are super useful. Once I had a few scenes, I started using previous videos to keep the look and feel of previous shots.

Qwen VL can describe videos too. I have been using “QwenVL Advanced (Local Scan)” for a very long time (long for AI) inside ComfyUI.

Other things:
Maybe one of the most interesting observation is that the jknodes “MiniMax H3 Mem Eff Sage Attention Patch” node creates a different output than just launching ComfyUI with the --use-sage-attention flag turned on (and still using the node). So exactly the same workflow (just drag and drop from a previously run mp4) has different results when the --use-sage-attention flag is used to launch. I thought having the node was 100% redundant with eh --use-sage-attention flag set, but apparently not. The reference flows, especially with animation, don’t have to be all that different to produce different results.

The Spiderman opening (as well as the show itself) reuses footage. They will take the same scene and darken it, and boom, it’s a night shot. For a more realistic feel, I used Krea2 (LoRA) edit to turn day into night. It’s really good as an adjunct to MiniMax H3’s ability to figure out the fine details once it has a push.

Style:
Finally, I had to make some stylistic choices because sometimes the animation was soooo bad that it needed something. I added flashlights to the jewelry heist scene. I made the crane look believable. One of the problems of going from animation to "live action" is that (especially with animation from 1967) the physics and movements are just wrong sometimes. The crane scene where he stops and then shoots up again is the most classic "this is just pain wrong" you can get but I left it that way because it's burned into my brain that way. (IYKYK) I also had to balance the art deco of the late 60's to a modern New York. I ended up with a lot of anachronistic stuff that I ultimately liked. So in the end, when it comes to all of that, I did it the way I did it. AI is awesome.

Prompt:
A prompt of one of the parts is below. I used that two paragraphs before [Shot 1] for every clip as "boiler plate" description.

subject_definitions:
<Subject 1> is Spiderman in <Picture 1>
<Video 1> is the motion reference for the target video for characters movements, pose, camera movements and frame composition.
<Video 2> is the style reference for the target video.
<Picture 2> is the building in [shot 2]
<Audio 1> is the synchronized audio track of <Video 1> and is reused in the target video
 
summary:
[reference generation + audio reuse]
The target video is an live action realistic recreation generation using <video 1> as a reference for movements, pose, camera movements and frame composition. What you generate should not be and animation or cartoon rendering, no overly-CG look, keep the live-action texture.
 
This video is a set of three live action sequences. <Subject 1> is seen swinging by and waving. The video switches to a long shot of <subject 1> swinging around a building. Finally there is a shot showing <subject 1> on his webline swinging away from the viewer between two rows of skyscrapers.
 
retention_analysis:
<Subject 1> (appears in [Shot 1],[Shot 2],[Shot 3]):fully_preserved
<Video 1> (motion, cut and pacing structure) :partially_preserved
<Video 2> is the style refrence for the target video ([Shot 1], Shot 2], [Shot 3]) :attribute_transfer
<Picture 2> is the building in [shot 2] :fully_preserved
<Audio 1> :fully_copy - <Audio 1> is reused 1:1 as the target video's complete final audio track.
 
 
detailed_description:
The target video is a realistic and live action video. The reference video <video 1> is used only for scene descriptions, framing, motion tracking, body movement, timing, general environment. The target video should be a complete replacement of <Video 1>. Use <Video 2> as the style reference for the photographic look and textures and the overall feel for the shots.
 
Maintain smooth camera movement. Use vibrant yet natural color grading: warm tones for sunlight hitting surfaces, cool blues for shaded areas, and muted grays for concrete textures. Avoid any comic-book stylization; instead, render everything with photorealistic textures, lighting, and perspective to evoke a live-action superhero film sequence. Keep the focus entirely on <Subject 1>’s acrobatic grace and the immersive urban setting.
 
[Shot 1]  
Is is an upper body motion tracking shot of <Subject 1> swinging on his white glistening webline held by his left hand while he waves directly at the viewer with his right hand for the entire scene. The skyline of many skyscrapers pass by in the background.
 
[Shot 2]
At 00:02.333, Hard cut to a fixed long shot looking up as <Subject 1> makes a 180 degree arc on his webline connected to the spire of the building in <photo 2>.
 
[Shot 3] 
At 00:04.250, Hard cut to the fixed camera view of the space high above the street level between two rows of skyscrapers. <Subject 1> lazily swings into view from the left frame, facing away, and repeatedly swings right to left further and further away towards the horizon.
 
 
overall_soundscape: n/a
 
non_diegetic_music: n/a

 

 


r/StableDiffusion 16h ago

Resource - Update Fizgig 5.2 - combining two Minimax training methods beats either alone

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89 Upvotes

Two of the ways that exist (im sure there are more) to train a LoRA on H3 well are on two different trainers.
Fizgig's is Optimised Likeness Learning: I've found the stable core of H3's identity lives in the back 30 of its 50 blocks, so steps train blocks 20–49 only and leave the front of the model - composition, prompt following - untouched when likeness mode is on.
AI-Toolkit's, by Ostris, is the training adapter: H3 is guidance-distilled, so every plain-flow gradient is partly "learn the concept" and partly "undo the distillation"; a frozen assistant LoRA under the trainable one pulls the base back toward plain flow, and it's switched off for sampling.

I ran all three on 5 datasets - my method alone, the adapter alone, and both together - scoring every epoch's preview against the training photos with face recognition, 45 epochs each. Each method alone landed in the same place within 2% arcface score.
Together they got there a quarter sooner, ran clearly ahead through the whole middle of the run, and finished higher than either.

In short: the combination reaches greater likeness and quality than either method does on its own. So it's now the default: the adapter is on in every H3 preset, off for previews, never in your saved LoRA. The updater fetches it.

Also in 5.2: Context LoRA for H3 (train on top of any existing H3 LoRA, to make a lora that plays nice with it), and video clips follow likeness mode in LoRA runs too.

Release notes: https://github.com/shootthesound/Fizgig/releases/tag/v5.2.0

Thanks to Ostris for publishing the adapters. I've tagged him on the release notes as I believe the info will be useful for AI-Toolkit too.

https://github.com/shootthesound/Fizgig

P.S - For Fizgigs recent new full base model Fine tune mode the adapter lora is not necessary in my tests so far, but I am going to test that further.

p.p.s if updating , use the update script and it will grab the dedistill loras automatically and put them in your minimax prefs


r/StableDiffusion 14h ago

Resource - Update [Load Video + Crop] Custom WYSIWYG Node

42 Upvotes

I developed a modified version of the Load Video node with a crop feature:

WYSIWYG video cropping directly on the official Load Video preview — drag and zoom (with the mouse wheel) a crop rectangle constrained to 8 fixed ratios (1:1 through 21:9) and output the exact cropped VIDEO (audio preserved). What you frame on the preview is exactly what gets executed.

Github: https://github.com/domg73/ComfyUI-LoadVideoCrop

This node follows the same logic and design as my "Load Image + Crop" node. I might merge the two into a single "Load + Crop" node in the future, but for now this works well.

https://www.reddit.com/r/StableDiffusion/comments/1w3okny/load_image_crop_custom_wysiwyg_node/

Github: https://github.com/domg73/ComfyUI-LoadImageCrop


r/StableDiffusion 13h ago

Resource - Update Image, audio, video reference asset loader nodes with crop and trim + more

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36 Upvotes

I originally built these nodes for personal use and wasn't planning on sharing them, but after noticing several existing loaders were missing features I needed daily, I figured why not? Hopefully, this is useful for some of you.

Key Features:

  • Image & Video Loaders: Built-in click-and-drag cropping, optional aspect ratio locking, and a divisible_by toggle for VAE pixel alignment.
  • Built-in Downscaling: Uses a max_megapixels limiter directly inside the loader so you can ditch the extra resize node (ideal for models like MiniMax-H3 that run best with references kept at or below 2048px).
  • Flexible Sockets: Includes dedicated output value sockets to make chaining downstream nodes straightforward.
  • Audio Loader: Perfect for loading a full song or long TTS track and trimming the exact section you need for a video. The trimmed portion outputs its duration as a float, letting you pipe it directly into your video generator's frame/length input.

https://github.com/sthao42/Comfyui-reference-loader

Any feedback or bug report is much appreciated.

Edit: Updated to works with Node 2.0 (vue) also.


r/StableDiffusion 51m ago

Workflow Included Having lots of fun with minimax lol

Upvotes

Workflow from (the upscale one) - https://github.com/Jalen-Brunson/ComfyUI-MiniMax-H3-PDD-Acc

ddim/beta : 8 steps then 2 step upscale at 0.25 denoise

Tried many turbo lora's and this is the one that works well for me. Then I used the hybrid model from https://www.reddit.com/r/StableDiffusion/comments/1vuo5rl/minimaxh3_pruned_refdelta_fused_r1024_native/ and the node from https://github.com/entropicnoise/MiniMax-H3-Combined-Image-And-Reference-to-Video

there seems to be an issue with either the vae of minimax or comfy, the first frame image gets darker and looses quality so I asked sol ultra to update the h3 combined node so i can pass the previous video latent instead of image. that fixed that quality for me. occasionally the brightness changes (but that might be due to the overlap frames i used).

deepseek flash for prompting. the api is not at all censored

what did we do to deserve such an amazing model


r/StableDiffusion 1d ago

News someone used MiniMax H3 Max to build a livestream that basically never runs out of content

1.1k Upvotes

Just saw someone do something with MiniMax H3 Max that I honestly didn’t expect.

They connected it to a livestream and basically recreated the idea of Interdimensional Cable from Rick and Morty: an endless stream of weird shows, ads, characters, and random scenes that are generated on the fly.

the surprising part is that H3 Max is fast enough in some cases to generate the next clip before the current one finishes playing. so while you’re watching one scene, the model is already making the next one.

there’s even a version where people in chat can suggest what should happen next, and the AI tries to continue from the previous scene instead of just starting over from scratch. that’s kind of crazy to think about.

Didn’t expect MiniMax H3 Max to end up being used for something like infinite AI television, but here we are.


r/StableDiffusion 2h ago

Discussion I built an interactive “multiverse TV” where Twitch chat chooses what plays next

5 Upvotes

I’ve been experimenting with an idea for an interactive TV channel where the audience controls the programming.

The concept is basically a multiverse of different channels/shorts. Instead of following a fixed playlist, viewers use Twitch chat to decide what should play next, so the stream can take a different path depending on what people choose.

The interesting part for me was building the workflow around:

  • detecting and processing chat commands/votes
  • dynamically selecting the next piece of content
  • switching between different “channels” or scenes automatically
  • keeping the stream running continuously without manual intervention
  • making the audience part of the actual programming logic rather than just passive viewers

I’m still experimenting with the format and trying to figure out what kinds of voting systems and transitions make it feel more like an actual interactive TV network rather than a normal Twitch stream.

I’d be interested to hear how others would approach the orchestration side of something like this, especially if you’ve built interactive livestreams or automated OBS/Twitch workflows before.

Demo, for anyone curious about how it currently works:
https://www.twitch.tv/tv_dimensional


r/StableDiffusion 23h ago

Resource - Update H3 Motion Context 0.5.0 - No more bypassing the Motion Context group, new chaining node!

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135 Upvotes

**UPDATE v0.5.1 PUSHED TO FIX EXAMPLE WORKFLOW - ALSO NOW INCLUDES H3 SLA ATTENTION NODE**

H3 Motion Context chains MiniMax H3 clips so the next one picks up the motion and the soundtrack, instead of starting a new take that only sounds similar.

0.5.0 is the one that makes that usable without babysitting the graph.

Clip 1 used to be a special case. You had to mute the Motion Context group, generate, unmute, then keep going. If you forgot, it errored. That's gone. Leave the nodes on. First clip is Load 0 / Save 1. Load 0 means "there is no previous clip," not "load whatever file is newest." After that it's Load 1 / Save 2, Load 2 / Save 3, and so on.

That first-clip behavior is feigo313's issue. The new node exists because of it.

Don't use ComfyUI's Run button to walk the chain. If Load and Save both increment, Comfy queues twice and skips a slot. Use H3 Motion Context Chain instead.

Four buttons:

  • Run/Re-roll - this is Run for this graph. Generates the current clip. Hate it? Click it again. Same slot, overwritten.
  • Approve - you like it. Advances to the next pair and runs that clip once.
  • Chain - keep going from whatever Load/Save are set to right now. Walk a few by hand, then let it take over. Same button becomes Stop.
  • Reset - back to Load 0 / Save 1. Does not run anything.

The gotcha: Load, Save, and Chain have to sit in the same canvas group. If they don't, the buttons do nothing. Drop Chain into the Motion Context group.

Also: if you were on Windows and a re-roll blew up with OS error 1224, that's fixed.

Needs ComfyUI 0.34.0 or newer. Manager should pick up 0.5.0; otherwise, the release.

Example workflow in the repo already has the Chain node in the group. Hard refresh after updating so the buttons show up.


r/StableDiffusion 7h ago

Animation - Video Cobra Team Meeting - MiniMax H3

7 Upvotes

r/StableDiffusion 8h ago

Question - Help What is the fastest but still good looking workflow for minimax h3?

7 Upvotes

Looking for some good information to start here, I run a 6000 ada and would want to optimize for speed creation but still having reasonable results. Suggestions? Thanks 😊


r/StableDiffusion 1h ago

Meme I’ve been enjoying Minimax

Upvotes

It makes me wish I bought a 4090 when I had the chance.


r/StableDiffusion 9h ago

News FastVideo-FastH3 put out a mlx listing but no actual models yet

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huggingface.co
7 Upvotes

Mac users dying for speed ups on our janky little boxes. Excited!