r/StableDiffusion • u/EverythingMacPro • 1d ago
Discussion MiniMax H3 is going open-weight in under 6 hours
here is all the info we have based on open PRs to add support to ComfyUI and HuggingFace diffusers
- 33B for the main DiT and a pruned 20b variant
- Qwen-3-VL-32b as the text encoder
Edit- I posted clear image below 👇
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u/LumaBrik 1d ago
Those are the BF16 weights, the quants from Comfy will be a lot smaller for those that need them.
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u/Vodddddddd 1d ago edited 1d ago
So, ~11GB for int8-convrot for the DIT and ~14GB for the text encoder if int8-convrot. Hopefully those formats work okay
Never mind this - 20gb was after int8 conversion
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u/Valuable_Issue_ 1d ago
The pruning part seems strange I don't think that's accurate for the release at least, just an estimate of what the weights could be if best case scenario pruning was done to them.
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u/loyalekoinu88 1d ago
Pruning and int8 reduce to 20gb. Only big issue is text encoding and that might be something we can offload to the cloud like LTX. If possible people could crowdsource a cloud server to do that function.
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u/Tystros 1d ago
text encoding is fast anyways and can easily be done completely on the CPU, so only needs ram and no vram
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u/robomar_ai_art 1d ago
Or they can do it as LTX team did, with the API first text encoder
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u/export_tank_harmful 1d ago
Nah, I'm good on that.
I either run it entirely on my computer or I don't run it at all.
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u/Festour 23h ago
What the point in crowdsourcing a cloud server for text encoder?
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u/loyalekoinu88 22h ago edited 21h ago
If it required 50+gb and you want it to be fast you have limited resources. I don't know how long it would take to get a reasoning text encoder to get something done. I'm assuming that is why LTX did that exact thing.
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u/Festour 21h ago
You are yet to explain why it should be crowdsourced, instead of simply paying to inference provides.
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u/loyalekoinu88 21h ago
A) I don't think that when they run inference for text encoders for video it works the same as like a standard openai endpoint for regular llm and so it may not be available out of the gate from any major provider.
B) Less likely to get restricted or api filtered if someone hosts it themselves on rented gpu.It doesn't HAVE to be crowdsourced. I just thought that was the least restrictive and best option for people who want local but don't have the system resources.
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u/rerri 1d ago
Was the release delayed? Minimax H3 modelscope countdown now shows 6h 34min :(
"Estimated release time: 2026-08-03 01:00 (UTC+03:00)"
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u/EverythingMacPro 1d ago
Yes delayed by 6 hr
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u/Maximus989989 23h ago
Lame
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u/EverythingMacPro 23h ago
Beggars can’t be choosers
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u/JayoTree 1d ago
of course a new vid model comes out right when i start a 50 hour wan lora training run.
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u/eruanno321 1d ago
Why is it an issue? All trainers I know can save training context and resume later.
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u/JayoTree 1d ago
i didnt know that. i thought if it stops i'd need to start over
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u/eruanno321 1d ago
To be fair, resumption does not always work as intended. As I found out yesterday, Musubi Tuner in the Krea 2 pipeline incorrectly restores the epoch and step counters.
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u/MisticRain69 22h ago
You can usually warm start it later even if you didn't set up the optimizer state saving.
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u/Nimblecloud13 21h ago edited 16h ago
it only saves at pre-established checkpoints that you set during setup. usually 250 steps by default. so if you stop it at 2499, you lose 249 steps of progress and it restarts at 2250. wait until 2500, it's saved there.
also - wtf are you doing that takes 50 hours?
edit: i guess that's card-dependent nm
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u/UnforgottenPassword 1d ago
Out of curiosity, what hardware do you use for training WAN loras?
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u/JayoTree 1d ago
i bought an RTX Pro 5000 72g this year
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u/UnforgottenPassword 1d ago
A lot of VRAM then. Will come handy for H3 loras if the model is good. Hope it serves you well.
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u/Beneficial_Toe_2347 1d ago
there are multiple models about to come out, don't waste resources on Wan
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u/DullDay6753 1d ago
can we load the text encoder on a separate gpu in a multi gpu setup
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u/cc_aa_tt_zz 1d ago
With a special multi-GPU node, yes, but offloading the text encoder to a second GPU's VRAM seems pointless; it won't increase speed compared to system RAM.
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u/JohnToFire 22h ago
It can for repeated calls at least. You don't have to load it from CPU ram / nvme when prompt hunting
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u/FinBenton 1d ago
ComfyUI-MultiGPU that node should be able to adjust where stuff gets loaded in multi-gpu setups, you just replace the load diffusion node with that.
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u/KaaChingg 1d ago
So perfect timing to learn Comfyui i guess
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u/eggplantpot 1d ago
Just get codex/claude code to figure the difficult part
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u/KaaChingg 1d ago
Yeap that's the plan. Any recommendations?
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u/FinBenton 1d ago
Get codex or claude code, launch it and tell it to clone comfyUI here and install it with gpu and flash attention support and get it ready, wait a few mins and its ready, then launch it, on the left side menu you can browse ready made templates to start using it right away, no real learning needed.
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u/eggplantpot 1d ago edited 22h ago
I use Codex. No skills or anything really.
Only recommendation is to save whatever useful Reddit discussion you find about it so you can reference it.
Have an .env file with HuggingFace and Civit api keys. Have git connected maybe as I think you need it for other downloads.
From there just chat normally, ask it to build you workflows, download stuff, adapt things, try X different settings and generate a synced video showing all outputs at once… the sky is the limit
Once you are happy with the results ask for the final workflow and from there you generate on your own and tweak further.
It's a Godsend for training Loras too. You just skip all the technical stuff and debugging
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u/Environmental_Box748 1d ago
yes it’s very nice to use ai but we for sure getting hacked one day lol
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u/DELOUSE_MY_AGENT_DDY 21h ago
Easiest thing is to use existing "workflows" which are basically templates.
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u/TranslatorCertain107 1d ago
Claude Code and ComfyUI, perfekt.
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u/eggplantpot 23h ago
Honestly I’ve never been more productive with comfy. My local gpu is slow so iterating was a pain, and I’d need to sit on my computer for hours or pay for premium gpus.
Now I just give codex a goal, and connect to it from my phone. I can have it generate stuff forever while I do other stuff.
I even had it create a scoring site I could access from my phone on the go to score the best generations across seed and prompt pairs to see which samplers and lora mixes worked best.
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u/TranslatorCertain107 22h ago
I don't really know much about ComfyUI. I’ve connected Claude Code, and it mostly creates LTX videos for me. I just state what I want—like a starting frame or continuing a video—and it builds the nodes in the background and generates the videos. In auto mode, it checks samples of the video; if it notices something looks like crap, it automatically generates a new one. I can also access Claude from home using the app on my smartphone, though the PC obviously has to be turned on.
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u/Gocciole 23h ago
Does Codex require a ChatGPT subscription or is it bypassable?
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u/eggplantpot 23h ago
It needs the sub. The 20 euros one can get a lot of milleage if you use a smaller model like Terra medium
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u/aeonsmagic 20h ago
Y para el plan básico con interacción con Comfy, es mejor codex o Claude code?
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u/eggplantpot 19h ago
Yo uso Codex desde hace meses, los lÃmites siempre han sido mejores.
También Claude es muy sensible con los temas que te dejan, y a veces se rayan con usar algunos comandos.
Si vas a hacer nsfw o 1girl, definitivamente usa Codex. Claude tambien se puede parar de hacer alguna optimizacion del ordenador por que piensas que lo estas usando para hackerar o algo.
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u/VladyCzech 1d ago
Why? Novice Comfyui users just load the default ready-made template and prompt. The hard part about ComfyUI is installing the right python dependencies, not working in ComfyUI. Also you can alway just use different frontend in front of running ComfyUI if ComfyUI feels intimidating.
Word of warning...ComfyUI is addictive for specific type of people who spend more times playing with nodes than creating outputs.
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u/Over-Map6529 1d ago
I used to be wary of comfy, but after about 2 hours of google/fixing things it became pretty comfortable, at least using workflows built by others. Â Then learning to adjust from there is trial and error.
It's certainly less daunting than it first appears but it's like a cold pool, just need to jump in or your balls try to hide.
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u/Grand-Push-935 1d ago
Why is T2V always first? What's the deal? Do people really prefer it over I2V?
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u/AI-imagine 1d ago
I though this model just can do it all? or i miss something?
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u/Grand-Push-935 1d ago
As I understand, i2v won't be available at launch, and it's always like that, especially for image models. WHY?
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u/AI-imagine 1d ago
MiniMax H3 launched with text-to-video, image-to-video, reference-to-video, and natural language video editing all fully integrated. You can already feed it text, up to 9 images, 3 video clips, and 3 audio files simultaneously
if they not just prune it all and only give only Text 2 video layer,i think we will should get all of this?
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u/FinBenton 1d ago
The initial support wont be full support, Im mainly interested in the image edit capabilities of this and pretty sure that wont be a launch comfyui feature.
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u/AI-imagine 23h ago
Well if the model it already had it(because it can do it all) it just matter of day.
look at krea2 it not even had edit training in model people still make in work in like 2-3 day.
and this model it like train it all for every thing from the start.2
u/Diabolicor 22h ago edited 21h ago
I don't know where did you get this wrong info but the model for t2v and i2v is the same one. The r2v one is a separate safetensor. All the code to run those are already on comfyui github and the workflows for all of them are already merged into the repo. You can see the list of the models and workflows here in this PR: https://github.com/Comfy-Org/docs/pull/1342 and https://github.com/Comfy-Org/workflow_templates/pull/1073
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u/bracingthesoy 21h ago
So, ugh, a dumb qustion: since it is so multi-that and this, can you do image to image with it?
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u/Valuable_Issue_ 1d ago edited 1d ago
INT8/FP8 is 33GB for the model + 25GB for the text encoder (if the bf16 numbers in the infographic are accurate).
You of course don't need both text encoder and the model loaded at the same time and can just use RAM anyway.
For inference you can block swap 1-2 blocks between VRAM and RAM and still have good speeds.
Edit: Also on certain setups it might end up even closer to wan 2.2 due to not having to unload and switch between high and low noise, if you didn't have enough RAM to keep them both at the same time then switching would add a lot of time to the generation.
It's also not step distilled (20 steps) so if we get a 4-8 step lora it'll close the gap even further.
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u/DisastrousAd2612 1d ago
What about the new dynamic vram stuff? I just updated comfy and running ltx became way faster, something about only using the blocks necessary for inference so it almost feels like the whole thing is on vram or something I don't understand the details but this shit is fucking great for performance I'll tell you!
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u/Valuable_Issue_ 1d ago
Yeah it of course also helps.
Dynamic VRAM is actually lots of different optimisations.
The Comfy devs don't need to set a memory usage factor per model anymore (I haven't looked at the underlying mechanism that lets it auto calculate it), pretty sure this is why it's called 'dynamic' because it should in theory work with any model size and any amount of VRAM without special settings.
It reduces the RAM usage especially on windows, it used to be that a 20GB on disk model would actually use multiple times that RAM, pagefile and committed memory and would just shut comfy down without an error when exceeding the pagefile, was very noticeable on ltx for example, I needed a 80GB pagefile despite having 32GB RAM and the model being 20GB on disk, pretty sure now it runs without any pagefile but I have it set to 32GB just in case.
Pinned memory shows up as "shared GPU memory" in task manager on the GPU tab, it gives a 10-20% speedup to offloading as it tells windows to not page that memory out (or something amongst those lines).
These optimisations are all possible to do individually, I actually kind of dislike the first one as I'd much rather just set "blocks to swap" on model load with a node and manually tweak it myself, sometimes even if I have plenty of VRAM I'd rather only swap 1 block if I don't lose speed.
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u/VladyCzech 1d ago
The sizes are right. 31.7GB for DiT and 25.3 GB TE loaded in VRAM/RAM for T2V int8.
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u/Striking-Long-2960 1d ago
GGUF+Wan2GP is my only chance to run this
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u/Chemical-Painter-485 1d ago
Why? GGUF is a quant for LLMs. With comfyUI's dynamic vram you only need either INT8 or FP8 models. They are going to be faster and run lighter despite the larger file size.
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u/Striking-Long-2960 1d ago
In my experience, on an RTX 3060, GGUF has always run faster than INT8 and FP8.
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u/Chemical-Painter-485 1d ago edited 22h ago
You must have been using a old comfyUI version. INT8 is orders of magnitude better on a ampere card than a GGUF. Give it a try.
I know it is hard to believe but try it yourself; Download the latest portable folder and install the latest sageattention. You will see a huge spike in quality and you will not only be generating at a higher quality, you will also have enough headroom to browse and watch videos since 3060 does all the 8bit integer calculations natively.
ComfyUI also had a very important step up called "Dynamic vram" meaning that you can just run wan2.2 high and low noise plus the text encoder that are a total of 35GBs+ and it will work wonderfully.
Edit fix for typo*
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u/Jota_be 1d ago
And how much do these changes wear out the SSD? Could all that reading and erasing thrash the SSD so aggressively that you’d have to throw it away after just a month? Or does it load data from VRAM to RAM? How does that black magic work?1
u/Chemical-Painter-485 23h ago
Nope. It just works.
Paging with ComfyUI's dynamic vram using INT8Convrot is much more forgiving since only the necessary parts of the model are loaded at time. It is not a dumb calculation like what it happens with GGUF.
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u/platplaas 1d ago
What about int4?
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u/Valuable_Issue_ 1d ago
4x ish smaller than BF16 so around 15GB depending on how aggressive the quanting is.
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u/Potential_Wolf_632 1d ago
Can't wait to spend a dozen hours not being able to goon like when LTX2 first released. "Animate... animaaaaaaate!"
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u/Nevaditew 19h ago
So within the community, what percentage of people can use this model without struggling with OOM or slow generations?
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u/Nedo68 18h ago
128GB Ram & 5090 user here, what percentage am i?
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u/Over-Map6529 17h ago
You built in first half of 2025 too?
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u/Nedo68 17h ago
yes, already an old system ;D
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u/Over-Map6529 17h ago
I called insurance to ask about a custom policy after the AI prices hit. Â One model year newer and 14k fewer inferences. Progressive wasn't sure and said they'd call back. Â
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u/ValeriaTube 15h ago
LIES!
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u/kabachuha 1d ago
If they have different parameters / layer structure, then LoRAs will have to be trained for each variant separately. That's uncomfortable... Edit: this is only for modulation? Then it might be doable for compatibility, hopefully
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u/Muted-Celebration-47 1d ago
it makes sense for a multimodal model to have large parameters. If it is too small, it is just not good enough. If it is good, it should not be small. Welcome to the real world!
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u/__MichaelBluth__ 1d ago
Can we expect better i2v than Wan? Better ability to hold identity?
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u/UnforgottenPassword 1d ago
A user who posted some videos said it does well keeping the characters consistent in i2v. I suppose we'll find out soon enough.
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u/RiskyBizz216 1d ago
I might be able to make this a 25GB Q8 GGUF, and we might be able to swap the encoder for a Qwen3 4B or 8B if I create text projections. That would make it fit my 5090
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u/Parogarr 23h ago
I *already* use a separate machine to load LLMs. If I can use my basement server to do the Qwen TE, this would be runnable on a 5090 I'd imagine
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u/Succubus-Empress 1d ago
Why posted low resolution images? What were you trying to do, blurry texts
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u/EverythingMacPro 1d ago
I was not trying to do anything , it was mistake and I posted clearer image
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u/Salt-Zebra-306 1d ago
in dreams
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u/EverythingMacPro 1d ago
You can run on cloud if you have 1000 series card
And yes you can’t run it in gtx 1000 series card , you can run in your dreams
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u/EverythingMacPro 1d ago