I've been using MiniMax H3 on my M5 Pro 64GB MacBook Pro through ComfyUI. It works extremely well.
I had to modify the default ComfyUI workflows to use a GGUF quant (city96's ComfyUI-GGUF custom node, UnetLoaderGGUF in place of the stock loader) [0].
I use the model labeled Q5_K_M. There is Q8_0 available as well, which is 34GB and fits fine in 64GB unified memory if you keep resolution modest.
The main issue is speed, a ~9-second 480x864 clip at 20 steps takes me a bit over an hour. So this will be cool to try for the speed up alone.
There's a lot of great information and workflows available to follow on the r/StableDiffusion subreddit.
[0] https://huggingface.co/Abiray/MiniMax-H3-GGUF/tree/main/unet
This implementation is much faster on my M5 Max, like a few minutes for the same video, but on an M5 Max with 128GB, didn't test on M5 Pro. About memory, could be executed on 64GB with a few changes.
Memory bandwidtih between pro and max is double. 300gb/s vs. 600gb/s btw.
Does not matter much in this case. GPU bound.
Seems to be true, but also seems hard t obenchmark with max having more GPU cores too.
My understanding is that that tends to be more critical with LLMs than image/video gen models, which are relatively more compute vs. memory transfer intensive than LLMs
Performance might still end up being bounded by data transfer speed if SSD streaming is heavily used to make up for limited RAM. By comparison, it doesn't take many parallel-batched sessions to make LLM decode compute-bound on typical hardware (hence seeing very limited gains from even wider batching), but this just doesn't apply when streaming weights from disk, the setting is completely different.
GGUF is unsupported by ComfyUI’s memory management system that enables running models much larger than fit in VRAM with tolerable efficiency via weight streaming, but for unified memory systems that system is less relevant (unless using models too big to run in unified memory AND having fast enough mass storage to benefit from direct-from-disk weight streaming.)
This is good advice if you have nvidia, but for Mac does not apply currently.
So I did test this, and it doesn't work because the quantized layers need torch._int_mm, which PyTorch's MPS backend doesn't implement. It just throws NotImplementedError.
> a ~9-second 480x864 clip at 20 steps takes me a bit over an hour
that's rough. for comparison, i tried the exact same parameters on my 5090 RTX and it took 2 minutes to generate.
i believe diffusion models are primarily compute bound so the macs aren't really the ideal hardware for this kind of stuff
I wonder how much faster your m5 pro is compared to my M1 Max @ 64gb
wait till the M7 bro you’re almost there, rumor has it that Apple is skipping the M6 but it still might be 2028
What is the quality of the output like compared to something like Veo?
It's better than all private video models like Veo. Yes, I too am incredulous they released this open weights. It's a VERY disruptive model in all the good ways.
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How much free space do you have left after running this llm model? Have you tried to develop your own model with the M5?
In the AMA Minimax said that H3 could support sparse attention, that would be a huge speedup! I wonder if there are any news on that. H3 is very cool. EDIT: testing a --sparse-attention optional mode based on what they said in the Reddit post.
running this on an m1 max 64gb, it produces some really nice clips with music and audio, stitching the clips together after makes a nice short story generated entirely using a local ai system. It takes quite a while to generate each clip though, But at least it is working. I would like to know a few things:
-Optimal settings/configs examples for h3.c to help speed things up
-Optimal recommended generation settings for each mac product, i am sure it is easy to do
-Prompt generator assistant
Great work from the github author. The more i use it the more i realise i don't need a gui to generate video, just terminal.
My setup:
Macbook #1 as a client
Macbook #2 as server
-use macbook #1 terminal + ssh
-run mactop in terminal tab to monitor Macbook #2's hardware during ai video generation
-run h3.c on Macbook #2 via ssh session
-transfer the output video file from macbook #2 to macbook #1 using terminal scp
-view the video
This is where the DGX spark makes up a bit of the ground it loses on llm work, diffusion and cuda go together like peanut butter and jelly.
cough DiffusionGemma cough
Seriously, very dumb model compared to what you can run locally, but holy moly is it FAST on one GPU, seriously impressive. Can't wait for those to be scaled up a bit to fit perfectly within 96GB VRAM, then they'll be competitive.
On my 128GB M4 Max Mac Studio, generating a 15s 480p video with MiniMax H3 in ComfyUI takes an hour and a half.
Put Codex to work on deploying it now, hoping the speed can improve quite a lot :-) Thanks anyway
> On my 128GB M4 Max Mac Studio, generating a 15s 480p video with MiniMax H3 in ComfyUI takes an hour and a half.
That's crazy, a RTX Pro 6000 does that in in 2-3 minutes (give or take, depending on your exact settings). LLMs don't make the difference between standalone GPU vs unified memory + CPU so obvious as diffusion models seems to do.
It’s always been the case, it’s more the anomaly that LLMs work at comparable speeds on M series because almost all other ML runs way faster on Nvidia cards.
LLM prompt processing and diffusion models are compute bound, while LLM token generation is memory bandwidth bound.
An RTX6000 is a completely different class of hardware.
Really? No wonder I keep trying to type on it like a laptop but it doesn't work and doesn't even have a display!
Please keep up posted about the results!
First batch of quick test results: approximately 1/5 speed improvement
+20% or x5 speed improvement?
> Put Codex to work on deploying it now
Which codex?
For gods sakes, Apple let people have run other GPUs instead of these pissweak 2012 class mobile GPUs
This still requires 128Gb of memory, right? Me and my lowly 96Gb, like a commoner; missing out on the fun.
From README:
> On the 128 GB M5 Max, clean end-to-end image+audio and embedded-video+audio renders completed in 74.58 and 76.99 seconds respectively, each with about a 40.1 GB peak physical footprint and zero swaps.
Looks like it uses 40GB? So your 96GB mac setup should work fine i guess (Model itself is 33B)
This repo looks neat, but I hope they add some more clear benchmarks because that time (74.58s) is pretty meaningless given that the it/s (and total time) is highly dependent on mode (T2V vs I2V vs REF2V), resolution (0.4, 0.6mp, etc), duration (5-15 seconds), etc.
It shouldn't? Unless you're using BF16 for all weights (I'm using NVFP4 for the text encoder, otherwise everything BF16 (and audio F32)) you'll fit it all within 96GB VRAM, bugs non-with-standing :) I've been fitting this within 96GB VRAM without issues.
*notwithstanding
Anyway, good input!
I'll blame it on other book authors! :) https://en.wiktionary.org/wiki/nonwithstanding
> This misconstruction is very common, included in print publications spanning several centuries. It might be considered an alternative spelling, albeit still a mistaken usage.
Thanks though, I never actually knew so was helpful :)
you should have a look at https://github.com/deepbeepmeep/Wan2GP which is the goto tool for "gpu poor", although as people below already pointed out you should be fine with comfyui's standard setup aswell
First, I think they're not even talking about GPUs, this is macOS hardware so unified memory. Secondly, if they were talking about GPUs, then 96GB VRAM is hardly what people refer to when they say "gpu poor".
1) It would still run on the Mac's GPU.
2) Since it's unified memory, you won't have 96GB available.
3) I offered a solution that is usually recommended to the "gpu poor", if he's concerned with how much memory he would need.
4) I stated, that people already pointed out how he should be fine and that "gpu poor" doesn't apply to him.
5) "gpu poor" depends on what model you are trying to use. If you want to run Kimi or GLM you are still "gpu poor" even if you have an RTX Pro 6000 with 96GB of VRAM.
wow antirez does not sleep
when you have enough money to not have to worry about anything, you can go back to your hobbies. in this case, his hobby is programming.
Redis, hping and dump1090 were all side projects he started/written while having a full time job.
Your comment really sounds like "many other people would do A and B if they just had time and money to do so", but he's been doing so since time and money were major constraints.
Being a world class talent is independent of financial situation.
Of course it isn’t. If you can’t afford to eat you can’t achieve any potential you might have. Financial stability is a gamechanger for everyone.
That's stupid, if you're truly talented you'll solve the financial stuff in order to pursue whatever you want to do - if you don't then that's on you.
The majority of the population doesn't even have access to a functioning computer. So yeah maybe somebody truly talented can figure their way out of that hole after a few years but that's where alot of people are starting from.
You should read Outliers by Malcolm Gladwell
“I am, somehow, less interested in the weight and convolutions of Einstein's brain than in the near certainty that people of equal talent have lived and died in cotton fields and sweatshops."— Stephen Jay Gould
To show the world you're a "world class talent", whatever that means, also suggests you would either have to be a genius or have enough resources to work on your side quests. Latter implies you're well off so, no, I don't think there's zero correlation between the two in all cases.
talent w/o financial stability is a battery w/o circuit.
"enough money not to worry about anything" haha
Understatement of the year :-D
Wow, had to check some of his other repos; his the one behind dump1090
He's the one who wrote Kilo too!
Alright I’ve been afraid to ask but have been having trouble finding
What are some adult entertainment workflows in comfyui, I need best loras, best prompts to start with
and the communities, are they on telegram or something?
While you will find plenty of people willing to scam you to pay for “adult entertainment workflows”, the built in templates in ComfyUI for the model—perhaps dropping in a Lora Loader node for the a Turbo lora for speed—handle running the model, the subject matter adaptation isn’t really a workflow issue but one of reference/control images/audio/videos and prompting.
For Minimax H3, more than most models, you should read (and, if you are using an LLM for prompt assistance, make it sure it has access to) the official prompt guidelines, as each of the main models (fl2va that handles text-to-video and first- and/or last-frame-to-video and r2va that handles more complex reference cases) has its own structured prompt format (with many common features).
H3 is quite uncensored, but was not trained on p0rn, so it has no anatomy clues needed to generate that kind of stuff. For softer adult content it is reported to be fine on Reddit.
loras have been fixing that for years
Other than for pure t2v usage you probably don't need a LoRA for much, I have seen evidence that it is knowledgeable enough that it can handle a fair amount of anatomy looking and behaving reasonably with just relevant cues in control (for the fl2va model) or reference (for the r2va model) images.
And the r2va model can also use video input for motion reference.
This is a healthy question. We want to use these tools for regular old human needs and desires.
There will Reddit subs for it though couldn’t tell you which off top of my head
I’d personally steer clear of messaging platforms for this - who knows what one might stumble into there
> I’d personally steer clear of messaging platforms for this - who knows what one might stumble into there
Personally I have no interest, but sometime browse stuff out of curiosity. But this got more of my curiosity, what kind of "stuff" are you implying they might stumble upon on the open, public internet? Sure, some NSFW, horror and otherwise weird stuff is there, especially around AI generation, but hardly something that will leave you traumatized, unless I misunderstand what you're implying?
One thing I read on this topic on reddit is never EVER use the word "girl" when prompting H3. So CSAM probably.
Avoiding use of “girl” when you aren’t asking for a feminine child is good advice for any model that isn't specifically trained on a specialized prompting vocabulary (e.g., danbooru tags) where “girl” has a different meaning.
But I haven't seen anything reliable about H3 being particularly special in ther regard.
are these still 2026 problems? a simple vector index would associate girl as a synonym for adult woman as is used by both men and women in the English lexicon
even a Chinese model that thinks its Claude when asked would have inherited this association
Did you try this yourself? Of course you wouldn't, because not wanting to produce SCAM sorry I meant CSAM.
And no, including the word "girl" in H3 does not lead to CSAM in any way, shape or form, but it's a great example how FUD quickly spreads.
I don't have hardware to runs this, so no, I didn't.
One thing that I had experience with, that led me to believe this might be true: it seems one of the earlier llama models was over-tuned to resist generating CSAM. Once I tried a somewhat sensitive prompt containing the word "girl" in it. Llama only ever generated refusals for this prompt, citing I was prompting for CSAM. GPTs and Claudes of that era had no issues with the same prompt.
I do not know and very much plan to keep it that way
a friend told me there's a reddit called: unstable diffusion
How similar are Jeff Dean and Salvatore Sanfilippo?
My favorite Jeff Dean fact is that he’s also antirez. Which reminds me of my favorite Salvatore Sanfilippo fact. He’s also Jeff Dean
I'm totally following this
The claims seem fitting from a user named "onionisafruit"...
Is that what the identity function is?
It's why javascript had to add the triple equals check...
2 is not enough. 3 verifies the Dean-Sanfilippo correspondence.
Identify theft is not a joke Jim!
People are really good at stuff.
I noticed on a bar TV the other day that some of the Chromecast screensaver landscape photo credits were to Peter Norvig. They were really lovely pictures.
I've run into Peter Norvig twice. Once at a YC event; the other when I parked my motorhome in front of his house in Palo Alto for a couple of days while visiting a friend who happened to live on the same street (not on purpose, I didn't know it was his house, it was just where I found sufficient open street parking for a huge motorhome, big houses with fewer cars on the street than on my friend's block). I ran into him while walking my dog, he asked about the motorhome and we talked travel. He was lovely both times. Not everyone is nice about a big motorhome parking on their block, especially in California, but he was friendly.
I have had 2 encounters with Dr Norvig, all online. One, I randomly reach out for him to get a referral to a hiring manager at Google. He gave me a couple of email leads. Two, I emailed ask him about a writing piece regarding fuzzy logic and why it was not popular in the US academic landscape. I got a very long, specific and detail response back. I need to print that email out and frame it lol.
Anyone tried it with M4 Pro, 48GB of memory?
I'd love to know what the alternatives are and how this is better
This will be a little faster right now on an M4 or M5 because it's optimized for Apple Silicon. Assuming this model is still state of the art in six months, which might not be a surprise given how long other video models have taken, this should be much, much faster with the M7 chip.
I totally agree with you.
Noob question to all, is there any open source coding model that I can run on Mac mini 16gb?
I use Bonsai 27B ternary on my 24GB MBP. But, I believe you definitely can run it with 18 or even 8GB.
I'm looking to setup a way to create images for my own instagram marketing.
I do not care how long it takes to make 10 variations of a post as that speed would still be faster than me making it.
Does this model work with ComfyUI easily? Can I just download it?
Yes, there's a default workflow template in Comfy for that matter now.
How long to generate a 10-sec 1920x1080 vid on Mac M4 64GiB?
I mean yeah, a 5090 is obviously gonna smoke a Mac lol. But that’s not really the point. If I can run this thing locally and get a video in a few minutes instead of an hour, that’s already pretty sick.
neat — now I just need a machine with the memory bandwidth to render the three-second clip of my cat before the cat itself forgets what happened