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.
I wonder how much faster your m5 pro is compared to my M1 Max @ 64gb
diddid 2 hours ago [-]
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.
c0rruptbytes 3 hours ago [-]
wow antirez does not sleep
punnerud 31 minutes ago [-]
Wow, had to check some of his other repos; his the one behind dump1090
mlmonkey 2 hours ago [-]
Understatement of the year :-D
behnamoh 2 hours ago [-]
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.
azinman2 1 hours ago [-]
Being a world class talent is independent of financial situation.
behnamoh 52 minutes ago [-]
talent w/o financial stability is a battery w/o circuit.
stressback 2 hours ago [-]
"enough money not to worry about anything" haha
TechSquidTV 3 hours ago [-]
This still requires 128Gb of memory, right? Me and my lowly 96Gb, like a commoner; missing out on the fun.
thehamkercat 3 hours ago [-]
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)
vunderba 2 hours ago [-]
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.
tipiirai 2 hours ago [-]
I'd love to know what the alternatives are and how this is better
abhinai 3 hours ago [-]
How similar are Jeff Dean and Salvatore Sanfilippo?
onionisafruit 3 hours ago [-]
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
tomcam 2 hours ago [-]
I'm totally following this
ralusek 2 hours ago [-]
Is that what the identity function is?
silisili 17 minutes ago [-]
It's why javascript had to add the triple equals check...
songhonglei1985 1 hours ago [-]
[dead]
Rendered at 06:11:55 GMT+0000 (Coordinated Universal Time) with Vercel.
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
> 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)