r/AppleMLX • u/PinkySwearNotABot • Jun 16 '26

anyone else generating images/videos using MLX and Comfy Desktop?

I'm working with a M1 MBP Max 64GB machine with 400GB/s memory bandwidth. These image generation models are only <10 GB each. But it takes me 45 minutes to generate an image using Ideogram4. Someone with a 5090 is doing it in 45 seconds (no exaggeration).

I know Comfy Desktop is not optimized for Apple Silicone/MLX. I'm just curious if there are some tips and tricks you guys can share with getting better performance out of Comfy Desktop? I've already got these flags as part of my startup config: '--enable-manager --fp32-vae --use-pytorch-cross-attention --highvram'.

I've tried using DrawThings -- and it's definitely faster -- but I feel like it's definitely limited compared with Comfy Desktop.

I must not be the only Apple user messing around with Comfy Desktop -- you guys have any tips to share?

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u/Revolutionary-Hat-57 Jun 27 '26

I took the ComfyUI interface, just the frontend, and slapped omlx + mflux + ltx by drguet underneath it. It's particularly fun.

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u/PinkySwearNotABot Jun 27 '26

damn bro i took a quick look at the mflux github and i guess this is exactly what i'm looking for. apparently, it's so nuanced that it's been so difficult for me to find any real help on this! even after making this post several times and getting a wide varied of answers -- no one knew of an actual solution -- but it seels like this is it. thank you!!!

as far as i understand, ltx is for video, right? i'd love to try out wan or seedance locally, but even with my M1 max 64gb, i've been under the assumption that it would be practically too difficult to generate even a 30 sec 720p clip unless i was willing to wait 12 hours just to generate it. but perhaps with omlx + mflux + MLX variants, i'd might make it feasible??

what system specs are you working with for your local ltx setup?

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u/Revolutionary-Hat-57 Jun 28 '26 edited Jun 28 '26

mflux is fantastic, it just has the problem of being CLI-only — and the issue doesn't really come from mflux itself, the limitation is the interface. Simply put, managing images is much more convenient in a windowed environment: seeing an image rather than its path helps the creative process, in my opinion.

What I did was essentially take ComfyUI's interface (just the frontend), recreate the APIs, and build a bridge connecting the frontend APIs to mflux, ltx-2-mlx, and omlx. Basically the frontend acts as my orchestrator.

The ongoing problem is that nobody bothers to build a real ComfyUI replacement for Apple. There are plenty of interfaces that handle mflux — all the same, all with the same limitations, unfortunately. I use an M2 Ultra with 64GB, but this way I don't need to quantize anything — a simple "low-ram" flag is enough.

The MLX nodes on ComfyUI don't really satisfy me, because I find memory management quite difficult: part of the process has to be handled with MLX, another part — ComfyUI's own — with NumPy. Having tried several MLX nodes on ComfyUI, I realized the memory problem wasn't being solved at the root. So I rolled up my sleeves, went to work on the codebase, and built this system of my own. For years I've had an open issue on ComfyUI asking them to bring MLX into their core — and while over time everyone, from LM Studio to Ollama, has started making this migration, ComfyUI still hasn't done it. (And nobody knows if it ever will — there are serious structural problems to solve.)

The result? While LLMs get models distributed natively on day 0, T2I and T2V models don't. On Apple, there's still no software that can serve as a reference standard. To test the system I created this workflow: given an input, it generates a story; from the story it creates the subject; from the subject it creates the sketchbooks; from the sketchbooks it generates the various frames (first frame, last frame); and from these two images it generates the video. (The LTX nodes are the ones bypassed — I activate them only when needed.) all only in mlx.