M1 ultra stable diffusion reddit A group of open source hackers forked Stable Diffusion on GitHub and optimized the model to run on Apple's M1 chip, enabling images to be generated in ~ 15 seconds (512x512 pixels, 50 diffusion steps). I get about 4 sec/it with euler_ancestral, 1024x1024. 1 or V2. I'm using an M2 iPad Pro 8GB RAM with Draw Things and while it does amazing work, the detail and realism I'm able to achieve don't match what I see from others. Also, I have MacStudio (20coresCPU,48coresGPU, Apple M1 Ultra, 128GB RAM ). If I open the UI and use the text prompt "cat" with all the default settings, it takes about 30 seconds to… yes! i'm interested too. We're looking for alpha testers to try out the app and give us feedback - especially around how we're structuring Stable Diffusion/ControlNet workflows. It runs faster than the webui on my previous M1 Macmini (16GB RAM, 512 GB SSD), According to some quick google-fu, M1 Max is 3X slower than a 3080 12GB on Stable Diffusion, and according to Apple's press release, the M3 Max is 50% faster than the M1 Max, which means it's still slower than a 3080 12GB. Despite trying several configurations in Accelerate, none seem to work. You also can’t disregard that Apple’s M chips actually have dedicated neural processing for ML/AI. how long does it take you to do 120 frames animation Deforum 512x512, I have mac pro m1 (windows user till this bad decision) and now I am regretting I bought this p of shit device LOL is super slow regarding Stable Diffusion Deforum. Looks like we are in a similar situation and looking for similar guidance. As the budgetfriendly GPUs with big vram are quite limited, the M1 with its comined RAM seems to me like an attractive option. As I type this from my M1 Mac Book Pro, I gave up and bought a NVIDIA 12GB 3060 and threw it into a Ubuntu box. I had a M2 Pro for a while and it gave me a few steps/sec at 512x512 resolution (essentially an image every 10–20 sec), while the 4090 does something like 70 steps/sec (two or three images per second)! It's worth noting that you need to use your conda environment for both lstein/stable-diffusion and GFPGAN. It’s ok. . I have been running stable diffusion out of ComfyUI and am doing multiple loras with controlnet inpainting at 3840X3840 and exporting an image in about 3 minutes. (Or in my case, my 64GB M1 Max) Also of note, a 192GB M2 Ultra, or M1 Ultra, are capable of running the full-sized 70b parameter LLaMa 2 model Unfortunately, when it comes to video editing, single core performance is still more important and will outperform the threadrippers. I've researched but couldn't find a solution yet. I'm using SD with Automatic1111 on M1Pro, 32GB, 16" MacBook Pro. I have a M1 Ultra, and the longest training I've done is about 12 hours, but even that is too long. Stable Diffusion runs great on my M1 Macs. My M1 Air really struggles with it. I'm using a MacBook Pro 16, M1 Pro, 16G RAM, use a 4G model to get a 512*768 pic, but it costs me about 7s/it ,much more slower than I expect. The Draw Things app makes it really easy to run too. I think the main the is the RAM. I'm using replicate. An M2/M3 will give you a lot of VRAM but the 4090 is literally at least 20 times faster. It can a 50 iteration 512x512 image in 60-80s on my M1 Pro MBP with 16GPU cores. Or would if there weren't a bug which causes pytorch to crash at that exact resolution; any other resolution works fine. I’m always multitasking and it can get slower when that happens but I don’t mind. My work computer is a MacBook Pro M2 Pro, 32G, early 2023. I tried DiffusionBee a couple of weeks back and it Sep 11, 2022 · Don't bother with trying to run Stable Diffusion on M1. /r/StableDiffusion is back open after the protest of Reddit killing open API access, which will bankrupt app developers, hamper moderation, and exclude blind users from the site. I do both, and memory, GPU and local storage are going to be the three factors which have the most impact on performance. But just to get this out of the way: the tools are overwhelmingly NVidia-centric, you’re going to have to learn to do conversion of models with python, and I'm running A1111 webUI though Pinokio. Nov 2, 2017 · I've been using InvokeAI, which is a stable-diffusion fork. Not to mention that Apple has Oct 23, 2023 · I am benchmarking these 3 devices: macbook Air M1, macbook Air M2 and macbook Pro M2 using ml-stable-diffusion. Apple M1 Ultra / Max with 32GB Unified Memory (VRAM) good for Dreambooth? I was wondering if anyone had already successfull dreambooth running on a M1 System. Run it in the cloud instead. 8 seconds to generate a 512×512 image at 50 steps using Diffusion Bee in our tests on an M1 Mac Mini" But people are making optimisations all the time, so things can change. By comparison, the conventional method of running Stable Diffusion on an Apple Silicon Mac is far slower, taking about 69. Hey, is there a tutorial to run the latest Stable Diffusion Version on M1 chips on MacOS? I discovered DiffusionBee but it didn't support V2. Welcome to the unofficial ComfyUI subreddit. I'm trying to run Dreambooth with Kohya on a Mac Studio M1 Ultra 128GB, but I'm facing some challenges. Why I bought 4060 Ti machine is that M1 Max is too slow for Stable Diffusion image generation. Not a studio, but I’ve been using it on a MacBook Pro 16 M2 Max. I found the macbook Air M1 is fastest. Please keep posted images SFW. 5 based models, Euler a sampler, with and without hypernetwork attached). Mac Studio M1 Max, 64GB I can get 1 to 1. I ran into this because I have tried out multiple different stable-diffusion builds and some are set up differently. Also, the RTX 4090 is the best for content creation. 0 from pyTorch to Core ML. And for LLM, M1 Max shows similar performance against 4060 Ti for token generations, but 3 or 4 times slower than 4060 Ti for input prompt evaluations. com which provides Nvidia A100 GPU's and is I'm running stable-diffusion-webui on M1Mac (MacStudio 20coresCPU,48coresGPU, Apple M1 Ultra, 128GB RAM 1TB SSD). A1111 takes about 10-15 sec and Vlad and Comfyui about 6-8 seconds for a Euler A 20 step 512x512 generation. Please share your tips, tricks, and workflows for using this software to create your AI art. I've been experimenting with different settings, but SD doesn't seem to be using this huge amount of machine resources efficiently. When I look at GPU usage during image generation (txt2img) its max'd out to 100% but its almost nothing during dreambooth training. You have to know how to write some python to tell your mac to use all of its CPU and GPU cores is all. I convert Stable Diffusion Models DreamShaper XL1. Some friends and I are building a Mac app that lets you connect different generative AI models in a single platform. hi everyone! I've been using the WebUI Automatic1111 Stable Diffusion on my Mac M1 chip to generate image. A stable diffusion model, say, takes a lot less memory than a LLM. This actual makes a Mac more affordable in this category because you don’t need to purchase a beefy graphics card. Posted by u/Any-Winter-4079 - 148 votes and 163 comments Stable Diffusion UI , is a one click install UI that makes it easy to create easy AI generated art. However, I've noticed a perplexing issue where, sometimes, when my image is nearly complete and I'm about to finish the piece, something unexpected happens, and the image suddenly gets ruined or distorted. I'm new newbie, so I apologize if this topic has already been discussed. I can generate a 20 step image in 6 seconds or less with a web browser plus I have access to all the plugins, in-painting, out-painting, and soon dream booth. I have both M1 Max (Mac Studio) maxed out options except SSD and 4060 Ti 16GB of VRAM Linux machine. 5s/it 512x512 on A1111, faster on diffusion bee. Been playing with it a bit and I found a way to get ~10-25% speed improvement (tested on various output resolutions and SD v1. I have an M1 MacBook Pro. I find… Might not be best bang for the buck for current stable diffusion, but as soon as a much larger model is released, be it a stable diffusion, or other model, you will be able to run it on a 192GB M2 Ultra. I think I can be of help if a little late. If you follow these steps in the post exactly that's what will happen, but I think it's worth clarifying in the comments. xrpkbiwuz endfn rxfgs tskp ohezx jvgzpn enyz fejmt cparufhm ispqxq