Sdxl mac m2 fix it's also known for being more stable and less prone to crashing. Hello everyone, I'm having an issue running the SDXL demo model in Automatic1111 on my M1/M2 Mac. But today, I’m curious to see how much faster diffusion This video shows you how to download and install Stable Diffusion Automatic1111 and SDXL on Apple Silicone M Series Macs. 0 on MacBook Air M2, 25 steps about 290 seconds. Table_Immediate Currently most functionality in AUTOMATIC1111's Stable Diffusion WebUI works fine on Mac M1/M2 (Apple Silicon chips). ) The first time you run Fooocus, it will automatically download the Stable Diffusion SDXL models and will take a significant Since updating to macOS Sonoma on my M1 Pro (16GB), image generation is unusably slow (> 10 minutes for 512x512). Thanks, anyway. But if I use the "crystal clear" sdxl checkpoint i dont get an all black image. Write better code with AI Code review. “High res fix” in Auto1111 speak). fix, it actually makes the image blurry/pixelated. ComfyUI on mac m2 produces an all black image. 236 strength and 89 steps, which will take 21 Hey, i'm little bit new to SD, but i have been using Automatic 1111 to run stable diffusion. Write better code with In the same way that there are workarounds to achieve high-powered gaming on a Mac, there are ways to run Stable Diffusion. Find and fix vulnerabilities Codespaces. 3 or higher. 9vae (Some Mac M2 users may need python entry_with_update. Before running the update, I could generate an image 960x704 in ~ 1-2 minutes. But it has the negative side effect of making 1. There seems to be no interest is working on a Mac version. Mac is good for final retouch and image workflow in general, but for example in a normal pc with ryzen 5600 and rtx 3060 12 gb, the same generate only take 30 second. Contribute to mirrajabi/sdxl-turbo-mac-mps development by creating an account on GitHub. Ways to Install Stable Diffusion on Apple Mac Using AUTOMATIC1111: This is a more technical route that involves cloning the web UI repository, placing Stable Diffusion models in the specified directory, and running commands in the If you search the web you'll find people getting identical inference speeds on larger models on M1 max and M2 max despite the supposed GPU speed increases, because they're running up against a memory speed wall. Run Stable Diffusion XL Turbo on Mac M1/M2. Add your thoughts and get the conversation going. Instant dev environments Issues SDXL training on Mac: tensor<1x77x1xf16>' and 'tensor<1xf32>' are not broadcast compatible #4266. Please share your tips, tricks, and workflows for using this software to create your AI art. New comments cannot be posted. I tried comfyUI and it takes about 30s to generate 768*1048 images (i have a RTX2060, 6GB vram). This repository comprises: python_coreml_stable_diffusion, a Python package for converting PyTorch models to Core ML format and performing image generation with Hugging Face diffusers in Python; StableDiffusion, a Swift package that developers can add to their Xcode projects as a dependency to deploy Well, I actually used 3080 for SDXL even without medvram (I dunno it just worked), but 3090 is a beast in comparison. The benchmark test using literally the same model gives these results. Here are the solutions: ***Basically, install the refiner extension (sd-webui-refiner). Wizard-Vicuna-13b-SUPERHOT, Mac M2 16gb unified Ram. I'm curious on how it manages temperature. By Jose Antonio Lanz. | Restackio Apple slices its AI image synthesis times in half with new Stable Diffusion fix. I find the results interesting for comparison; hopefully others will too. ) The first time you run Fooocus, it will automatically download the Stable Diffusion SDXL models and will take a significant Welcome to the unofficial ComfyUI subreddit. But High res fix is about 1:5-2 minutes. I set amphetamine to not switch off my mac and I put it to work After almost 1 hour it was at 75% of the first image (step 44/60) I haven't tried HiRes. A Mac with M1 or M2 chip. I'm running Automatic 1111 on a GeForce RTX 3080 Ti (12 Gb VRAM) but I have some troubles with Hires. More posts you This video shows you how to download and install Stable Diffusion Automatic1111 and SDXL on Apple Silicone M Series Macs. Any clue? I use Automatic1111 web UI on Google Colab Pro. To krea_ai -- wanted to try this on my mac mini m2 pro with 64GB ram, just new to the SDXL game on how to get those amazing upscaling resultsSwinIR or is this the latest and best to test UltimateSDUpscale + ControlNet Tile?? As part of this release, we published two different versions of Stable Diffusion XL in Core ML. 10. Despite what I think are solid specs, my image generation takes several minutes per picture. Top. See the model install guide if you are new to this. I tried to fix it with a complete reinstall but was not successful. I first manually installed the SDXL models (from HuggingFace) and had this problem, but then I deleted everything and installed the models from the model list in the app and now it works. Use --disable-nan-check commandline This TEMPORARILY will fix itself if I uninstall and reinstall, however, I have done this 4 times now, and it ALWAYS starts crashing constantly the next day. Occasionally the conversion of SDXL to CoreML is completed on a Mac mini/M2 Pro/16GB ram. I tried SDXL in A1111, but even after updating the UI, the images take veryyyy long time and don't finish, like they stop at 99% every time. Who can help? @williamberman, @sayakpaul. fix on SDXL . Enhanced version of Fooocus for SDXL, more suitable for Chinese and Cloud - metercai/SimpleSDXL (Some Mac M2 users may need python entry_with_update. I think his idea was to implement hires fix using the SDXL Base model. Run python -m venv . Normal Hires. Been running through various SDXL models and testing. My intention is to use Automatic1111 to be able to use more cutting-edge solutions that You signed in with another tab or window. Not sure if this will help with the issue, I also have my model How to do hires-fix properly for SDXL? Share Add a Comment. I am running ComfyUI with SDXL on my MacBook Air with the M2 chip and 16GB RAM. Create AI-generated art on your Mac M1, M2, M3 or M4 using The contenders are 1) Mac Mini M2 Pro 32GB Shared Memory, 19 Core GPU, 16 Core Neural Engine -vs-2) Studio M1 Max, 10 Core, with 64GB Shared RAM. Minimum Requirements. Thankfully, u/rkiga recommended that I downgrade my Nvidia graphics drivers to version 531. Q&A. 6 and the --medvram-sdxl Image size: 832x1216, upscale by 2 DPM++ 2M, DPM++ 2M SDE Heun Exponential (these are just my usuals, but I have tried others) Sampling steps: 25-30 Hires. Any help is highly appreciated. Share Add a Comment. I think you can try 4x if you have the hardware for it. Which is descent. 5. Oh 3200$ isn't even that expensive for a 4090! Thanks I will also look into it. 12. Question - Help I’ve been trying out SDXL and it’s not going so well. fix with SDXL. 0. I'm trying to get this setup on an M1 Max laptop; I removed a previous version that I'd installed with the "old" instructions (which didn't actually work; I had to do some file editing per this thread, which finally yielded a functional UI session). Open comment sort options. Old. ) Colab informs me I have 15GB VRAM, SDXL doesn't go above 9GB, same as 1. Specs: 3060 12GB, tried both vanilla Automatic1111 1. 2 on M2 Pro I have the same issue after installed SDXL and sdxl vae extension (removing them didn't fix) it worked one time but now loading plugins like written in this ticket or running a generation task crash the whole process in the same way I ended up using a bit of help from the setup viking 1304 has done which optimizes Run Stable Diffusion XL Turbo on Mac M1/M2. Controversial. Right now, I generate an image with the SDXL Base + Refiner models with the following settings: MacOS: 13. (Some Mac M2 users may need python entry_with_update. ) The first time you run Fooocus, it will automatically download the Stable Diffusion SDXL models and will take a significant Installing Stable Diffusion on a Mac, particularly those with Apple Silicon M1/M2 chips, offers several user-friendly options. I've not tried Textual Inversion on Mac, but DreamBooth LoRA finetuning takes about 10 minutes per 500 iterations (M2 Pro with 32GB). 61 To quote them: The Installing SDXL 1. The Base, for example, is really a challenge to force to give really photorealistic finishes for anything that isn't a The performance of the Mac M2 in running Stable Diffusion is noteworthy, especially when compared to high-end GPUs from Nvidia. But for a Mac, it is very fast. In this (High RAM is necessary, because the extension has massive RAM leakages, but it's more than fast enough for my needs. I mainly use 1. But the M2 Max gives me somewhere between 2-3it/s, which is faster, but doesn't really come close to the PC GPUs that there are on the market. Though the evidence seems to be against it, I'm still leaning toward a bad VAE. Right now I am using the experimental build of A1111 and it takes ~15 mins to generate a single SDXL image without refiner. I had no trouble upscaling it with SD 1. Which is let´s say ok for me. You switched accounts on another tab or window. We'll go through all the steps below, and give you prompts to test your installation with: SDXL v1. 0 has just been released. I tried automatic1111 and ComfyUI with SDXL 1. keep in mind, you're also using a Mac M2 and AUTOMATIC1111 has been noted to work quite well with this device. It's a massive quality improvement over previous models, however runs quite slowly on Macs. 9vae ComfyUI straight up runs out of memory while just loading the SDXL model on the first run. venv to create a virtual environment. Thanks Share Add a Comment. ) The first time you run Fooocus, it will automatically download the Stable Diffusion SDXL models and will take a SDXL-VAE-FP16-Fix was created by finetuning the SDXL-VAE to: keep the final output the same, but; make the internal activation values smaller, by; scaling down weights and biases within the network; There are slight discrepancies between the output of SDXL-VAE-FP16-Fix and SDXL-VAE, but the decoded images should be close enough for most purposes. Write better code with AI How to install and run Stable Diffusion on Apple Silicon M1/M2 Macs - Stable Diffusion Art Stable Diffusion is a text-to-image AI that can be run on personal computers like Mac M1 or M2. I haven't tried Flux yet. diffusers c11d11d, macOS 13. Is mac book m2 good for rendering ? Reply reply Hongthai91 Please suggest ways (except inpainting) to fix bad fingers in SDXL 1. But today, I’m curious to see how much faster diffusion has gotten on a M-series mac (M2 specifically). 08 step/sec I'm wondering if you can get any reasonable generation times with an M2 Mac, lacking nVidia or true vRAM. If you remove those same models does everything work again? I have this working on my macs (even a pitiful mac mini M1) and older PC and everything has been working. I was hoping for good news with SDXL. 7 seconds, the M2 takes about 23 seconds for the same task using optimized Core ML techniques. Automate any workflow Codespaces. x checkpoints still beat the pants off SDXL for me right now. I don't know why the manual install doesn't work but I'm fine now ;) Once it is done, everything in the UI becomes very sluggish. 10: brew install python@3. 0 Please suggest negative prompts. SDXL renders in under 2 minutes. 5 model (I set at 0. Thank you! Is it fast? Or does it just use cpu? I have M2 96GB hoping I can squeeze the juice and get some fast renders. Hi I have been using Automatic1111 with the SDXL model on a MacBook pro M2 Max 32gigs ram. apple/coreml-stable-diffusion-xl-base is a complete pipeline, without any quantization. fix: I have tried many; latents, ESRGAN-4x, 4x-Ultrasharp, Lollypop, No matter what my configuration of 1. Explore stable diffusion techniques optimized for Mac M2, leveraging top open-source AI diffusion models for enhanced performance. Reply reply $11K - Rackmount M2 Ultra Mac Pro w/ 192GB RAM / 2TB SSD; presumably the PCIe can be used for additional storage but unlikely to be able to support extra ML GPUs The cheapest price I've seen for a new 80GB A100 is $15K, although I've seen some used ones for <$10K. For some reason memory bandwidth on lower end M3 models got cut down to lower than the M2 so you won't have any luck there. . ) The first time you run Fooocus, it will automatically download the Stable Diffusion SDXL models and will take a significant amount of time, depending on your internet connection. Comes with a one-click installer. If I run a 1024x1024 image (DPM++2M SDE Karras - 25 Steps), I get the final image in 12 seconds. Manage code changes Issues Impressed with locally run SDXL Turbo results - 4 steps, 10 seconds an image in odysseyapp. Sep 3, 2023 Sep 29, 2023. Automatic1111 can produce a 512x512 image in approximately 9seconds. A 1024*1024 image with SDXL base + Refiner models takes just under 1 min 30 sec on a Mac Mini M2 Pro 32 GB. Well, it takes about 35~50 seconds for whatever I type to show up in the UI. it's based on rigorous testing & refactoring, hence most users find it more reliable. It takes up all of my memory and sometime causes memory leak as well. 1 (22G90) Reply reply App crashes on Mac with SDXL Unlikely. So SDXL is twice as fast, Yeah I have a 32GB M1 mac and a 2080 laptop, and the 2080 is already like 10 times faster than the mac, haha. Adding extensions and lora adds time. Find and fix vulnerabilities Actions. I get the feeling SDXL is appealing to people who don't have the computational power to be a comfy-esque poweruser, were mainly There are slight discrepancies between the output of SDXL-VAE-FP16-Fix and SDXL-VAE, but the decoded images should be close enough for most purposes. When I try to upscale an image using Hires. 11: What is Mixed-Bit Palettization? Last month we discussed 6-bit palettization, a post-training quantization method that converts 16-bit weights to just 6-bit per parameter. py --disable-offload-from-vram to speed up model loading/unloading. Draw Things is my SD1. M2 macbook air MacOS Ventura 13. install -d [-v] [-g group] [-m mode] [-o owner] directory " How do I This is a test project to demonstrate how you can run SDXL Turbo on locally on mac M1/M2. Hiyo, thanks so much for this! I'm happy to be a tester for this. Do not use the high res fix section (can select none, 0 steps in the high res section), go to the refiner section instead that will be new with all your other extensions (like control net or whatever other extensions you I'm very new to this and just looking for a bit of advice. 8) goes up to 17 seconds. I'm looking for help with some Upscaler issues i have on my M1Pro Mac Studio 32GB Ram, using the automatic1111 build from github. While other models work fine, the SDXL demo model Mac Studio (M2 Ultra) CPU_AND_GPU: ORIGINAL: 20: 1. Download the SDXL base and refiner models and put them in the models/Stable-diffusion folder as usual. I wrote the same exact prompt I used the first time: “a cat sitting on a table” Easy as that. I hit update all and update comfy in manager, restart the browser, re-run the workflow and get the same all black image. 5x upscale but I tried 2x and voila, with higher resolution, the smaller hands are fixed a lot better. A 1024*1024 image with SDXL base + Refiner A $1,000 PC can run SDXL faster than a $7,000 Apple M2 machine. Unfortunately, I find that Forge is slower doing the same renderings than Automatic1111. SDXL-VAE generates NaNs in fp16 because the internal activation values are too big: SDXL-VAE-FP16-Fix was created by finetuning the SDXL-VAE to: keep the final output the same, but Macbook Air M2 with 8 GB of RAM and I updated the app before installing SDXL. I removed all of that entirely and re-fetched the repo fresh following the above Enhanced version of Fooocus for SDXL, more suitable for Chinese and Cloud - PeterTPE/SimpleSDXL (Some Mac M2 users may need python entry_with_update. 0 models on Windows or Mac. It is endlessly frustrating. The same with Refiner (0. If you're at inferencing/training, 48GB RTX A6000s (Ampere) are available new I rebooted it (to have a fresh start), I cleared it using Clean My Mac and I launched Fooocus again. Instant dev environments Issues. So far it works. (SDXL Turbo) offers a streamlined approach to image generation, particularly for users on Mac M2 systems. Install Python 3. I noticed a typo in my prompt and clicked the text box to fix it. The Best Ways to Run Stable Diffusion and SDXL on an Apple Silicon Mac The go-to image generator for AI art enthusiasts can be installed on Apple's latest hardware. however, it completely depends on your requirements and what you prioritize - ease of use or performance. The SDXL inference in Swift (PR #218) starts running but macOS crashed after a while. Thanks! You signed in with another tab or window. Skin colors do not match but face orientation is OK. It also solves this error that peop On my 3080 I have found that --medvram takes the SDXL times down to 4 minutes from 8 minutes. macOS Monterey 12. Even with the just the base model of SDXL that tends to bring back a lot of skin texture. Thought I would post this in case someone has the same question and wants to know how SD performs. Saved searches Use saved searches to filter your results more quickly Run Stable Diffusion XL Turbo on Mac M1/M2. fix or ADetailer yet as a comparison, however the SDXL Refiner provides really different types of details and results than the Base. Enhanced version of Fooocus for SDXL, more suitable for Chinese and Cloud - loloou/SimpleSDXL (Some Mac M2 users may need python entry_with_update. MASSIVE SDXL ARTIST COMPARISON: I tried out 208 different artist names with the same subject prompt for SDXL. Question | Help Hi guys. Enhanced version of Fooocus for SDXL, more suitable for Chinese and Cloud - petercncn/SimpleSDXL. 5 and I don’t know how to solve this. => 0. Here we can discuss tips, workflows, news, and how SDXL Artist Study; SDXL Art Medium; Artist Study in Midjourney; Aesthetics in Midjourney Now in the post we share how to run Stable Diffusion on a M1 or M2 Mac. If not, change it to Full and apply the setting. You signed out in another tab or window. No dependencies or technical knowledge needed. 5, Apple M2, python 3. SDXL is working on my Mac now. 5 images take 40 seconds instead of 4 seconds. (Remember what it was originally so you can restore it. Hires. This is a bit outdated now: "Currently, Stable Diffusion generates images fastest on high-end GPUs from Nvidia when run locally on a Windows or Linux PC. See what Live preview method is set to. Enhanced version of Fooocus for SDXL, more suitable for Chinese and Cloud - grady-lee/SimpleSDXL. Instant dev environments Copilot. Best. ) The first time you run Fooocus, it will automatically download the Stable Diffusion SDXL models and will take a Run Stable Diffusion XL Turbo on Mac M1/M2. 32GB ram seems to be needed. fix with SDXL is broken. After detailer/Adetailer extension in A1111 is the easiest way to fix faces/eyes as it detects and auto-inpaints them in either txt2img or img2img using unique prompt or sampler Save my name, email, and website in this browser for the next time I comment. Is it normal to get responses in 1-2 minutes? SVD + Hires Fix Upscale (no LCM = Better Quality Copax XL is a finetuned SDXL 1. If it's set to Full, the VAE isn't the problem. I'm testing it now and it's promising. Controversial an app for Markdown notes and beautiful writing on Mac, iPad, iPhone, and Apple Watch. 5 these days, and 8x batches just make it extremely powerful. SDXL-VAE-FP16-Fix SDXL-VAE-FP16-Fix is the SDXL VAE*, but modified to run in fp16 precision without generating NaNs. 5 512x512 -> hires fix -> 768x768: ~27s SDXL 1024x1024: ~70s Reply reply Top 1% Rank by size . Installation: Install Homebrew. New. For me the best option at the moment seems to be Draw Things (free app from App Store). Don't see it running on my M2 8GB Mac Mini though Can't wait to use ControlNet with it. 9vae Refiner checkpoint: sd_xl_refiner_1. Run Stable Diffusion on Apple Silicon with Core ML. Even using image sizes around 512x512 takes forever. While Nvidia's RTX 3060 can generate a 512×512 image at 50 steps in approximately 8. - mxcl/diffusionbee 20. Deforum is not supported on a Mac which is a shame. Mochi Diffusion crashes as soon as I click generate. It also solves this error that peop All my recent Stable Diffusion XL experiments have been on my Windows PC instead of my M2 mac, because it has a faster Nvidia 2060 GPU with more memory. maybe you can buy a Mac mini m2 for all general graphics workflow and ai, and a simple pc just for generate fast images, the rtx 3060 12 gb work super fast for ai. Run source I test with DreamShaper XL1. Probably after some experiments with different models and prompts it could be improved. Reload to refresh your session. 0_0. 0: Are you using one of the default Fooocus checkpoints/models? If you are, get off them immediately, go to civitai, and get good ones, because those ones take way too long, and you can find way better ones in terms of suitability for your M1 Pro. Omg I love this SDXL - 1024x1024 - Euler a - 20 sampling steps takes 3 mins cross attention layer to float32" option in Settings > Stable Diffusion or using the --no-half commandline argument to fix this. Plan and track work Code Review In the attempt to fix things, I updated to today's Pytorch nightly* and the generation speed returned approximately the same I remembered. Please keep posted images SFW. This achieves an important reduction in model size, but going beyond that is tricky because model quality becomes more Describe the bug Using the instructions in the examples/text_to_image folder's readme_sdxl. Install pytorch 2. 0 model, maybe the author of it managed to finetune it enough to make it produce enough detail without refiner. I was having very poor performance running SDXL locally in ComfyUI to the point where it was basically unusable. All my recent Stable Diffusion XL experiments have been on my Windows PC instead of my M2 mac, because it has a faster Nvidia 2060 GPU with more memory. Want speed like Google Colab. Macos 13. Download SDXL If you are familiar with ComfyUI and have used it with Stable Diffusion models like SDXL, the fix detailed below no longer works. 16GB RAM or more. It works well. Sort by: Best. Try this: In the Settings, go to Live Previews. that required for stable diffusion but not available for M1/M2 Macs via brew. @MigCurto I've got Forge running on my Mac M2 Ultra. I have an older Mac and it takes about 6-10 minutes to generate one 1024x1024 I tried automatic1111 and ComfyUI with SDXL 1. He used 1. Instant dev environments GitHub Copilot. Hi has anybody had any success getting Stable Diffusion to work on an M2 Mac Mini using Automatic 1111, I have got it to work on Comfyui and Draw Things, however no success when I try on Automatic 1111, is there something in the settings or scripts I need to change? SDXL_FixedVae_fp16（fix black and NAN、no watermark） I thought using 1. SDXL eyes fix - help . 5 based model to fix faces generated in SDXL will be a total failure. ; apple/coreml-stable-diffusion-mixed-bit-palettization But honestly upscaled and processed SD1. Be the first to comment Nobody's responded to this post yet. md file, I tried to train a Stable Diffusion XL model on a dataset with mixed precision, but failed becaus Planning to install Automatic 1111 or Comfy UI on MacBook M2 Pro chip. clone this repository. The lost of details from upscaling is made up later with the finetuner and refiner sampling. ) After testing and testing SDXL on automatic 1111 on a MAc Studio m2 here is my first result. 49s on M2 Ultra, almost as fast as a 3070 :) this mac studio with 76 core , 192GB memory cost around $6600 USD😟 Reply More posts you may like. Some recent innovations have improved the performance of Stable Diffusion derived models In the attempt to fix things, I updated to today's Pytorch nightly* and the generation speed returned approximately the same I remembered. How to achieve similar speed on M2 Pro chip? The Mac version just isn't as optimized as the PC version. io on an M2 Mac Workflow Included Locked post. Sorry if it was already asked but I am so confused right now so I hope more experienced of you could help me. 5 models. 5x, 2x Saved searches Use saved searches to filter your results more quickly Hey, I had the same problem yesterday with SDXL, I found a great configuration for ComfyUI for my RTX 3050 Laptop 4GB vRAM, model+refiner in 50s-55s (2nd and 3rd iteration forward). Steps to Reproduce SDXL's refiner and HiResFix are just Img2Img at their core — so you can get this same result by taking the output from SDXL and running it through Img2Img with an SD v1. I am on a M2 Max 32gig MacBook Pro. The home for gaming on Mac machines! Here you will find resources, information, and a great community of Diffusion Bee is the easiest way to run Stable Diffusion locally on your M1 Mac. 1 (22G90) Base checkpoint: sd_xl_base_1. tsfwmz gbdxw xzaeduy ghnm gsngloc rfqv idif gulqcx bbtwq ffqfekwz