5, all extensions updated. A Tensor with all NaNs was produced in the vae. It seems like the actual working of the UI part then runs on CPU only. fix) is about 14% slower than 1. 0. set COMMANDLINE_ARGS=--xformers --medvram. 8 / 3. This uses my slower GPU 1with more VRAM (8 GB) using the --medvram argument to avoid the out of memory CUDA errors. Introducing our latest YouTube video, where we unveil the official SDXL support for Automatic1111. 1 512x512 images in about 3 seconds (using DDIM with 20 steps), it takes more than 6 minutes to generate a 512x512 image using SDXL (using --opt-split-attention --xformers --medvram-sdxl) (I know I should generate 1024x1024, it was just to see how. If it still doesn’t work you can try replacing the --medvram in the above code with --lowvram. 6. 2gb (so not full) I tried different CUDA settings mentioned above in this thread and no change. nazihater3000. bat` Beta Was this translation helpful? Give feedback. I have always wanted to try SDXL, so when it was released I loaded it up and surprise, 4-6 mins each image at about 11s/it. That speed means it is allocating some of the memory to your system RAM, try running with the commandline arg —medvram-sdxl for it to be more conservative in its memory. You can make AMD GPUs work, but they require tinkering ; A PC running Windows 11, Windows 10, Windows 8. 05s/it over 16g vram, I am currently using ControlNet extension and it worksYeah, I don't like the 3 seconds it takes to gen a 1024x1024 SDXL image on my 4090. It takes a prompt and generates images based on that description. Open 1 task done. The Base and Refiner Model are used sepera. プロンプト編集のタイムラインが、ファーストパスと雇用修正パスで別々の範囲になるように変更(seed breaking change) マイナー： img2img バッチ： img2imgバッチでRAM節約、VRAM節約、. XX Reply replyComfy UI after upgrade: Sdxl model load used 26 GB sys ram. the problem is when tried to do "hires fix" (not just upscale, but sampling it again, denoising and stuff, using K-Sampler) of that to higher resolution like FHD. 0 Everything works perfectly with all other models (1. 2. Also, don't bother with 512x512, those don't work well on SDXL. add --medvram-sdxl flag that only enables --medvram for SDXL models prompt editing timeline has separate range for first pass and hires-fix pass (seed breaking change) ( #12457 ) OnlyOneKenobiI tried some of the arguments from Automatic1111 optimization guide but i noticed that using arguments like --precision full --no-half or --precision full --no-half --medvram actually makes the speed much slower. Do you have any tips for making ComfyUI faster, such as new workflows?We might release a beta version of this feature before 3. Enter the following formula. You can also try --lowvram, but the effect may be minimal. Please use the dev branch if you would like to use it today. I've also got 12GB and with the introduction of SDXL, I've gone back and forth on that. My full args for A1111 SDXL are --xformers --autolaunch --medvram --no-half. And I'm running the dev branch with the latest updates. So I'm happy to see 1. During renders in the official ComfyUI workflow for SDXL 0. Reviewed On 7/1/2023. 5 model to generate a few pics (take a few seconds for those). ago. 6. Also, as counterintuitive as it might seem,. Put the VAE in stable-diffusion-webuimodelsVAE. #stablediffusion #A1111 #AI #Lora #koyass #sd #sdxl #refiner #art #lowvram #lora This video introduces how A1111 can be updated to use SDXL 1. 0 version ratings. In ComfyUI i get something crazy like 30 minutes because high RAM usage and swapping. I had to set --no-half-vae to eliminate errors and --medvram to get any upscalers other than latent to work, have not tested them all, only LDSR and R-ESRGAN 4X+. Next is better in some ways -- most command lines options were moved into settings to find them more easily. This is the same problem. Reply reply gunbladezero • Try using this, it's what I've been using with my RTX 3060, SDXL images in 30-60 seconds. Introducing our latest YouTube video, where we unveil the official SDXL support for Automatic1111. I get new ones : "NansException", telling me to add yet another commandline --disable-nan-check, which only helps at generating grey squares over 5 minutes of generation. bat with --medvram. bat is), and type "git pull" without the quotes. SDXL initial generation 1024x1024 is fine on 8GB of VRAM, even it's okay for 6GB of VRAM (using only base without refiner). use --medvram-sdxl flag when starting. --always-batch-cond-uncond. Your image will open in the img2img tab, which you will automatically navigate to. I posted a guide this morning -> SDXL 7900xtx and Windows 11, I. I have the same GPU, 32gb ram and i9-9900k, but it takes about 2 minutes per image on SDXL with A1111. However, when the progress is already 100%, suddenly VRAM consumption jumps to almost 100%, only 200-150Mb is left free. . My GPU is an A4000 and I have the --medvram flag enabled. 0. 6: with cuda_alloc_conf and opt. 5GB vram and swapping refiner too , use --medvram-sdxl flag when starting r/StableDiffusion • SDXL 1. 1 / 4. md, and it seemed to imply that when using the SDXL model loaded on the GPU in fp16 (using . 筆者は「ゲーミングノートPC」を2021年12月に購入しました。 RTX 3060 Laptopが搭載されています。専用のVRAMは6GB。 その辺のスペック表を見ると「Laptop」なのに省略して「RTX 3060」と書かれていることに注意が必要。ノートPC用の内蔵GPUのものは「ゲーミングPC」などで使われるデスクトップ用GPU. Say goodbye to frustrations. 9 model for Automatic1111 WebUI My card Geforce GTX 1070 8gb I use A1111. isocarboxazid increases effects of dextroamphetamine transdermal by decreasing metabolism. 17 km. Example: set VENV_DIR=C: unvar un will create venv in. Side by side comparison with the original. It defaults to 2 and that will take up a big portion of your 8GB. I just loaded the models into the folders alongside everything. In your stable-diffusion-webui folder, create a sub-folder called hypernetworks. Reply. But it has the negative side effect of making 1. Happy generating everybody! (i) Generate the image more than 512*512px size (See this link > AI Art Generation Handbook/Differing Resolution for SDXL) . 5 models) to do the same for txt2img, just using a simple workflow. Long story short, I had to add --disable-model. You should see a line that says. Open in notepad and do a Ctrl-F for "commandline_args". Strange i can Render full HD with sdxl with the medvram Option on my 8gb 2060 super. I have also created SDXL Profiles on a dev environment . Next. 5, but for SD XL I have to, or doesnt even work. 5 models, which are around 16 secs). It's definitely possible. This is the way. I'm on an 8GB RTX 2070 Super card. 既にご存じの方もいらっしゃるかと思いますが、先月Stable Diffusionの最新かつ高性能版である Stable Diffusion XL が発表されて話題になっていました。. finally , AUTOMATIC1111 has fixed high VRAM issue in Pre-release version 1. fix resize 1. 4. No, it's working for me, but I have a 4090 and had to set medvram to get any of the upscalers to work, cannot upscale anything beyond 1. 0 out of 5. But it has the negative side effect of making 1. I can generate 1024x1024 in A1111 in under 15 seconds, and using ComfyUI it takes less than 10 seconds. Speed Optimization. . See more posts like this in r/StableDiffusionPS medvram giving me errors and just wont go higher than 1280x1280 so i dont use it. Even with --medvram, I sometimes overrun the VRAM on 512x512 images. 5 Models. Training scripts for SDXL. Results on par with midjourney so far. ダウンロード. . • 4 mo. If you have more VRAM and want to make larger images than you can usually make (e. 3. I just loaded the models into the folders alongside everything. amd+windows kullanıcıları es geçiliyor. AUTOMATIC1111 版 WebUI Ver. If you have low iterations with 512x512, use --lowvram. 0 version ratings. So at the moment there is probably no way around --medvram if you're below 12GB. 5 images take 40. 5 models in the same A1111 instance wasn't practical, I ran one with --medvram just for SDXL and one without for SD1. 9. 6. For example, you might be fine without --medvram for 512x768 but need the --medvram switch to use ControlNet on 768x768 outputs. --xformers --medvram. Reply LawProud492 • Additional comment actions. 0 est le dernier modèle en date. To save even more VRAM set the flag --medvram or even --lowvram (this slows everything but alows you to render larger images). Its not a binary decision, learn both base SD system and the various GUI'S for their merits. I've gotten decent images from SDXL in 12-15 steps. 2 You must be logged in to vote. For 8GB vram, the recommended cmd flag is "--medvram-sdxl". The recommended way to customize how the program is run is editing webui-user. Option 2: MEDVRAM. fix: I have tried many; latents, ESRGAN-4x, 4x-Ultrasharp, Lollypop, Ok sure, if it works for you then its good, I just also mean for anything pre SDXL like 1. 새로운 모델 SDXL을 공개하면서. Reply AK_3D • Additional comment actions. I shouldn't be getting this message from the 1st place. Once they're installed, restart ComfyUI to enable high-quality previews. commandline_args = os. Jumped to 24 GB during final rendering. (Also why should i delete my yaml files ?)Unfortunately yes. Memory Management Fixes: Fixes related to 'medvram' and 'lowvram' have been made, which should improve the performance and stability of the project. There is also an alternative to --medvram that might reduce VRAM usage even more, --lowvram,. Launching Web UI with arguments: --medvram-sdxl --xformers [-] ADetailer initialized. Integration Standard workflows. 1 File (): Reviews. tif, . 5 in about 11 seconds each. This allows the model to run more. --lowram: None: False: Load Stable Diffusion checkpoint weights to VRAM instead of RAM. sd_xl_base_1. set COMMANDLINE_ARGS=--xformers --opt-split-attention --opt-sub-quad-attention --medvram set PYTORCH_CUDA_ALLOC_CONF=garbage_collection_threshold:0. User nguyenkm mentions a possible fix by adding two lines of code to Automatic1111 devices. set COMMANDLINE_ARGS= --xformers --no-half-vae --precision full --no-half --always-batch-cond-uncond --medvram call webui. tiffFor me I have an 8 gig vram, trying sdxl in auto1111 just tells me insufficient memory if it even loads the model and when running with --medvram image generation takes a whole lot of time, comfi ui is just better in that case for me, lower loading times, lower generation time, and get this sdxl just works and doesn't tell me my vram is shit. EDIT: Looks like we do need to use --xformers, I tried without but this line wouldn't pass meaning that xformers wasn't properly loaded and errored out, to be safe I use both arguments now, although --xformers should be enough. If you’re unfamiliar with Stable Diffusion, here’s a brief overview:. Then, I'll go back to SDXL and the same setting that took 30 to 40 s will take like 5 minutes. However, for the good news - I was able to massively reduce this >12GB memory usage without resorting to --medvram with the following steps: Initial environment baseline. pth (for SDXL) models and place them in the models/vae_approx folder. ago. . on my 6600xt it's about a 60x speed increase. Don't forget to change how many images are stored in memory to 1. I have searched the existing issues and checked the recent builds/commits. 1-495-g541ef924 • python: 3. • 8 mo. Don't give up, we have the same card and it worked for me yesterday, i forgot to mention, add --medvram and --no-half-vae argument i had --xformerd too prior to sdxl. 👎 2 Daxiongmao87 and Nekos4Lyfe reacted with thumbs down emojiImage by Jim Clyde Monge. --medvram VRAMが4～6GBの場合に必須です。VRAMが少なくても生成可能になりますが、若干生成速度は落ちます。. It can produce outputs very similar to the source content (Arcane) when you prompt Arcane Style, but flawlessly outputs normal images when you leave off that prompt text, no model burning at all. On a 3070TI with 8GB. Workflow Duplication Issue Resolved: The team has resolved an issue where workflow items were being run twice for PRs from the repo. It's definitely possible. tiff in img2img batch (#12120, #12514, #12515) postprocessing/extras: RAM savingsMedvram has almost certainly nothing to do with it. not SD. ptitrainvaloin. tiff ( #12120、#12514、#12515 )--medvram VRAMの削減効果がある。後述するTiled vaeのほうがメモリ不足を解消する効果が高いため、使う必要はないだろう。生成を10%ほど遅くすると言われているが、今回の検証結果では生成速度への影響が見られなかった。 生成を高速化する設定You can remove the Medvram commandline if this is the case. --xformers-flash-attention：启用带有 Flash Attention 的 xformers 以提高再现性（仅支持 SD2. Hit ENTER and you should see it quickly update your files. We have merged the highly anticipated Diffusers pipeline, including support for the SD-XL model, into SD. Support for lowvram and medvram modes - Both work extremely well Additional tunables are available in UI -> Settings -> Diffuser Settings;Under windows it appears that enabling the --medvram (--optimized-turbo for other webuis) will increase the speed further. r/StableDiffusion. If I do a batch of 4, it's between 6 or 7 minutes. Medvram actually slows down image generation, by breaking up the necessary vram into smaller chunks. Then put them into a new folder named sdxl-vae-fp16-fix. 4 used and the rest free. . I've also got 12GB and with the introduction of SDXL, I've gone back and forth on that. And, I didn't bother with a clean install. 5. py in the stable-diffusion-webui folder. Safetensors on a 4090, there's a share memory issue that slows generation down using - - medvram fixes it (haven't tested it on this release yet may not be needed) If u want to run safetensors drop the base and refiner into the stable diffusion folder in models use diffuser backend and set sdxl pipelineRecommandé : SDXL 1. Try setting the "Upcast cross attention layer to float32" option in Settings > Stable Diffusion or using the --no-half commandline argument to fix this. AutoV2. The sd-webui-controlnet 1. I've been using this colab: nocrypt_colab_remastered. In. 0 base, vae, and refiner models. 576 pixels (1024x1024 or any other combination). I switched over to ComfyUI but have always kept A1111 updated hoping for performance boosts. With 12GB of VRAM you might consider adding --medvram. bat file. @weajus reported that --medvram-sdxl resolves the issue, however this is not due to the usage of the parameter, but due to the optimized way A1111 now manages system RAM, therefore not running into the issue 2) any longer. 6) with rx 6950 xt , with automatic1111/directml fork from lshqqytiger getting nice result without using any launch commands , only thing i changed is chosing the doggettx from optimization section . You should definitively try them out if you care about generation speed. SDXL 1. --force-enable-xformers：强制启动xformers，无论是否可以运行都不报错. Huge tip right here. 8~5. finally , AUTOMATIC1111 has fixed high VRAM issue in Pre-release version 1. 16GB VRAM can guarantee you comfortable 1024×1024 image generation using the SDXL model with the refiner. 7. I have the same issue, got an Arc A770 too so i guess the card is the problem. Also 1024x1024 at Batch Size 1 will use 6. Hey guys, I was trying SDXL 1. And when it does show it, it feels like the training data has been doctored, with all the nipple-less breasts and barbie crotches. A brand-new model called SDXL is now in the training phase. 0 base model. then select the section "Number of models to cache". So at the moment there is probably no way around --medvram if you're below 12GB. My hardware is Asus ROG Zephyrus G15 GA503RM with 40GB RAM DDR5. For a 12GB 3060, here's what I get. --full_bf16 option is added. For the actual training part, most of it is Huggingface's code, again, with some extra features for optimization. I don't know if you still need an answer, but I regularly output 512x768 in about 70 seconds with 1. OK, just downloaded the SDXL 1. ComfyUIでSDXLを動かす方法まとめ. 1. @weajus reported that --medvram-sdxl resolves the issue, however this is not due to the usage of the parameter, but due to the optimized way A1111 now manages system RAM, therefore not running into the issue 2) any longer. They have a built-in trained vae by madebyollin which fixes NaN infinity calculations running in fp16. Refiner same folder as Base model, although with refiner i can't go higher then 1024x1024 in img2img. Hello, I tried various LoRAs trained on SDXL 1. --medvram By default, the SD model is loaded entirely into VRAM, which can cause memory issues on systems with limited VRAM. If you’re unfamiliar with Stable Diffusion, here’s a brief overview:. 0. x and SD2. @SansQuartier temporary solution is remove --medvram (you can also remove --no-half-vae, it's not needed anymore). If your GPU card has less than 8 GB VRAM, use this instead. 0_0. Normally the SDXL models work fine using medvram option, taking around 2 it/s, but when i use Tensor RT profile for SDXL, it seems like the medvram option is not being used anymore as the iterations start taking several minutes as if the medvram. It was easy and dr. --xformers：启用xformers，加快图像的生成速度. Moved to Installation and SDXL. aiイラストで一般人から一番口を出される部分が指の崩壊でしたので、そのあたりの改善の見られる sdxl は今後主力になっていくことでしょう。 今後もAIイラストを最前線で楽しむ為にも、一度導入を検討されてみてはいかがでしょうか。My GTX 1660 Super was giving black screen. I've seen quite a few comments about people not being able to run stable diffusion XL 1. I have trained profiles using both medvram options enabled and disabled but the. Many of the new models are related to SDXL, with several models for Stable Diffusion 1. You can go here and look through what each command line option does. Effects not closely studied. tif, . For 8GB vram, the recommended cmd flag is "--medvram-sdxl". Horrible performance. You can make it at a smaller res and upscale in extras though. 5 min. Comfy is better at automating workflow, but not at anything else. 3 on 10: 35: 31-732037 INFO Running setup 10: 35: 31-770037 INFO Version: cf80857b Fri Apr 21 09: 59: 50 2023 -0400 10: 35: 32-113049 INFO Latest published. I am a beginner to ComfyUI and using SDXL 1. python launch. 5 model is that SDXL is much slower, and uses up more VRAM and RAM. 3s/it on an M1 mbp with 32gb ram, using invokeAI, for sdxl 1024x1024 with refiner. I have used Automatic1111 before with the --medvram. To start running SDXL on a 6GB VRAM system using Comfy UI, follow these steps: How to install and use ComfyUI - Stable Diffusion. (--opt-sdp-no-mem-attention --api --skip-install --no-half --medvram --disable-nan-check)RTX 4070 - have tried every variation of MEDVRAM , XFORMERS on and off and no change. For a few days life was good in my AI art world. Next with SDXL Model/ WindowsIf still not fixed, use command line arguments --precision full --no-half at a significant increase in VRAM usage, which may require --medvram. add --medvram-sdxl flag that only enables --medvram for SDXL models; prompt editing timeline has separate range for first pass and hires-fix pass (seed breaking change) Minor: img2img batch: RAM savings, VRAM savings, . 최근 스테이블 디퓨전이. set COMMANDLINE_ARGS= --medvram --autolaunch --no-half-vae PYTORCH_CUDA_ALLOC_CONF=garbage_collection_threshold:0. This is the same problem as the one from above, to verify, Use --disable-nan-check. Sigh, I thought this thread is about SDXL - forget about 1. 9 はライセンスにより商用利用とかが禁止されています. 4 - 18 secs SDXL 1. Beta Was this translation helpful? Give feedback. 5. (just putting this out here for documentation purposes) Reply reply. I've been trying to find the best settings for our servers and it seems that there are two accepted samplers that are recommended. Raw output, pure and simple TXT2IMG. You'd need to train a new SDXL model with far fewer parameters from scratch, but with the same shape. 9 through Python 3. Sdxl batch of 4 held steady at 18. When generating images it takes between 400-900 seconds to complete (1024x1024, 1 image with low VRAM due to having only 4GB) I read that adding --xformers --autolaunch --medvram inside of the webui-user. I can tell you that ComfyUI renders 1024x1024 in SDXL at faster speeds than A1111 does with hiresfix 2x (for SD 1. Pour Automatic1111,. The post just asked for the speed difference between having it on vs off. 5GB vram and swapping refiner too , use --medvram-sdxl flag when startingUsing (VAE Upcasting False) FP16 Fixed VAE with the config file will drop VRAM usage down to 9GB at 1024x1024 with Batch size 16. 0. 9, causing generator stops for minutes aleady add this line to the . We invite you to share some screenshots like this from your webui here: The “time taken” will show how much time you spend on generating an image. To enable higher-quality previews with TAESD, download the taesd_decoder. そこで今回はコマンドライン引数「xformers」を使って、Stable Diffusionの動作を高速化する方法について解説します。. @echo off set PYTHON= set GIT= set VENV_DIR= set COMMANDLINE_ARGS=--medvram-sdxl --xformers call webui. try --medvram or --lowvram Reply More posts you may like. old 1. add --medvram-sdxl flag that only enables --medvram for SDXL models prompt editing timeline has separate range for first pass and hires-fix pass (seed breaking change). I go from 9it/s to around 4s/it with 4-5s to generate an img. Myself, I've only tried to run SDXL in Invoke. 0. 0-RC , its taking only 7. Slowed mine down on W10. 5 stuff generates slowly, hires fix or not, medvram/lowvram flags or not. 0 base and refiner and two others to upscale to 2048px. Now everything works fine with SDXL and I have two installations of Automatic1111 each working on an intel arc a770. 5 min. 5. It still is a bit soft on some of the images, but I enjoy mixing and trying to get the checkpoint to do well on anything asked of it. Other users share their experiences and suggestions on how these arguments affect the speed, memory usage and quality of the output. tiff in img2img batch (#12120, #12514, #12515) postprocessing/extras: RAM savings It's not the medvram problem, I also have a 3060 12Gb, the GPU does not even require the medvram, but xformers is advisable. 5, but it struggles when using SDXL. Idk why a1111 si so slow and don't work, maybe something with "VAE", idk. Happy generating everybody!At the line where set " COMMANDLINE_ARGS =" , add in these parameters " --xformers" and " --medvram" and " --opt-split-attention" to reduce further the VRAM needed BUT it will added the processing time. Web. Reply reply more replies. If you want to switch back later just replace dev with master . that FHD target resolution is achievable on SD 1. Reddit just has a vocal minority of such people. 5 there is a lora for everything if prompts dont do it fast. Note that the Dev branch is not intended for production work and may. With 3060 12gb overclocked to the max takes 20 minutes to render 1920 x 1080 image. use --medvram-sdxl flag when starting. The company says SDXL produces more detailed imagery and composition than its predecessor Stable Diffusion 2. 0, just a week after the release of the SDXL testing version, v0. Well dang I guess. 5 model to refine. Also, as counterintuitive as it might seem, don't generate low resolution images, test it with 1024x1024 at least. there is no --highvram, if the optimizations are not used, it should run with the memory requirements the compvis repo needed. I run on an 8gb card with 16gb of ram and I see 800 seconds PLUS when doing 2k upscales with SDXL, wheras to do the same thing with 1. --medvram: None: False: Enable Stable Diffusion model optimizations for sacrificing a some performance for low VRAM usage. It's still around 40s to generate but that's a big difference from 40 minutes! The --no-half-vae option doesn't. If you have bad performance on both, take a look on the following tutorial (for your AMD gpu):So, all I effectively did was add in support for the second text encoder and tokenizer that comes with SDXL if that's the mode we're training in, and made all the same optimizations as I'm doing with the first one. FNSpd. refinerモデルを正式にサポートしている. Both GUIs do the same thing. Consumed 4/4 GB of graphics RAM. Reply. Reviewed On 7/1/2023. 9 (changed the loaded checkpoints to the 1. 24GB VRAM. #stability #stablediffusion #stablediffusionSDXL #artificialintelligence #dreamstudio The stable diffusion SDXL is now live at the official DreamStudio. 0 Version in Automatic1111 installiert und nutzen könnt. add --medvram-sdxl flag that only enables --medvram for SDXL models; prompt editing timeline has separate range for first pass and hires-fix pass (seed breaking change) Minor: img2img batch: RAM savings, VRAM savings, . In the hypernetworks folder, create another folder for you subject and name it accordingly. ここでは. Image by Jim Clyde Monge. Try the other one if the one you used didn’t work. safetensors at the end, for auto-detection when using the sdxl model. I updated to A1111 1. whl, change the name of the file in the command below if the name is different:set COMMANDLINE_ARGS=--medvram --opt-sdp-attention --no-half --precision full --disable-nan-check --autolaunch --skip-torch-cuda-test set SAFETENSORS_FAST_GPU=1. Currently, only running with the --opt-sdp-attention switch. Decreases performance. 1024x1024 instead of 512x512), use --medvram --opt-split-attention. 0: 6. Important lines for your issue. It's a much bigger model. A1111 is easier and gives you more control of the workflow. /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. CeFurkan • 9 mo. Note that the Dev branch is not intended for production work and may break other things that you are currently using. To save even more VRAM set the flag --medvram or even --lowvram (this slows everything but alows you to render larger images). The t2i ones run fine, though. 5gb. If it is the hi-res fix option, the second image subject repetition is definitely caused by a too high "Denoising strength" option. stable-diffusion-webui * old favorite, but development has almost halted, partial SDXL support, not recommended. There is also another argument that can help reduce CUDA memory errors, I used it when I had 8GB VRAM, you'll find these launch arguments at the github page of A1111. I have a weird config where I have both Vladmandic and A1111 installed and use the A1111 folder for everything, creating symbolic links for. with this --opt-sub-quad-attention --no-half --precision full --medvram --disable-nan-check --autolaunch I could have 800*600 with my 6600xt 8g, not sure if your 480 could make it. We highly appreciate your help if you can share a screenshot in this format: GPU (like RGX 4096, RTX 3080,. The. Afroman4peace. 1. 4: 1. What a move forward for the industry. Then, I'll change to a 1. 00 GiB total capacity; 2.