How much faster is comfyui a1111 github. - a1111-sd-webui-dtg_comfyui/README.
- How much faster is comfyui a1111 github Can someone help to make a1111 as fast as invoke?. ComfyUI also uses xformers by default, which is non-deterministic. I can get ~14 it/s with my 3060 (512x512) using AITemplate compared to ~8 in A1111; ComfyUI is almost twice as fast as A1111 at small gens. Saved searches Use saved searches to filter your results more quickly #Rename this to extra_model_paths. In ComfyUI, Automatic1111 WebUI is terrific for simple image generation, retouching images (inpainting), and basic controls. 35 it. I will give it a try ;) EDIT : got a bunch of errors at start. It should be at least as fast as the a1111 ui if you do that. But my findings are: ComfyUI nodes for the roop extension originally for a1111 stable-diffusion-webui - usaking12/ComfyUI_roop In ComfyUI, images saved through the Save Image or Preview Image nodes embed the entire workflow. 9 it vs 5. The image generation metadata created by ComfyUI cannot be expressed in a simple format like A1111's metadata, which only includes basic information such as positive prompts, I hypothesize this can impact SATA SSD's along with people pulling checkpoints across a LAN connection. Custom nodes for Aesthetic, Anime,, Fantasy, Gothic, Line art, Movie posters, Punk and Travel poster art styles for use with Automatic 1111 - ubohex/ComfyUI-Styles-A1111 Hmmm. g. Mmmh, I will wait for comfyui to get the proper update to unvail the "x2" boost. On the other hand, ComfyUI is more performant and Automatic1111 works way slower than Forge and ComfyUI on Linux Ubuntu A6000 GPU This doesn't make sense to me. 30it/s with these settings: 512x512, Euler a, 100 steps, 15 cfg and ComfyUI with the same settings is only 9. At present, the main problem of ComfyUI-Model-Manager is that it takes a lot of time to calculate the hash value of the model. On my 12GB 3060, A1111 can't generate a single SDXL 1024x1024 image without using RAM for VRAM at some point near the end of generation, even with --medvram set. The moment you add a LoRA, A1111 takes a good while to start to do inference. CUI is also faster. 63 it vs 4. ComfyUI's slow checkpoint I have a custom workflow that uses AITemplate and on-demand upscaling with the tile controlnet; it's so much better than A1111 that I don't really have a reason to use A1111 anymore. py for generating the required workflow block because it'd be extremely tedious to create the workflow manually. I don't understand the part that need some "export default engine" part. CUI can do a batch of 4 and stay within the 12 GB. 70it/s. for me its the The big current advantage of ComfyUI over Automatic1111 is it appears to handle VRAM much better. Here more info Saved searches Use saved searches to filter your results more quickly Saved searches Use saved searches to filter your results more quickly I tried implementing a1111's kdiffusion samplers in diffusers along with the ability to pass user changable settings from a1111 to kdiffusion. Test were done with batch = 1, IIRC on older pytorch it was possible to fit more in one batch to Fast and Simple Face Swap Extension for StableDiffusion WebUI (A1111, SD. However, the focus should be on improving completeness in terms of node-based UX rather than steering towards a direction similar to A1111. It’s more beginner-friendly. I am open every suggestion to experiment and test The weights are also interpreted differently. Do note that I don't have much experience in this field, it's just something I got into for fun the last month or two. But the performance between a1111 and ComfyUI is similar, given you select the same optimization and have proper environment. The more complex the workflows get (e. For now it seems that nvidia foooocus(ed) (lol, yeah pun intended) on A1111 for this extension. ComfyUI support; Mac M1/M2 support; Console log level control; NSFW filter free (this extension is aimed at highly developed intellectual people, ComfyUI-Book-Tools Nodes for ComfyUI: ComfyUI-Book-Tools is a set o new nodes for ComfyUI that allows users to easily add text overlays to images within their ComfyUI projects. guidance_factor : Mix factor used on guidance steps. This is from the discussions here: #853 (reply in thread) and here: city96/SD-Advanced-Noise#1if @Extraltodeus and @city96 want to continue. ComfyUI and Forge are default installations Forge doesn't even have xFormers enabled System has CUDA 11. multiple LoRas, negative prompting, upscaling), the For instance (word:1. In this case during generation vram memory doesn't flow to shared memory. This Node leverages Python Imaging Library (PIL) and PyTorch to dynamically render text on images, supporting a wide range of customization options including font size, alignment, color, and I really love comfyui. A1111 generates an image with the same settings (in spoilers) in 41 seconds, and Saved searches Use saved searches to filter your results more quickly The big current advantage of ComfyUI over Automatic1111 is it appears to handle VRAM much better. 1. Actual Behavior However, it is not able to read the workflow data from a web The Fast and Simple FaceSwap Extension with a lot of improvements and without NSFW filter (uncensored, use it on your own responsibility) Ex "Roop-GE" (GE - Gourieff Edition, aka "NSFW-Roop"), the extension was renamed with the version 0. Two new ComfyUI nodes: CLIPTextEncodeA1111 : A variant of CLIPTextEncode that converts A1111-like prompt into standard prompt Fast and Simple Face Swap Extension for StableDiffusion WebUI (A1111 SD WebUI, SD WebUI Forge, SD. 1) in A1111. 3. Anyways, really thanks for all your work on Forge. 2) and just gives weird results. Personally I recommend setting this to latent . Try using an fp16 model config in the CheckpointLoader node. The A1111 uses less steps proportional to the denoising, that is why it is faster with less denoising, there is a configuration in A1111 that disables it, to have the same in ComfyUI just use less steps. Comfyui has this standalone beta build which runs on python 3. A sd-webui extension for utilizing DanTagGen to "upsample prompts". Fresh install - default settings. Next, Cagliostro) - roniejisa/sd-webui-reactor ComfyUI support; Mac M1/M2 support; Console log level control; NSFW filter free (this extension is invokeai is 2 times faster then a1111 when i generate images. . And if you include all the time invested in dealing with the interface, then A1111 is an order of magnitude faster. I find that much faster. Next, Cagliostro) - nutrisuri/sd-webui-reactor ComfyUI support; Mac M1/M2 support; Console log level control; NSFW filter free (this extension is The Dev branch of A1111 is faster than Comfy on my PC, but I have 64 GB of RAM and a 4900 with 24 GB of VRAM. A1111 gives me 10. Expected Behavior When using an image generated from A1111/forge/reforge, comfyUI has the ability to interpret the metadata into a basic workflow automatically. - a1111-sd-webui-dtg_comfyui/README. For instance, tasks that take several minutes in A1111 can often be What is ComfyUI? ComfyUI has become one of the fastest growing open-source web UIs for Stable Diffusion. Then it's the same or faster. It also seems like ComfyUI is way too intense on using heavier weights on (words:1. I think the noise is also generated differently where A1111 uses GPU by default and ComfyUI uses CPU by default, which makes using the same seed give Enhanced Performance: Many users report significantly faster image generation times with ComfyUI. I think the noise is also generated differently where A1111 uses GPU by default and ComfyUI uses CPU by Much faster than either this or cdboops fork. md at main · toyxyz/a1111-sd-webui-dtg_comfyui And it's 2. Saved searches Use saved searches to filter your results more quickly Saved searches Use saved searches to filter your results more quickly Fast and Simple Face Swap Extension for StableDiffusion WebUI (A1111 SD WebUI, SD WebUI Forge, SD. ComfyUI nodes for the roop extension originally for a1111 stable-diffusion-webui - nicofdga/ComfyUI_faceswapper I compared forge vs A1111 on the dev branch, and A1111 seems to be generally faster on SDXL on a RTX 4090, BUT without using loras. Next, Cagliostro) - titusfx/sd-webui-reactor. On my 12GB 3060, A1111 can't generate a single SDXL 1024x1024 image without I consistently get much better results with Automatic1111's webUI compared to ComfyUI even for seemingly identical workflows. 8. Therefore, you can load a workflow by dragging and dropping the image into ComfyUI. I took a closer look at the repo a1111-civitai-browser-plus and found that it is indeed great, but it may not be what I want. I no longer use automatic unless I want to play around with Temporal kit. I give up. On my machine, comfy is only marginally faster than 1111. I have no idea what runs under the hood which makes it ComfyUI uses the CPU for seeding, A1111 uses the GPU. If it isn't let me know because it's something I need Comfy is basically a backend with very light frontend, while A1111 is very heavy frontend. ComfyUI was created in Jan 2023 and has positioned itself as a more powerful and flexible version of A1111. So from that aspect, they'll never give the same results unless you set A1111 to use the CPU for the seed. 0 In web-ui, go to the "Extensions" tab and use this URL easy fullLoader and easy a1111Loader have added a new parameter a1111_prompt_style,that can reproduce the same image generated from stable-diffusion-webui on comfyui, but you need to install ComfyUI_smZNodes to use this feature in the current version Automatic1111 vs Forge vs ComfyUI on our Massed Compute VM image - 3. Guys, I hope you have something. My limit of resolution with controlnet is The script comfyui_a1111_prompt_array_generator. Not sure what is happening on that side. 5 to 3 times faster than automatic1111. 0 means use 100% DiffuseHigh guidance for those steps (like the original implementation). Only xformers command line argument is used. That makes no sense. 11. The UX that conceals nodes and complex workflows, exposing only functionalities, is already being worked on in a much better direction by 3rd party front ends. It works on latest stable relese without extra nodes like this: comfyUI impact pack / efficiency-nodes-comfyui / tinyterraNodes. Soapbox mode: Ever since SSDs went mainstream 12-15 years ago I've feared coders would generally stop caring about efficient storage I/O given that devices with sub-millisecond latency can cover for an enormous number of sins. For instance (word:1. yaml and ComfyUI will load it #config for a1111 ui #all you have to do is change the base_path to where yours is installed a111: base_path: path/to/stable-diffusion-webui/ checkpoints: models/Stable-diffusion configs: models/Stable-diffusion vae: models/VAE loras: | models/Lora models/LyCORIS upscale Alternatively, you can try using guidance via the latent instead which is much faster. That should speed things up a bit on newer cards. 1) in ComfyUI is much stronger than (word:1. No other command line arguments. Couldn't make it work for the SDXL Base+Refiner flow. wtrka qftkcs irhh mklww wrocf ysngiy dco zoce kuan yjnrkw