No more OOM errors here with 16gbvram. Use this workflow as a reference to incorporate these optimization nodes to your own workflow or use it yourself if you really want to.I modified <a target="_blank" rel="ugc" href="https://civarchive.com/user/definitelynotadog">definitelynotadog</a>'s version 1 workflow to optimize for 16gbvram (I'm sure lower can work too) so shoutout to him for making the main thing - <a target="_blank" rel="ugc" href="https://civarchive.com/models/1622023?modelVersionId=1835720">https://civarchive.com/models/1622023?modelVersionId=1835720</a>I added SageAttention, BlockSwap and TeaCache nodes. Around 3 minutes using the 480p GGUF model. Around 6 minutes using 720p GGUF. Feel free to yoink the optimization nodes I added and add it to his V2 workflow or to your own workflow even.Firstly, Download a GGUF version of Wan2.1 model of your choice for better performance. higher the Q number = higher quality. I personally went with Q3 bc it is faster than Q8 and the difference in quality was very minimal from what I could tell.LoRa Accelerators: The Causvid LORA is replaceable with FusionX or LightX lora because it's built-in apparently so choose one or the other. SelfForcing - <a target="_blank" rel="ugc" href="https://civarchive.com/models/1713337/wan-self-forcing-rank-16-accelerator">https://civarchive.com/models/1713337/wan-self-forcing-rank-16-accelerator</a>FusionX - <a target="_blank" rel="ugc" href="https://civarchive.com/models/1678575/wan21fusionx-the-lora">https://civarchive.com/models/1678575/wan21fusionx-the-lora</a>CausVid - <a target="_blank" rel="ugc" href="https://civarchive.com/models/1585622/self-forcing-causvid-accvid-lora-massive-speed-up-for-wan21-made-by-kijai">https://civarchive.com/models/1585622/self-forcing-causvid-accvid-lora-massive-speed-up-for-wan21-made-by-kijai</a>Models: Here are I2V 720p gguf models - <a target="_blank" rel="ugc" href="https://huggingface.co/city96/Wan2.1-I2V-14B-720P-gguf/tree/main">https://huggingface.co/city96/Wan2.1-I2V-14B-720P-gguf/tree/main</a>I2V 480p gguf models model - <a target="_blank" rel="ugc" href="https://huggingface.co/city96/Wan2.1-I2V-14B-480P-gguf/tree/main">https://huggingface.co/city96/Wan2.1-I2V-14B-480P-gguf/tree/main</a>Make sure to also download the missing VAE, clip vision, and clip<a target="_blank" rel="ugc" href="https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/blob/main/split_files/vae/wan_2.1_vae.safetensors">https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/blob/main/split_files/vae/wan_2.1_vae.safetensors</a><a target="_blank" rel="ugc" href="https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/blob/main/split_files/clip_vision/clip_vision_h.safetensors">https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/blob/main/split_files/clip_vision/clip_vision_h.safetensors</a><a target="_blank" rel="ugc" href="https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/blob/main/split_files/text_encoders/umt5_xxl_fp8_e4m3fn_scaled.safetensors">https://huggingface.co/Comfy-Org/Wan_2.1_ComfyUI_repackaged/blob/main/split_files/text_encoders/umt5_xxl_fp8_e4m3fn_scaled.safetensors</a> Make sure you have Custom Manager to install Custom Nodes and dependencies but this specific one you might have to install manually: <a target="_blank" rel="ugc" href="https://github.com/city96/ComfyUI-GGUF">https://github.com/city96/ComfyUI-GGUF</a>Settings:Make sure you're running 4-10 steps when using fusionx lora or causvid lora, stick to 16fps, 81 length max. 7 steps is the sweet spot for me, anything below I get a lot of artifacts/glitches. 848 for 480p and 1280 for 720pOPTIMIZATIONS:Sage gives ~25% more speed. If you don't have SageAttention installed on your system. Here's a guide for sage on windows, you might bork your comfyui if done incorrectly: <a target="_blank" rel="ugc" href="https://www.reddit.com/r/StableDiffusion/comments/1h7hunp/how_to_run_hunyuanvideo_on_a_single_24gb_vram_card/">https://www.reddit.com/r/StableDiffusion/comments/1h7hunp/how_to_run_hunyuanvideo_on_a_single_24gb_vram_card/</a>BlockSwap Node, it offloads VRAM to system RAM (NO MORE OOM ERRORS)Set to 40 for 14B model, 30 for 1.3B model. Look at vram usage while generating to find the sweetspot; the higher the blocks, the less vram usage. Keep in mind resolution effects VRAM by a lot.TeaCache Node gives 2X speed but at the cost of QUALITY. If video is too fuzzy or you are missing limbs, set the thres lower to 0.140 or feel free to bypass/delete this node if you don't like the results. I'm still tweaking it to find the best settings for it.I'm still new to these nodes so feel free provide any useful info you may know to help others.

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