<h1 id="works-on-both-t2v-and-i2v"><span style="color:rgb(247, 217, 20)">Works on both T2V and I2V</span></h1><h1 id="this-is-just-a-simple-modified-version-of-the-official-comfyui-wan-2.2-5b-workflow.-i-just-added-the-gguf-model-loader-and-clear-vram-nodes-at-different-stages-of-the-generation-to-help-prevent-oom-on-machines-that-don't-have-a-lot-of-vram.-using-a-q8-quant-of-wan-2.2-5b-generating-at-704x1024-33-frames-peaks-at-11.8gb-of-vram.-if-you-have-a-lower-end-machine-reduce-the-quant-level-to-a-q5-or-q4-quant.-quantstack-has-some-quants-of-wan-2.2-5b-on-their-huggingface."><span style="color:rgb(64, 192, 87)">This is just a simple modified version of the official ComfyUI Wan 2.2 5B workflow. I just added the GGUF model loader and clear VRAM nodes at different stages of the generation to help prevent OOM on machines that don't have a lot of VRAM. Using a Q8 quant of Wan 2.2 5b, generating at 704x1024 33 frames peaks at 11.8gb of VRAM. If you have a lower-end machine, reduce the quant level to a Q5 or Q4 quant. Quantstack has some quants of Wan 2.2 5B on their huggingface.</span></h1><p></p>

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