It finally happened!
Now there's a way for smoother continuous videos thanks to SVI team and Kijai.

We are at v1.0!

I've updated the workflow to add a few more features;

• Video extend option by loading an initial video then converting it to latent that goes into first I2V (WIP)

• Option to switch between 3 and 2 ksampler phases by setting the initial step

• Option to set cfg > 1 if you wanted to disable lightx2v

• Images are saved partially in loseless format (use something like VLC to view them) and only loaded again on final merge, if something goes wrong you can merge those files to get a flowing video.

• Implemented a bus system to reduce connections. Report if you have any issues but things should work as long as you have the right models and loras selected.

• You can set and fix the seed for each part

• There are options to upscale and interpolate before final save

• Final save happens on main graph so you can preview your output

Slow motion issue probably persists. Couldnt find a consistent solution since when speed up using a third party tool every part becomes faster since they take previous latents as input until everything breaks.

Weak points of most SVI workflows right now is that it references first image in all parts so you might have background warping/chaning shape/textures on switches if the background has changed a lot.

I'll only be updating the workflow if kijai updates the node (there are two merge requests about end frame and better consistency(?)) and/or something breaks. So we can call this a semi final :)

Comfyui compatible SVI lora's;

https://huggingface.co/Kijai/WanVideo_comfy/blob/main/LoRAs/Stable-Video-Infinity/v2.0/SVI_v2_PRO_Wan2.2-I2V-A14B_HIGH_lora_rank_128_fp16.safetensors

https://huggingface.co/Kijai/WanVideo_comfy/blob/main/LoRAs/Stable-Video-Infinity/v2.0/SVI_v2_PRO_Wan2.2-I2V-A14B_LOW_lora_rank_128_fp16.safetensors

LightX2V lora's I'm using;

https://huggingface.co/Kijai/WanVideo_comfy/blob/main/LoRAs/Wan22_Lightx2v/Wan_2_2_I2V_A14B_HIGH_lightx2v_MoE_distill_lora_rank_64_bf16.safetensors

https://huggingface.co/Kijai/WanVideo_comfy/blob/main/LoRAs/Wan22-Lightning/old/Wan2.2-Lightning_I2V-A14B-4steps-lora_LOW_fp16.safetensors

FP32 vae:

https://huggingface.co/calcuis/wan-gguf/blob/ff59c62b6a008bc99677228596e096130066b234/wan_2.1_vae_fp32.safetensors

Ultra Flux VAE for sharper !"Z Image"! outputs:

https://huggingface.co/Owen777/UltraFlux-v1/blob/main/vae/diffusion_pytorch_model.safetensors

GGUF still seems to be performing better than fp8 scaled in my experience.

Just share your outputs with us folks as well :)

v0.9

Left sampling on (1 + 3 + 3) steps with 4 parts (19s~). Takes around 10mins on my 4070ti with sage + torch compile. Feel free to extend it further if you need.

Everything is GGUF. Patch sage attention and torch compile are disabled by default but you are welcome to enable them back since they speed things up a lot if you have the environment set up.

You can set part specific or common lora's thanks to rgthree power lora node.

Happy generations! \('-')