Online Workflow: Wan2.2-Remix-I2V-Comfy-Qwen3
Experience here: https://www.runninghub.ai/post/1986632318448267265/?inviteCode=rh-v1325

Online Workflow: Wan2.2-Remix-T2V-v2.0 text-to-video workflow
Experience here: https://www.runninghub.ai/post/1991533843182264322/?inviteCode=rh-v1325

Wan2.2-Remix is a research and creative model built to generate short, cinematic video clips directly from text prompts. It focuses on human dynamics, realistic motion, and scene consistency, producing lifelike movement and smooth transitions without requiring LoRA setup.

This model already includes NSFW capabilities, enabling the generation of high-quality NSFW-themed videos without the need for additional LoRA.

• High-noise model T2V: Lightx2v Wan2.2 Lightning dyno version (quantized to fp8)
• High-noise model I2V: Comfy-Org Wan 2.2 ComfyUI Repackaged (fp16, quantized to fp8)
• Low-noise model: Comfy-Org Wan 2.2 ComfyUI Repackaged (quantized to fp8)
• Enhancements: Blended with open-source motion LoRA data and refined pose training for enhanced realism, anatomical precision, and gesture diversity.
• Integration: Fully compatible with lightx2v, no extra setup required.
• Recommended CLIP: NSFW-Wan-UMT5-XXL

This model is currently in beta. It’s functional and improving—feedback is welcome!

• Optimized character stability in generated videos, reducing jitter and unwanted motion artifacts
• Enhanced video detail for more visually rich scenes
• Added dynamic motion effects to improve realism and cinematic impact
• Updated base model to original Wan2.2 version to minimize differences across random seeds

• Significantly enhanced character motion and poses for more dynamic animations
• Greatly improved camera movement and cinematic framing
• Optimized NSFW content weighting to reduce jitter in generated videos when producing SFW scenes
• Enhanced explosions and particle effects for more impactful visuals
• SFW version will no longer receive updates

• Updated lighting acceleration module to Wan2.1 version, fixing slow-motion character issues
• Integrated over 20 open-source LoRAs and 10 custom-trained LoRAs to enhance motion dynamics
• Removed several low-quality LoRAs to improve overall visual fidelity

• Enhanced walking, dancing, and running movements
• Improved overall motion coherence
• Introduced gesture-rich motion set

• Reduced dyno weighting to improve stability across different random seeds
• Added more Asian facial datasets for greater diversity
• Enhanced character motion dynamics for fluid animation
• Improved motion amplitude, gesture diversity, and overall visual quality

• High-noise T2V model: Lightx2v Wan2.2 Lightning dyno version (fp8)
• High-noise I2V model: Comfy-Org Wan 2.2 ComfyUI Repackaged (fp16, fp8 quantized)
• Low-noise model: Comfy-Org Wan 2.2 ComfyUI Repackaged
• Refined character motion blending for smoother transitions
• Enhanced anatomical articulation and natural body flow