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This release focuses on critical memory optimizations for large model workflows, particularly improving performance with WAN 2.2 models and enhancing VRAM management for high-end systems:
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## WAN 2.2 Model Optimizations
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-**Reduced Memory Footprint**: Eliminated unnecessary memory clones in WAN 2.2 VAE operations, significantly reducing memory usage during image encoding/decoding workflows
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-**5B I2V Model Support**: Major memory optimization for WAN 2.2 5B image-to-video models, making these large-scale models more accessible for creators with limited VRAM
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## Enhanced VRAM Management
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-**Windows Large Card Support**: Added extra reserved VRAM allocation for high-end graphics cards on Windows, preventing system instability during intensive generation workflows
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-**Better Memory Allocation**: Improved memory management for users working with multiple large models simultaneously
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## Workflow Performance Benefits
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-**Faster VAE Processing**: WAN 2.2 VAE operations now run more efficiently with reduced memory overhead, enabling smoother image generation pipelines
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-**Stable Large Model Inference**: Enhanced stability when working with billion-parameter models, crucial for professional AI art creation and research workflows
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-**Improved Batch Processing**: Memory optimizations enable better handling of batch operations with large models
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These targeted optimizations make ComfyUI more reliable for professional workflows involving large-scale models, particularly benefiting creators working with cutting-edge image-to-video generation and high-resolution image processing tasks.
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These improvements make ComfyUI more robust for production workflows while expanding creative possibilities for AI artists working with advanced sampling techniques and model control systems.
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