Memory Optimization With Attention Slicing Vae Tiling And Gradient Checkpointing

via “vae (variational autoencoder) swapping and optimization”

Stable Diffusion web UI

Unique: Implements VAE swapping without full checkpoint reload, supporting multiple VAE variants (standard, MSE, EMA) with automatic caching. Includes VAE-specific optimizations: tiling for large images (avoids VRAM overflow) and sliced attention for memory efficiency. Supports both standard VAEs and specialized variants trained for specific domains.

vs others: More flexible than single-VAE models (swap variants without reloading) and more memory-efficient than naive tiling (optimized kernel implementations)