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## TT VAE Decode (Tiled) *TT_VaeDecodeTiled*
*This description was generated with AI assistance. If you spot any errors, please create an issue on GitHub.*
Tiled VAE decoder for processing large images without running out of VRAM.
### Inputs
| Parameter | Type | Required | Description |
|---------------|---------|----------|---------------------------------------------------------------------|
| `vae` | VAE | Yes | VAE model for decoding |
| `latent` | LATENT | Yes | Latent image to decode |
| `tile_width` | INT | Yes | Width of each tile in pixels (320-4096, step: 64, default: 512) |
| `tile_height` | INT | Yes | Height of each tile in pixels (320-4096, step: 64, default: 512) |
| `overlap` | INT | Yes | Overlap between tiles to reduce seams (0-256, step: 8, default: 64) |
| `circular` | BOOLEAN | Yes | Enable circular padding for seamless tiling (default: False) |
### Outputs
| Parameter | Type | Description |
|-----------|-------|----------------------|
| `IMAGE` | IMAGE | Decoded image tensor |
### Usage
Decode large latent images by processing them in smaller tiles. Useful for generating high-resolution images that would
otherwise exceed VRAM capacity. The overlap parameter helps reduce visible seams between tiles. Enable circular padding
for seamless texture generation.
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[View on GitHub](https://github.com/tenser-tensor/ComfyUI-TenserTensor)