ComfyUI의 Empty Latent Image 노드

Q: Error: height and width must be divisible by 8

A size like 1000x700 was entered. Use multiples of 8, ideally 64 (1024, 960, 896, 832, 768).

Q: Out of memory with a batch

batch_size multiplies the memory the sampler needs. Lower batch_size and queue several runs instead.

Empty Latent Image creates the blank latent canvas (width, height, batch_size) that text-to-image sampling starts from; dimensions must be multiples of 8 and match the model family.

노드 팩: ComfyUI core

카테고리: 잠재 공간

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Empty Latent Image이(가) 하는 일

Text-to-image needs a starting point. Empty Latent Image produces a latent tensor filled with zeros at the requested size, and KSampler adds the noise. Latent space is 8 times smaller than pixels for SD models, so a 1024x1024 image is a 128x128 latent; the node takes pixel sizes and divides for you.

Pick sizes the model was trained on: 512x512 or 512x768 for SD 1.5, 1024x1024 / 832x1216 / 1216x832 for SDXL, Pony and Illustrious. Larger first-pass sizes cause duplicated subjects; use a hires pass for more pixels. For Flux, SD3 and video models use EmptySD3LatentImage or the family-specific latent node, which has a different channel count.

입력

이름	타입	의미
width	INT	Image width in pixels, multiple of 8 (64 recommended).
height	INT	Image height in pixels, multiple of 8.
batch_size	INT	How many images to make in one run with consecutive seeds.

출력

이름	타입	의미
LATENT	LATENT	The empty latent for KSampler latent_image.

설치는 건너뛰세요: 클라우드에 미리 설치된 ComfyUI 워크플로

BitVector는 완성된 ComfyUI 워크플로를 자체 GPU에서 실행합니다. 설치 없음, 누락 노드 없음, 빨간 박스 없음. 휴대폰이나 노트북에서 열고 1분 안에 생성하세요.

BitVector 사용해 보기

Empty Latent Image 사용법

Add Empty Latent Image.
Set width and height for the model family (1024x1024 for SDXL).
Set batch_size 1 while testing, higher once the prompt works.
Connect LATENT to KSampler latent_image and keep denoise at 1.0.

설정과 팁

SDXL sweet spots: 1024x1024, 896x1152, 832x1216, 1152x896, 1216x832, 1344x768.
SD 1.5 above 768 on the long side tends to double heads and bodies; upscale afterwards instead.
batch_size 4 is a cheap way to explore seeds; VRAM scales with it.
Width and height that are not multiples of 8 are rounded down.