⚡ Quick Answer
CLIP is a text encoder model that reads your prompt and converts it into a numerical representation called conditioning — the format the sampler actually understands. Without CLIP, your typed words never reach the image-generation process at all.
Stable Diffusion and Flux-family models can't read English directly. CLIP (Contrastive Language-Image Pretraining) was trained to map text and images into the same mathematical space, so a phrase like "a red bicycle" produces a vector the checkpoint was trained to associate with red bicycles.
Where You'll See It
On SD1.5 and SDXL checkpoints, Load Checkpoint already outputs a CLIP connection alongside MODEL and VAE — nothing extra to load. On Flux and other split-architecture models, a DualCLIPLoader or CLIPLoader node loads the CLIP files separately, and its output feeds directly into CLIP Text Encode (Prompt), which is where you actually type your prompt text.
Quick Example
A Flux workflow commonly loads clip_l.safetensors together with t5xxl_fp8_e4m3fn.safetensors through a DualCLIPLoader node set to type flux. CLIP-L handles short, style-driven phrasing, while the much larger T5XXL model handles longer, more literal instructions in the same prompt.
Common Mix-Up
Frequently Asked Questions
See It In Action
Ready to see CLIP at work?
Our interface overview walks through every core node, including where CLIP sits in the graph.
Published: 2026-09-04 · Last updated: 2026-09-04
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