⚡ Quick Answer
Character consistency is the challenge of keeping the same character's face and features recognizable across multiple generated images, since a diffusion model normally reinterprets a character slightly differently every single time it generates. Several techniques exist to solve this.
Without any of these techniques, prompting "the same woman from before" gives you a different-looking woman almost every time — the model has no actual memory of what it generated last.
Where You'll See It
The most common no-training method is an IP-Adapter node, fed a reference photo alongside your normal prompt. A heavier but more reliable option is training a LoRA specifically on that character beforehand.
Quick Example
Feeding an IP-Adapter node a reference photo of a specific face, then generating a batch of images in different outfits and settings, keeps that same face recognizable across every result in the batch.
Frequently Asked Questions
See It In Action
Want the same face every time?
Our guide compares the main character consistency methods side by side.
Published: 2026-09-17 · Last updated: 2026-09-17
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