# LoRA stacking

**Source:** https://promtable.com/glossary/lora-stacking

> LoRA stacking applies multiple LoRA adapters simultaneously to a diffusion model — combining a character LoRA, a style LoRA, and a quality LoRA — to compose effects without retraining.

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LoRA stacking applies multiple LoRA adapters simultaneously to a diffusion model — combining a character LoRA, a style LoRA, and a quality LoRA — to compose effects without retraining.

LoRA stacking is the production technique for combining trained character / style / detail LoRAs in Stable Diffusion and Flux pipelines. Each LoRA gets a strength weight (0-2 typically) and the model applies them in series. Stacking lets you compose effects that no single LoRA produced: character X + 1980s-anime style + detail enhancement. Limits: combining 5+ LoRAs starts producing artefacts as the adapters interact. Best practice in 2026: train LoRAs at low rank, use moderate strength weights (0.4-0.8), and test combinations explicitly.

## When to use

- Composing character + style + detail effects in SD or Flux.
- Brand-consistent generation with multiple controlled features.

## Common mistakes

- Stacking too many LoRAs — artefacts compound.
- Using uniform strength — different LoRAs need different weights.

## Related terms

- [lora](https://promtable.com/glossary/lora)
- [controlnet](https://promtable.com/glossary/controlnet)
- [diffusion-model](https://promtable.com/glossary/diffusion-model)

*Last updated: 2026-06-01*
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Original page: https://promtable.com/glossary/lora-stacking
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