# What is SwiGLU? Definition & Technical Mechanics

> **Source:** [SPIDITS AI AI Glossary](https://spidits.com/ai-glossary)  
> **Category:** Neural Architectures  
> **Canonical Citation:** [https://spidits.com/ai-glossary/swiglu](https://spidits.com/ai-glossary/swiglu)

## Definition
SwiGLU is an activation function combining the Gated Linear Unit with Swish activation, used in feed-forward networks of modern Transformer blocks.

## Architectural Mechanics & Deep Dive
SwiGLU (Swish Gated Linear Unit) is a neural network activation function commonly used in modern LLMs (like Llama). It combines Swish and Gated Linear Unit math to construct a smooth gating activation. SwiGLU has been shown to deliver significantly better training convergence and model accuracy compared to traditional activations.

## Industry Applications & Real-World Use Cases
Transformer performance optimization, model training.

## Frequently Asked Questions

### Why use SwiGLU over ReLU or GELU?
SwiGLU consistently improves model perplexity and evaluation scores.

### What is its main cost?
It increases parameter size and computational cost slightly by adding gate layers.

## Related Terminology
- [activation-function](https://spidits.com/ai-glossary/activation-function)
- [transformer](https://spidits.com/ai-glossary/transformer)
- [llama](https://spidits.com/ai-glossary/llama)

---
*From the SPIDITS AI Knowledge Base (336+ terms indexed). Explore full technical definitions: [https://spidits.com/ai-glossary](https://spidits.com/ai-glossary)*