> ## Documentation Index
> Fetch the complete documentation index at: https://docs.sglang.io/llms.txt
> Use this file to discover all available pages before exploring further.

# Caching Acceleration

> Compare caching acceleration strategies for diffusion models.

SGLang provides two complementary caching strategies for Diffusion Transformer (DiT) models. Both reduce denoising cost by skipping redundant computation, but they operate at different levels.

## Overview

SGLang supports two complementary caching approaches:

<table style={{width: "100%", borderCollapse: "collapse", tableLayout: "fixed"}}>
  <colgroup>
    <col style={{width: "18%"}} />

    <col style={{width: "18%"}} />

    <col style={{width: "42%"}} />

    <col style={{width: "22%"}} />
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  <thead>
    <tr style={{borderBottom: "2px solid #d55816"}}>
      <th style={{textAlign: "left", padding: "10px 12px", fontWeight: 700, whiteSpace: "nowrap", backgroundColor: "rgba(255,255,255,0.02)"}}>Strategy</th>
      <th style={{textAlign: "left", padding: "10px 12px", fontWeight: 700, whiteSpace: "nowrap", backgroundColor: "rgba(255,255,255,0.05)"}}>Scope</th>
      <th style={{textAlign: "left", padding: "10px 12px", fontWeight: 700, whiteSpace: "nowrap", backgroundColor: "rgba(255,255,255,0.02)"}}>Mechanism</th>
      <th style={{textAlign: "left", padding: "10px 12px", fontWeight: 700, whiteSpace: "nowrap", backgroundColor: "rgba(255,255,255,0.05)"}}>Best For</th>
    </tr>
  </thead>

  <tbody>
    <tr>
      <td style={{padding: "9px 12px", fontWeight: 500, backgroundColor: "rgba(255,255,255,0.02)"}}>Cache-DiT</td>
      <td style={{padding: "9px 12px", backgroundColor: "rgba(255,255,255,0.05)"}}>Block-level</td>
      <td style={{padding: "9px 12px", backgroundColor: "rgba(255,255,255,0.02)"}}>Skip individual transformer blocks dynamically</td>
      <td style={{padding: "9px 12px", backgroundColor: "rgba(255,255,255,0.05)"}}>Advanced, higher speedup</td>
    </tr>

    <tr>
      <td style={{padding: "9px 12px", fontWeight: 500, backgroundColor: "rgba(255,255,255,0.02)"}}>TeaCache</td>
      <td style={{padding: "9px 12px", backgroundColor: "rgba(255,255,255,0.05)"}}>Timestep-level</td>
      <td style={{padding: "9px 12px", backgroundColor: "rgba(255,255,255,0.02)"}}>Skip entire denoising steps based on L1 similarity</td>
      <td style={{padding: "9px 12px", backgroundColor: "rgba(255,255,255,0.05)"}}>Simple, built-in</td>
    </tr>
  </tbody>
</table>

## Cache-DiT

[Cache-DiT](https://github.com/vipshop/cache-dit) provides block-level caching with
advanced strategies like DBCache and TaylorSeer. It can achieve up to **1.69x speedup**.

See [cache\_dit.md](./cache_dit) for detailed configuration.

### Quick Start

```bash theme={null}
SGLANG_CACHE_DIT_ENABLED=true \
sglang generate --model-path Qwen/Qwen-Image \
    --prompt "A beautiful sunset over the mountains"
```

### Key Features

* **DBCache**: Dynamic block-level caching based on residual differences
* **TaylorSeer**: Taylor expansion-based calibration for optimized caching
* **SCM**: Step-level computation masking for additional speedup

## TeaCache

TeaCache (Temporal similarity-based caching) accelerates diffusion inference by detecting when consecutive denoising steps are similar enough to skip computation entirely.

See [teacache.md](./teacache) for detailed documentation.

### Quick Overview

* Tracks L1 distance between modulated inputs across timesteps
* When accumulated distance is below threshold, reuses cached residual
* Supports CFG with separate positive/negative caches

### Supported Models

* Wan (wan2.1, wan2.2)
* Hunyuan (HunyuanVideo)
* Z-Image

For Flux and Qwen models, TeaCache is automatically disabled when CFG is enabled.

## References

* [Cache-DiT Repository](https://github.com/vipshop/cache-dit)
* [TeaCache Paper](https://arxiv.org/abs/2411.14324)