sglang/python/sglang/multimodal_gen/docs/cache_dit.md

Cache-DiT Acceleration

SGLang integrates Cache-DiT, a caching acceleration engine for Diffusion Transformers (DiT), to achieve up to 7.4x inference speedup with minimal quality loss.

Overview

Cache-DiT uses intelligent caching strategies to skip redundant computation in the denoising loop:

• DBCache (Dual Block Cache): Dynamically decides when to cache transformer blocks based on residual differences
• TaylorSeer: Uses Taylor expansion for calibration to optimize caching decisions
• SCM (Step Computation Masking): Step-level caching control for additional speedup

Basic Usage

Enable Cache-DiT by exporting the environment variable and using sglang generate or sglang serve :

SGLANG_CACHE_DIT_ENABLED=true \
sglang generate --model-path Qwen/Qwen-Image \
    --prompt "A beautiful sunset over the mountains"

Advanced Configuration

DBCache Parameters

DBCache controls block-level caching behavior:

Parameter	Env Variable	Default	Description
Fn	SGLANG_CACHE_DIT_FN	1	Number of first blocks to always compute
Bn	SGLANG_CACHE_DIT_BN	0	Number of last blocks to always compute
W	SGLANG_CACHE_DIT_WARMUP	4	Warmup steps before caching starts
R	SGLANG_CACHE_DIT_RDT	0.24	Residual difference threshold
MC	SGLANG_CACHE_DIT_MC	3	Maximum continuous cached steps

TaylorSeer Configuration

TaylorSeer improves caching accuracy using Taylor expansion:

Parameter	Env Variable	Default	Description
Enable	SGLANG_CACHE_DIT_TAYLORSEER	false	Enable TaylorSeer calibrator
Order	SGLANG_CACHE_DIT_TS_ORDER	1	Taylor expansion order (1 or 2)

Combined Configuration Example

DBCache and TaylorSeer are complementary strategies that work together, you can configure both sets of parameters simultaneously:

SGLANG_CACHE_DIT_ENABLED=true \
SGLANG_CACHE_DIT_FN=2 \
SGLANG_CACHE_DIT_BN=1 \
SGLANG_CACHE_DIT_WARMUP=4 \
SGLANG_CACHE_DIT_RDT=0.4 \
SGLANG_CACHE_DIT_MC=4 \
SGLANG_CACHE_DIT_TAYLORSEER=true \
SGLANG_CACHE_DIT_TS_ORDER=2 \
sglang generate --model-path black-forest-labs/FLUX.1-dev \
    --prompt "A curious raccoon in a forest"

SCM (Step Computation Masking)

SCM provides step-level caching control for additional speedup. It decides which denoising steps to compute fully and which to use cached results.

SCM Presets

SCM is configured with presets:

Preset	Compute Ratio	Speed	Quality
none	100%	Baseline	Best
slow	~75%	~1.3x	High
medium	~50%	~2x	Good
fast	~35%	~3x	Acceptable
ultra	~25%	~4x	Lower

Usage

SGLANG_CACHE_DIT_ENABLED=true \
SGLANG_CACHE_DIT_SCM_PRESET=medium \
sglang generate --model-path Qwen/Qwen-Image \
    --prompt "A futuristic cityscape at sunset"

Custom SCM Bins

For fine-grained control over which steps to compute vs cache:

SGLANG_CACHE_DIT_ENABLED=true \
SGLANG_CACHE_DIT_SCM_COMPUTE_BINS="8,3,3,2,2" \
SGLANG_CACHE_DIT_SCM_CACHE_BINS="1,2,2,2,3" \
sglang generate --model-path Qwen/Qwen-Image \
    --prompt "A futuristic cityscape at sunset"

SCM Policy

Policy	Env Variable	Description
dynamic	SGLANG_CACHE_DIT_SCM_POLICY=dynamic	Adaptive caching based on content (default)
static	SGLANG_CACHE_DIT_SCM_POLICY=static	Fixed caching pattern

Environment Variables

All Cache-DiT parameters can be set via the following environment variables:

Environment Variable	Default	Description
SGLANG_CACHE_DIT_ENABLED	false	Enable Cache-DiT acceleration
SGLANG_CACHE_DIT_FN	1	First N blocks to always compute
SGLANG_CACHE_DIT_BN	0	Last N blocks to always compute
SGLANG_CACHE_DIT_WARMUP	4	Warmup steps before caching
SGLANG_CACHE_DIT_RDT	0.24	Residual difference threshold
SGLANG_CACHE_DIT_MC	3	Max continuous cached steps
SGLANG_CACHE_DIT_TAYLORSEER	false	Enable TaylorSeer calibrator
SGLANG_CACHE_DIT_TS_ORDER	1	TaylorSeer order (1 or 2)
SGLANG_CACHE_DIT_SCM_PRESET	none	SCM preset (none/slow/medium/fast/ultra)
SGLANG_CACHE_DIT_SCM_POLICY	dynamic	SCM caching policy
SGLANG_CACHE_DIT_SCM_COMPUTE_BINS	not set	Custom SCM compute bins
SGLANG_CACHE_DIT_SCM_CACHE_BINS	not set	Custom SCM cache bins

Supported Models

SGLang Diffusion x Cache-DiT supports almost all models originally supported in SGLang Diffusion:

Model Family	Example Models
Wan	Wan2.1, Wan2.2
Flux	FLUX.1-dev, FLUX.2-dev
Z-Image	Z-Image-Turbo
Qwen	Qwen-Image, Qwen-Image-Edit
Hunyuan	HunyuanVideo

Performance Tips

1. Start with defaults: The default parameters work well for most models
2. Use TaylorSeer: It typically improves both speed and quality
3. Tune R threshold: Lower values = better quality, higher values = faster
4. SCM for extra speed: Use medium preset for good speed/quality balance
5. Warmup matters: Higher warmup = more stable caching decisions

Limitations

• Single GPU only: Distributed support (TP/SP) is not yet validated; Cache-DiT will be automatically disabled when world_size > 1
• SCM minimum steps: SCM requires >= 8 inference steps to be effective
• Model support: Only models registered in Cache-DiT's BlockAdapterRegister are supported

Troubleshooting

Distributed environment warning

WARNING: cache-dit is disabled in distributed environment (world_size=N)

This is expected behavior. Cache-DiT currently only supports single-GPU inference.

SCM disabled for low step count

For models with < 8 inference steps (e.g., DMD distilled models), SCM will be automatically disabled. DBCache acceleration still works.

References

• Cache-Dit
• SGLang Diffusion