Compatibility Matrix

The table below shows every supported model and the optimizations supported for them.

The symbols used have the following meanings:

• ✅ = Full compatibility
• ❌ = No compatibility
• ⭕ = Does not apply to this model

Models x Optimization

The HuggingFace Model ID can be passed directly to from_pretrained() methods, and sglang-diffusion will use the optimal default parameters when initializing and generating videos.

Video Generation Models

Note:

1. Wan2.2 TI2V 5B has some quality issues when performing I2V generation. We are working on fixing this issue.
2. SageSLA is based on SpargeAttn. Install it first with pip install git+https://github.com/thu-ml/SpargeAttn.git --no-build-isolation
3. LTX pipeline selection:
   • One-stage: --pipeline-class-name LTX2Pipeline
   • Two-stage: --pipeline-class-name LTX2TwoStagePipeline
   • Two-stage HQ: --pipeline-class-name LTX2TwoStageHQPipeline (HQ defaults to 1920×1088; you can still override --width/--height)
   • LTX-2 and LTX-2.3 support both T2V and TI2V (--image-path) on one-stage and two-stage pipelines (including HQ).
   • The spatial upsampler and distilled LoRA are auto-resolved from the model snapshot by default, and can still be overridden with --spatial-upsampler-path and --distilled-lora-path.
   • For LTX models, the Resolutions column uses output video width×height semantics, matching sglang generate --width ... --height ....
4. LTX-2 / LTX-2.3 two-stage also supports --ltx2-two-stage-device-mode {original,snapshot,resident}:
   • snapshot is the default and recommended mode.
   • resident usually provides the best latency/throughput but uses much more VRAM.
   • original keeps official two-stage semantics without the premerged stage-2 transformer path.
   • Example (one prior run): original 154.67s, snapshot 114.05s, resident 75.71s; peak VRAM trend is original < snapshot < resident.

Image Generation Models

Supported Components

SGLang Diffusion supports overriding individual pipeline components with --<component>-path. The value can be either a Hugging Face repo ID or a local component directory.

The same overrides can also be provided in config files through component_paths.<component>.

Common Syntax

CLI:

sglang generate \
  --model-path black-forest-labs/FLUX.2-dev \
  --vae-path black-forest-labs/FLUX.2-small-decoder \
  --transformer-path /models/flux2/transformer

Config file:

model_path: black-forest-labs/FLUX.2-dev
component_paths:
  vae: black-forest-labs/FLUX.2-small-decoder
  transformer: /models/flux2/transformer

Use the component name from the pipeline's model_index.json or the native pipeline's registered module name:

Known Component Repos

The table below lists concrete Hugging Face component repos that are already used in SGLang Diffusion docs or tests. It is not an exhaustive catalog of all compatible component repos.

VAE

• --vae-path is the common image-generation override.
• --video-vae-path and --audio-vae-path are only relevant for pipelines with separate video or audio VAEs.

Transformer / DiT

• --transformer-path is the standard override for the main denoising transformer.
• For quantized transformers, prefer --transformer-path or --transformer-weights-path; see quantization.md.
• --video-dit-path and --audio-dit-path are only for pipelines that split denoisers by modality.

Text Encoders and Preprocessors

• --text-encoder-path and --text-encoder-2-path override primary and secondary text encoders.
• --tokenizer-path, --processor-path, and --image-processor-path are useful when the replacement encoder requires matching preprocessing assets.

Auxiliary Components

• --scheduler-path is only relevant when the pipeline exposes a scheduler component.
• --spatial-upsampler-path is mainly for two-stage pipelines such as LTX2TwoStagePipeline.
• --vocoder-path, --connectors-path, --dual-tower-bridge-path, --image-encoder-path, and --vision-language-encoder-path are only valid for pipelines that expose those components.

Notes

1. Component overrides are only valid when the target pipeline actually uses that component.
2. The override key should match the component name in the pipeline's model_index.json or the native pipeline's registered module name.

Verified LoRA Examples

This section lists example LoRAs that have been explicitly tested and verified with each base model in the SGLang Diffusion pipeline.

Important: LoRAs that are not listed here are not necessarily incompatible. In practice, most standard LoRAs are expected to work, especially those following common Diffusers or SD-style conventions. The entries below simply reflect configurations that have been manually validated by the SGLang team.

Verified LoRAs by Base Model

Special requirements

Sliding Tile Attention

• Currently, only Hopper GPUs (H100s) are supported.