--- title: "Supported Models" description: "Check model compatibility across diffusion optimizations and backends." --- The table below shows every supported model and the optimizations supported for them. Key: - `Yes` = Compatible - `No` = Incompatible - `N/A` = Not applicable ## 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
Model Name HuggingFace Model ID Resolutions TeaCache Sliding Tile Attn Sage Attn Video Sparse Attention (VSA) Sparse Linear Attention (SLA) Sage Sparse Linear Attention (SageSLA) Sparse Video Gen 2 (SVG2)
FastWan2.1 T2V 1.3B `FastVideo/FastWan2.1-T2V-1.3B-Diffusers` 480p N/A N/A N/A Yes No No No
FastWan2.2 TI2V 5B Full Attn `FastVideo/FastWan2.2-TI2V-5B-FullAttn-Diffusers` 720p N/A N/A N/A Yes No No No
Wan2.2 TI2V 5B `Wan-AI/Wan2.2-TI2V-5B-Diffusers` 720p N/A N/A Yes N/A No No No
Wan2.2 T2V A14B `Wan-AI/Wan2.2-T2V-A14B-Diffusers` 480p, 720p No No Yes N/A No No No
Wan2.2 I2V A14B `Wan-AI/Wan2.2-I2V-A14B-Diffusers` 480p, 720p No No Yes N/A No No No
HunyuanVideo `hunyuanvideo-community/HunyuanVideo` 720x1280, 544x960 No Yes Yes N/A No No Yes
FastHunyuan `FastVideo/FastHunyuan-diffusers` 720x1280, 544x960 No Yes Yes N/A No No Yes
Wan2.1 T2V 1.3B `Wan-AI/Wan2.1-T2V-1.3B-Diffusers` 480p Yes Yes Yes N/A No No Yes
Wan2.1 T2V 14B `Wan-AI/Wan2.1-T2V-14B-Diffusers` 480p, 720p Yes Yes Yes N/A No No Yes
Wan2.1 I2V 480P `Wan-AI/Wan2.1-I2V-14B-480P-Diffusers` 480p Yes Yes Yes N/A No No Yes
Wan2.1 I2V 720P `Wan-AI/Wan2.1-I2V-14B-720P-Diffusers` 720p Yes Yes Yes N/A No No Yes
TurboWan2.1 T2V 1.3B `IPostYellow/TurboWan2.1-T2V-1.3B-Diffusers` 480p Yes No No No Yes Yes N/A
TurboWan2.1 T2V 14B `IPostYellow/TurboWan2.1-T2V-14B-Diffusers` 480p Yes No No No Yes Yes N/A
TurboWan2.1 T2V 14B 720P `IPostYellow/TurboWan2.1-T2V-14B-720P-Diffusers` 720p Yes No No No Yes Yes N/A
TurboWan2.2 I2V A14B `IPostYellow/TurboWan2.2-I2V-A14B-Diffusers` 720p Yes No No No Yes Yes N/A
1. Wan2.2 TI2V 5B has known quality issues for some I2V workloads. 2. SageSLA is based on SpargeAttn. Install SpargeAttn first with `pip install git+https://github.com/thu-ml/SpargeAttn.git --no-build-isolation`. ### Image Generation Models
Model Name HuggingFace Model ID Resolutions
FLUX.1-dev `black-forest-labs/FLUX.1-dev` Any resolution
FLUX.2-dev `black-forest-labs/FLUX.2-dev` Any resolution
FLUX.2-Klein `black-forest-labs/FLUX.2-klein-4B` Any resolution
Z-Image-Turbo `Tongyi-MAI/Z-Image-Turbo` Any resolution
GLM-Image `zai-org/GLM-Image` Any resolution
Qwen Image `Qwen/Qwen-Image` Any resolution
Qwen Image 2512 `Qwen/Qwen-Image-2512` Any resolution
Qwen Image Edit `Qwen/Qwen-Image-Edit` Any resolution
## Verified LoRA Examples This section lists example LoRAs that have been explicitly tested and verified with each base model in the **SGLang Diffusion** pipeline. 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
Base Model Supported LoRAs
Wan2.2 `lightx2v/Wan2.2-Distill-Loras`
`Cseti/wan2.2-14B-Arcane_Jinx-lora-v1`
Wan2.1 `lightx2v/Wan2.1-Distill-Loras`
Z-Image-Turbo `tarn59/pixel_art_style_lora_z_image_turbo`
`wcde/Z-Image-Turbo-DeJPEG-Lora`
Qwen-Image `lightx2v/Qwen-Image-Lightning`
`flymy-ai/qwen-image-realism-lora`
`prithivMLmods/Qwen-Image-HeadshotX`
`starsfriday/Qwen-Image-EVA-LoRA`
Qwen-Image-Edit `ostris/qwen_image_edit_inpainting`
`lightx2v/Qwen-Image-Edit-2511-Lightning`
Flux `dvyio/flux-lora-simple-illustration`
`XLabs-AI/flux-furry-lora`
`XLabs-AI/flux-RealismLora`
## Special requirements ### Sliding Tile Attention - Currently, only Hopper GPUs (H100s) are supported.