Install SGLang Diffusion

Install SGLang Diffusion on NVIDIA, AMD, MUSA, and Ascend platforms.

You can install SGLang Diffusion using one of the methods below.

Standard installation (NVIDIA GPUs)

Platform: NVIDIA GPUs (CUDA)

Pip or uv

Use uv for faster installation:

pip install --upgrade pip
pip install uv
uv pip install "sglang[diffusion]" --prerelease=allow

From source

git clone https://github.com/sgl-project/sglang.git
cd sglang
pip install --upgrade pip
pip install -e "python[diffusion]"

Or with uv:

uv pip install -e "python[diffusion]" --prerelease=allow

Docker

The Docker images are available on Docker Hub at lmsysorg/sglang, built from the Dockerfile. Replace <secret> below with your HuggingFace Hub token.

docker run --gpus all \
    --shm-size 32g \
    -p 30000:30000 \
    -v ~/.cache/huggingface:/root/.cache/huggingface \
    --env "HF_TOKEN=<secret>" \
    --ipc=host \
    lmsysorg/sglang:dev \
    zsh -c '\
        echo "Installing diffusion dependencies..." && \
        pip install -e "python[diffusion]" && \
        echo "Starting SGLang-Diffusion..." && \
        sglang generate \
            --model-path black-forest-labs/FLUX.1-dev \
            --prompt "A logo With Bold Large text: SGL Diffusion" \
            --save-output \
    '

Platform-specific installs

Use the tab that matches your accelerator.

ROCm (AMD GPUs)

Platform: AMD Instinct GPUs (ROCm)

For AMD Instinct GPUs (for example, MI300X), use the ROCm-enabled Docker image:

docker run --device=/dev/kfd --device=/dev/dri --ipc=host \
  -v ~/.cache/huggingface:/root/.cache/huggingface \
  --env HF_TOKEN=<secret> \
  lmsysorg/sglang:v0.5.9-rocm700-mi30x \
  sglang generate --model-path black-forest-labs/FLUX.1-dev --prompt "A logo With Bold Large text: SGL Diffusion" --save-output

For detailed ROCm system configuration and installation from source, see AMD GPUs.

MUSA (Moore Threads GPUs)

Platform: Moore Threads GPUs (MUSA)

For Moore Threads GPUs (MTGPU) with the MUSA software stack:

git clone https://github.com/sgl-project/sglang.git
cd sglang
pip install --upgrade pip
rm -f python/pyproject.toml && mv python/pyproject_other.toml python/pyproject.toml
pip install -e "python[all_musa]"

Ascend NPU

Platform: Ascend NPU

For Ascend NPU, follow the [NPU installation guide](../hardware-platforms/ascend-npus/SGLang installation with NPUs support).

Quick test:

sglang generate --model-path black-forest-labs/FLUX.1-dev \
    --prompt "A logo With Bold Large text: SGL Diffusion" \
    --save-output