Install SGLang-Diffusion#
You can install SGLang-Diffusion using one of the methods below.
Standard Installation (NVIDIA GPUs)#
Method 1: With pip or uv#
It is recommended to use uv for a faster installation:
pip install --upgrade pip
pip install uv
uv pip install "sglang[diffusion]" --prerelease=allow
Method 2: From source#
# Use the latest release branch
git clone https://github.com/sgl-project/sglang.git
cd sglang
# Install the Python packages
pip install --upgrade pip
pip install -e "python[diffusion]"
# With uv
uv pip install -e "python[diffusion]" --prerelease=allow
Method 3: Using 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: ROCm (AMD GPUs)#
For AMD Instinct GPUs (e.g., MI300X), you can 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:v0.5.5.post2-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.
Platform-Specific: MUSA (Moore Threads GPUs)#
For Moore Threads GPUs (MTGPU) with the MUSA software stack:
# Clone the repository
git clone https://github.com/sgl-project/sglang.git
cd sglang
# Install the Python packages
pip install --upgrade pip
rm -f python/pyproject.toml && mv python/pyproject_other.toml python/pyproject.toml
pip install -e "python[all_musa]"
Quick test:
sglang generate --model-path black-forest-labs/FLUX.1-dev \
--prompt "A logo With Bold Large text: SGL Diffusion" \
--save-output