SGLang v0.4.1 - DeepSeek V3 Support
We're excited to announce SGLang v0.4.1, which now supports DeepSeek V3 - currently the strongest open-source LLM, even surpassing GPT-4o.
The SGLang and DeepSeek teams worked together to get DeepSeek V3 FP8 running on NVIDIA and AMD GPU from day one. We've also supported MLA optimization and DP attention before, making SGLang one of the best open-source LLM engines for running DeepSeek models.
Special thanks to Meituan's Search & Recommend Platform Team and Baseten's Model Performance Team for their support, and DataCrunch for providing GPU resources.
Hardware Recommendation
- 8 x NVIDIA H200 GPUs
Installation & Launch
Using Docker (Recommended)
docker run --gpus all --shm-size 32g -p 30000:30000 -v ~/.cache/huggingface:/root/.cache/huggingface --ipc=host lmsysorg/sglang:latest \
python3 -m sglang.launch_server --model deepseek-ai/DeepSeek-V3-Base --enable-dp-attention --tp 8 --trust-remote-code --port 30000
Using pip
# Installation
pip install "sglang[all]" --find-links https://flashinfer.ai/whl/cu124/torch2.4/flashinfer
# Launch
python3 -m sglang.launch_server --model deepseek-ai/DeepSeek-V3-Base --enable-dp-attention --tp 8 --trust-remote-code
Example with OpenAI API
import openai
client = openai.Client(
base_url="http://127.0.0.1:30000/v1", api_key="EMPTY")
# Chat completion
response = client.chat.completions.create(
model="default",
messages=[
{"role": "system", "content": "You are a helpful AI assistant"},
{"role": "user", "content": "List 3 countries and their capitals."},
],
temperature=0,
max_tokens=64,
)
print(response)
DeepSeek V3 optimization plan
https://github.com/sgl-project/sglang/issues/2591
Appendix
SGLang is the inference engine officially recommended by the DeepSeek team.