Standard Hugging Face transformers waste up to 80% of GPU memory in KV-cache fragmentation. vLLM implements PagedAttention to serve 10x more concurrent requests:
bash
# Serve DeepSeek-V3 or Llama-3.3 with OpenAI-compatible endpoint vllm serve meta-llama/Llama-3.3-70B-Instruct \ --tensor-parallel-size 2 \ --max-model-len 8192 \ --gpu-memory-utilization 0.95 \ --port 8000
Connect from Any OpenAI Client
python
from openai import OpenAI client = OpenAI(base_url="http://localhost:8000/v1", api_key="none")
Enjoy continuous request batching with enterprise-grade token generation velocity.