Pick SGLang if
inference engineers who already have GPUs and will run sglang serve (or the Cookbook one-click recipe), not a team looking for a $20 chat plan.
Read the SGLang pageSGLang vs vLLM
Our take
Pick SGLang if inference engineers who already have GPUs and will run sglang serve (or the Cookbook one-click recipe), not a team looking for a $20 chat plan. Pick vLLM if platform and inference engineers who already have a GPU (or a kube cluster) and need an OpenAI-shaped endpoint. Skip vLLM if someone who wants a local ChatGPT window (Ollama, Jan) and will not run vllm serve.
vLLM
high-throughput LLM serving engine
Best for
SGLang Serve tokens (or diffusion frames) on GPUs you already own
vLLM Serving tokens at production QPS
Free plan
SGLang $0
vLLM $0 · apache-2.0. You pay the GPU, electricity, and (if you use them) model licenses
Lowest paid
SGLang Not published by the vendor
vLLM Not published by the vendor
Runs where
SGLang Hosted
vLLM Web, desktop; hosted
Watch out
SGLang You bring the GPU
vLLM The GPU is the bill
Last checked
SGLang 2026-10-22 · github.com/sgl-project/sglang/blob
vLLM 2026-10-20 · github.com/vllm-project/vllm
Which one, then?
Pick vLLM if
platform and inference engineers who already have a GPU (or a kube cluster) and need an OpenAI-shaped endpoint.
Read the vLLM page