Comparison

SGLang vs vLLM

A like-for-like, spec-level comparison. Both entries are verified against their docs and repo.

SGLang

Fast serving and structured generation engine.

+ Excellent for structured generation and multi-turn
+ RadixAttention reuses shared prefixes efficiently
− Newer than vLLM, smaller ecosystem
− Requires GPU ops expertise

vLLM

High-throughput self-hosted LLM serving engine.

+ Industry-standard throughput and batching
+ Broad model and hardware support
− Requires GPU ops expertise to run well
− Configuration surface is large

Spec	SGLang	vLLM
Role	Inference engine	Inference engine
Tags	inference-engine	inference-engine
License	Apache-2.0	Apache-2.0
Open source	Yes	Yes
Self-hostable	Yes	Yes
MCP support	No	No
Pricing	free	free
Price	Free	Free
Usage cost	No model cost	No model cost
Models	multi	multi
Languages	python	python
GitHub stars	29.9k	85.3k
Last activity	2026-07-04	2026-07-04