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Comparison

llama.cpp vs SGLang

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

llama.cpp

C/C++ inference for GGUF models on any hardware.

  • + Runs on almost any hardware, including CPU-only
  • + Defines the widely-used GGUF format
  • − Lower-level than managed servers
  • − Performance tuning requires quantization knowledge

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
Spec llama.cpp SGLang
Role Inference engine Inference engine
Tags inference-engine inference-engine
License MIT 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 local, multi multi
Languages cpp python
GitHub stars 119.2k 29.9k
Last activity 2026-07-03 2026-07-04