Runtime comparison
llama.cpp vs SGLang
llama.cpp is a MIT-licensed runtime for Linux · macOS · Windows running on CUDA · Metal · CPU · Vulkan · ROCm; SGLang is Apache-2.0-licensed for Linux on CUDA · ROCm. llama.cpp rates easier to set up (3/5 vs 2/5 in our sourced ratings). Pick llama.cpp for serving many requests at once; pick SGLang for serving many requests at once.
| Spec | llama.cpp | SGLang |
|---|---|---|
| License | MIT | Apache-2.0 |
| Operating systems | Linux · macOS · Windows | Linux |
| GPU backends | CUDA · Metal · CPU · Vulkan · ROCm | CUDA · ROCm |
| Install | source / binary | pip / source |
| Ease of use | 3/5 | 2/5 |
| Quant formats | gguf | awq, gptq |
| Engine | ggml | sglang |
| GitHub stars | 119,748 | 30,090 |
| Latest version | b9935 | v0.5.14 |
| Graphical app (GUI) | No | No |
| Server mode | Yes | Yes |
| OpenAI-compatible API | Yes | Yes |
| CPU offload | Yes | No |
| Multi-GPU | Yes | Yes |
| Speculative decoding | Yes | Yes |
| LoRA support | Yes | Yes |
| KV-cache quantization | Yes | Yes |
Which should you use?
llama.cpp
Best for serving many requests at once. Command line and server, runs on CUDA · Metal · CPU · Vulkan · ROCm.
Full llama.cpp guide →SGLang
Best for serving many requests at once. Command line and server, runs on CUDA · ROCm.
Full SGLang guide →Neither runtime changes whether a model fits — that is your memory and quantization. Check your hardware first, then pick the runtime.
Sources: llama.cpp github.com/ggml-org/llama.cpp (as of 2026-07-11); SGLang github.com/sgl-project/sglang (as of 2026-07-08).