Runtime comparison - verified
vLLM vs SGLang
vLLM (vLLM project) and SGLang (SGLang project (LMSYS)), compared field by field from their official docs as of October 18, 2026. Their docs differ on 3 feature points, listed below; the table also shows versions, install methods and links.
Key differences
- Interface: vLLM lists Python library and SGLang does not.
- Model formats: SGLang lists MLX and vLLM does not.
- MCP client: vLLM documents it; SGLang does not state it in its docs.
Generated from the fields below that differ. Versions, dates and links are left to the table.
Side by side
Every field we track, with the source linked on each value. Rows marked Differs are where the two runtimes' docs differ.
| Field | vLLM | SGLang |
|---|---|---|
| VendorDiffers | vLLM project | SGLang project (LMSYS) |
| License | Apache-2.0 | Apache-2.0 |
| Open source | Yes | Yes |
| Latest releaseDiffers | v0.31.0 | v0.5.21 |
| Release dateDiffers | October 5, 2026 | October 2, 2026 |
| InterfaceDiffers | CLI, Server, Python library, Docker | CLI, Server, Docker |
| Platforms | Linux, macOS | Linux, macOS |
| Backends | CUDA, ROCm, CPU, TPU, Metal, NPU, Other | CUDA, ROCm, CPU, TPU, NPU, Metal, Other |
| Model formatsDiffers | Safetensors, GGUF | Safetensors, GGUF, MLX |
| OpenAI-compatible API | Yeshttp://localhost:8000/v1 (server starts at http://localhost:8000 by default; change with --host and --port) | Yeshttp://localhost:30000/v1 (port 30000 as used in the official quickstart: sglang serve MODEL_PATH --host 0.0.0.0 --port 30000) |
| Anthropic-compatible API | Yes | Yes |
| Tool calling | Yes | Yes |
| Structured outputs | Yes | Yes |
| Vision (image input) | Yes | Yes |
| Multi-GPU | Yes | Yes |
| MCP clientDiffers | Yes | Not stated |
| Install methods listedDiffers | linux (NVIDIA CUDA); linux (AMD ROCm); Google TPU; docker (CUDA 13.0) | linux (NVIDIA CUDA 13, uv); docker (Linux, NVIDIA GPU) |
| Run exampleDiffers | vllm serve Qwen/Qwen2.5-1.5B-Instruct | sglang serve MODEL_PATH --host 0.0.0.0 --port 30000 |
| Audience, per the vendorDiffers | A high-throughput, memory-efficient inference and serving engine for LLMs, used to serve models over an OpenAI-compatible HTTP server or run offline batch inference in Python, mainly on Linux GPU and accelerator hardware. | A high-performance serving framework for large language and multimodal models, designed for low-latency, high-throughput inference from a single GPU up to large distributed clusters. |
| HomepageDiffers | docs.vllm.ai | docs.sglang.io |
| Source repositoryDiffers | github.com/vllm-project/vllm | github.com/sgl-project/sglang |
Install both
Copied verbatim from the page linked under each command.
vLLM
linux (NVIDIA CUDA)
uv pip install vllm --torch-backend=autolinux (AMD ROCm)
uv pip install vllm --extra-index-url https://wheels.vllm.ai/rocm/docker (CUDA 13.0)
docker pull vllm/vllm-openai:v0.31.0SGLang
linux (NVIDIA CUDA 13, uv)
uv pip install --prerelease=allow sglangdocker (Linux, NVIDIA GPU)
docker pull lmsysorg/sglang:latestFAQ
What is the difference between vLLM and SGLang?
Going by their official docs: Interface: vLLM lists Python library and SGLang does not. Model formats: SGLang lists MLX and vLLM does not. MCP client: vLLM documents it; SGLang does not state it in its docs.
Do vLLM and SGLang both have an OpenAI-compatible API?
vLLM: yes. http://localhost:8000/v1 (server starts at http://localhost:8000 by default; change with --host and --port). SGLang: yes. http://localhost:30000/v1 (port 30000 as used in the official quickstart: sglang serve MODEL_PATH --host 0.0.0.0 --port 30000).
Which platforms do vLLM and SGLang run on?
vLLM: Linux, macOS. SGLang: Linux, macOS. Both list Linux and macOS.
Are vLLM and SGLang open source?
vLLM is open source (Apache-2.0). SGLang is open source (Apache-2.0).
Do vLLM and SGLang support tool calling and MCP?
Tool calling: vLLM yes, SGLang yes. MCP client: vLLM yes, SGLang not stated. "Not stated" means the docs do not say.
What are the latest versions of vLLM and SGLang?
As of October 18, 2026: vLLM v0.31.0 (October 5, 2026) and SGLang v0.5.21 (October 2, 2026).
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