SGLang vs vLLM
Short answer
SGLang: Fast serving engine for LLMs and multimodal models on GPU servers, with an OpenAI-style API. vLLM: High-throughput LLM inference server for GPUs with an OpenAI-compatible API. Both are in our Local model runtimes category.
Choose vLLM if you want: larger community (95.9k vs 38.3k GitHub stars).
Last updated · computed from each project's official docs and live GitHub data · sources
SGLang vs vLLM side by side
| SGLang | vLLM | |
|---|---|---|
| Category | Local model runtimes | Local model runtimes |
| What it is | Fast serving engine for LLMs and multimodal models on GPU servers, with an OpenAI-style API. | High-throughput LLM inference server for GPUs with an OpenAI-compatible API. |
| License | Apache-2.0 | Apache-2.0 |
| License type | Permissive | Permissive |
| License conditions | Permissive. Internal and commercial use allowed. Models keep their own licenses. | Permissive. Internal and commercial use allowed. Models keep their own licenses. |
| Status | Active | Active |
| GitHub stars | 38.3k | 95.9k |
| Last commit | Oct 31, 2026 | Oct 31, 2026 |
| Latest release | v0.5.22 | v0.32.0 |
| Minimum hardware | Not published | Not published |
| Recommended hardware | Not published | Not published |
| RAM measured by us | Not tested yet | Not tested yet |
| GPU | Yes for the documented install path: Linux with a supported NVIDIA GPU and a CUDA 13-compatible driver. The project also documents AMD Instinct, Google TPU, Intel GPU and Xeon CPU, Ascend NPU and other platforms on separate hardware pages. | NVIDIA: compute capability 7.5 or higher (e.g. T4, RTX 20xx, A100, L4, H100, B200). |
| Est. server cost | GPU server (not estimated) | GPU server (not estimated) |
| Deploy method | Docker (NVIDIA GPU) | pip / uv (or Docker) |
| Known gotchas | 4 listed | 1 listed |
| Telemetry | Not documented | On by default |
| Calls home by default | Not documented | Not documented |
| SSO (OIDC / SAML / LDAP) | Not documented | Not documented |
| Audit log | Not documented | Not documented |
| RBAC | Not documented | Not documented |
| Details | Full SGLang guide → | Full vLLM guide → |
Key differences
- Deploy: SGLang: Docker (NVIDIA GPU) · single container. vLLM: pip / uv (or Docker) · pip / uv (or Docker).
- GitHub stars: SGLang: 38.3k. vLLM: 95.9k.
- Latest release: SGLang: v0.5.22 (Oct 19, 2026). vLLM: v0.32.0 (Oct 18, 2026).
Same for both: Category: Local model runtimes; License: Apache-2.0 (Permissive); Official hardware: not published; GPU: needed for practical use; Est. server cost: GPU server (not estimated); Status: Active; Last commit: Oct 31, 2026.
SGLang vs vLLM: FAQ
SGLang or vLLM: which should a small business choose?
Choose vLLM if you want: larger community (95.9k vs 38.3k GitHub stars).
Which is cheaper to self-host, SGLang or vLLM?
SGLang: GPU server (not estimated). vLLM: GPU server (not estimated). Our estimate is the cheapest Hetzner Cloud plan that meets each project's official RAM and vCPU figure; it covers the server only.
How much hardware do SGLang and vLLM need?
SGLang: not published. vLLM: not published. SGLang and vLLM needs a GPU for practical use.
What is the license difference between SGLang and vLLM?
SGLang: Apache-2.0 (Permissive). Permissive. Internal and commercial use allowed. Models keep their own licenses. vLLM: Apache-2.0 (Permissive). Permissive. Internal and commercial use allowed. Models keep their own licenses. This is a summary, not legal advice.
Is SGLang or vLLM more actively maintained?
SGLang: Active, last commit Oct 31, 2026. vLLM: Active, last commit Oct 31, 2026. GitHub data refreshed Oct 31, 2026.
Which is easier to deploy, SGLang or vLLM?
SGLang installs via Docker (NVIDIA GPU) (single container); vLLM via pip / uv (or Docker) (pip / uv (or Docker)). SGLang lists 4 known gotchas and vLLM lists 1; see each app page.
Related
- SGLang self-hosting guide · vLLM self-hosting guide
- All SGLang alternatives, ranked
- All vLLM alternatives, ranked
- GPUStack vs SGLang
- GPUStack vs vLLM
- llama.cpp vs SGLang
- llama.cpp vs vLLM
- LocalAI vs SGLang
- LocalAI vs vLLM
- Ollama vs SGLang
- Ollama vs vLLM
- SGLang vs TextGen (text-generation-webui)
- SGLang vs Xinference
- TextGen (text-generation-webui) vs vLLM
- vLLM vs Xinference
- Add a third app in the interactive comparison
Sources
- SGLang GitHub repository: github.com/sgl-project/sglang
- SGLang documentation, SGLang deploy instructions: docs.sglang.io/docs/get-started/install
- SGLang license: github.com/sgl-project/sglang/blob/main/LICENSE
- SGLang hardware requirements: github.com/sgl-project/sglang#supported-hardware
- vLLM GitHub repository: github.com/vllm-project/vllm
- vLLM documentation, vLLM hardware requirements: docs.vllm.ai/en/latest/getting_started/installation/gpu/
- vLLM license: github.com/vllm-project/vllm/blob/main/LICENSE
- vLLM deploy instructions: github.com/vllm-project/vllm#readme
- Hetzner Cloud pricing used for cost estimates (read 2026-10-25): www.hetzner.com/cloud/regular-performance
- GitHub REST API (stars, commits, releases): docs.github.com/en/rest
Every value is generated from the same verified data as the app pages. Spotted something wrong? Tell us.