GPUStack vs vLLM
Short answer
GPUStack: GPU cluster manager that deploys vLLM, SGLang and other engines behind an OpenAI-compatible 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 (95.5k vs 5.9k GitHub stars).
Last updated · computed from each project's official docs and live GitHub data · sources
GPUStack vs vLLM side by side
| GPUStack | vLLM | |
|---|---|---|
| Category | Local model runtimes | Local model runtimes |
| What it is | GPU cluster manager that deploys vLLM, SGLang and other engines behind an OpenAI-compatible 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; keep the Apache-2.0 license and notices. GPUStack Enterprise is a separate commercial edition. Models keep their own licenses. | Permissive. Internal and commercial use allowed. Models keep their own licenses. |
| Status | Active | Active |
| GitHub stars | 5.9k | 95.5k |
| Last commit | Oct 26, 2026 | Oct 26, 2026 |
| Latest release | v2.3.0 | 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 | Required on worker nodes (Linux only): for NVIDIA, a driver supporting CUDA 12.8 or higher plus the NVIDIA Container Toolkit; for AMD, ROCm 7.0 or higher. The GPUStack server itself does not need a GPU. | 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 | pip / uv (or Docker) |
| Known gotchas | 4 listed | 1 listed |
| Telemetry | Not documented | On by default |
| Calls home by default | Yes, by default | Not documented |
| SSO (OIDC / SAML / LDAP) | Free (OIDC free · SAML free) | Not documented |
| Audit log | Not documented | Not documented |
| RBAC | Basic free, more in paid plan | Not documented |
| Details | Full GPUStack guide → | Full vLLM guide → |
Key differences
- Deploy: GPUStack: Docker · single container. vLLM: pip / uv (or Docker) · pip / uv (or Docker).
- GitHub stars: GPUStack: 5.9k. vLLM: 95.5k.
- Latest release: GPUStack: v2.3.0 (Oct 23, 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 26, 2026.
GPUStack vs vLLM: FAQ
GPUStack or vLLM: which should a small business choose?
Choose vLLM if you want: larger community (95.5k vs 5.9k GitHub stars).
Which is cheaper to self-host, GPUStack or vLLM?
GPUStack: 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 GPUStack and vLLM need?
GPUStack: not published. vLLM: not published. GPUStack and vLLM needs a GPU for practical use.
What is the license difference between GPUStack and vLLM?
GPUStack: Apache-2.0 (Permissive). Permissive. Internal and commercial use allowed; keep the Apache-2.0 license and notices. GPUStack Enterprise is a separate commercial edition. 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 GPUStack or vLLM more actively maintained?
GPUStack: Active, last commit Oct 26, 2026. vLLM: Active, last commit Oct 26, 2026. GitHub data refreshed Oct 26, 2026.
Which is easier to deploy, GPUStack or vLLM?
GPUStack installs via Docker (single container); vLLM via pip / uv (or Docker) (pip / uv (or Docker)). GPUStack lists 4 known gotchas and vLLM lists 1; see each app page.
Related
- GPUStack self-hosting guide · vLLM self-hosting guide
- All GPUStack alternatives, ranked
- All vLLM alternatives, ranked
- GPUStack vs llama.cpp
- GPUStack vs LocalAI
- GPUStack vs Ollama
- GPUStack vs Xinference
- llama.cpp vs vLLM
- LocalAI vs vLLM
- Ollama vs vLLM
- vLLM vs Xinference
- Add a third app in the interactive comparison
Sources
- GPUStack GitHub repository: github.com/gpustack/gpustack
- GPUStack documentation, GPUStack hardware requirements: docs.gpustack.ai/latest/installation/requirements/
- GPUStack license: github.com/gpustack/gpustack/blob/main/LICENSE
- GPUStack deploy instructions: github.com/gpustack/gpustack#readme
- 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 2026-10-26): 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.