GPUStack pools heterogeneous GPUs across machines into one cluster and schedules model workloads across them, with a web UI and OpenAI-compatible endpoints.
| Category | Run LLMs locally |
| Type | GPU cluster manager |
| License | Apache-2.0 |
| Runs locally | Yes |
| Built with | Python |
| Skill level | Advanced |
| Best for | teams with several GPU machines to pool |
Other open-source run llms locally tools worth comparing:
OllamaRun open LLMs locally from one command
JanOpen-source, offline ChatGPT-style desktop app
GPT4AllPrivate local AI that runs on CPU
llama.cppThe C/C++ engine powering local inference
LocalAIA drop-in OpenAI API you self-host
Text Generation WebUIFeature-rich web UI for local models
KoboldCppSingle-file local model runner
MLC LLMRun LLMs on any device, even phones
llamafileOne executable file = model + runtime
exoRun big models across your everyday devices
CortexOllama-style runtime from the Jan team
Nexa SDKRun any model on any device — CPU, GPU, NPU
RamaLamaRun models as OCI containersGPUStack is free and open-source (Apache-2.0 license), so you can use, self-host and modify it at no cost.
Yes. GPUStack is designed to run on your own machine or server, keeping your data private.
Popular open-source alternatives include Ollama, LM Studio, Jan. See the comparisons above to choose.
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