GPUStack is a control plane that turns a pile of GPU servers into a model-serving platform, where you pick a model from a catalog and the system decides which machine, engine, and settings run it. Deploy language, embedding, reranker, speech, and image models from the Catalog page, then watch each replica move from downloading to Running on the Deployments screen. A built-in Playground offers chat, side-by-side model comparison, embedding and rerank testing, audio, and image generation and editing, so a model gets judged before it is wired into an app. Add GPU workers with a generated Docker command, register a Kubernetes cluster, or provision cloud machines, and manage several clusters from one server. Create API keys for teammates, apply access control, and read token, GPU-hour, and storage usage by user, key, or model. Auto Tune benchmarking searches for the highest throughput that still meets your latency targets. GPU Instances hand out SSH-accessible machines for fine-tuning and interactive work. Single sign-on works through OIDC or SAML. Running on a dedicated VPS on RepoCloud with guaranteed CPU, RAM, and SSD, full root SSH access, and a browser serial console. Apache 2.0 licensed.