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GPUStack is an open-source GPU cluster management platform designed to simplify the deployment and operation of artificial intelligence models across heterogeneous hardware environments. The system aggregates GPU resources from multiple machines into a unified cluster so developers and administrators can run large language models and other AI workloads efficiently across distributed infrastructure. Instead of requiring complex orchestration systems such as Kubernetes, GPUStack provides a lightweight environment that automatically selects appropriate inference engines, configures deployment parameters, and schedules workloads across available GPUs. The platform supports GPUs from a wide range of vendors and can run on laptops, workstations, and servers across operating systems such as macOS, Windows, and Linux. It also enables developers to deploy models from common repositories like Hugging Face and access them through APIs similar to cloud-based AI services.
Features
- GPU cluster aggregation across heterogeneous hardware environments
- Distributed inference across single-node and multi-node GPU systems
- Support for multiple inference backends such as llama.cpp and vLLM
- OpenAI-compatible API endpoints for model serving
- Real-time monitoring of GPU utilization and token usage
- Model deployment workflows integrated with popular repositories
Project Samples
