GPUStack vs TORQUE Resource Manager
GPUStack
gpustack.aiTORQUE Resource Manager
github.comSide by side
| Figure | GPUStack | TORQUE Resource Manager |
|---|---|---|
| Price from | Free | Free |
| Free plan | Yes | Yes |
| Free trial | — | — |
| Open source | — | — |
| Web | Yes | — |
| Windows | Yes | — |
| macOS | Yes | Yes |
| Linux | Yes | Yes |
| API | Yes | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 1 | 1 |
| Spec score · GPU Cluster Management Software | 8.3 (#4) | 7.5 (#12) |
| Integrations | Listed integrations include OpenWebUI, LangChain, n8n, Dify, RAGFlow, Claude Code, OpenClaw, Docker, Podman, Kubernetes, Helm, Prometheus, and Grafana. | The maker's documentation describes integration between TORQUE and the Moab Workload Manager. |
| Support | The contact page offers personalized demos and architecture, deployment, and scaling guidance, and says replies typically arrive within one business day. | The project README directs questions and contributions to the [email protected] mailing list. |
Plans
In their own words
GPUStack
GPUStack is an open-source GPU cluster manager for deploying, governing, and scaling AI models across on-premise, cloud, or hybrid infrastructure. It provides OpenAI-compatible and Anthropic-compatible inference endpoints, with support for engines such as vLLM, SGLang, llama.cpp, TensorRT-LLM, and MindIE. Users can browse models from Hugging Face and ModelScope or supply local files, with automated compatibility checks. GPUStack can provision GPU instances with lifecycle controls, partitioning, SSH key injection, Jupyter access, and persistent S3 or NFS storage. Deployment options include on-premise, Kubernetes, and multi-cloud, including air-gapped deployments. The maker lists support for accelerators from NVIDIA, AMD, Ascend, T-head, Hygon, MetaX, Moore Threads, Cambricon, and Iluvatar. Security controls include RBAC, multi-tenancy, SSO, scoped API keys, IP allowlisting, token quotas, and usage analytics. GPUStack Community Edition is free. Worker nodes support Linux only; Windows users are directed to consider WSL2, and macOS worker nodes are not supported.
TORQUE Resource Manager
TORQUE Resource Manager is an open-source resource and queue manager for compute clusters, based on the original PBS resource manager. The project is free, with Linux, macOS, API and self-hosted options. TORQUE 4.0 release notes state that it can support clusters with more than 15,000 compute nodes; that release also introduced a multithreaded pbs_server intended to improve command response and job throughput. An optional MOM hierarchy can reduce update traffic from compute nodes to pbs_server and lets administrators manage network communication. In version 4.0, component communication moved to TCP/IP, removing UDP and RPP. The trqauthd daemon authorizes client connections to pbs_server and must run as root on client hosts. Linux builds can optionally use control groups and cpusets, and documentation describes integration with Moab Workload Manager. The project is built from source using configure and make; installation instructions also cover RPM and self-extracting package creation. Its license terms are in the repository's PBS_License.txt. A compatibility caveat for version 4.0 is that its components cannot communicate with earlier TORQUE versions, so rolling upgrades will not work.