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dstack vs OpenPBS

dstack

dstack.ai

OpenPBS

openpbs.org

Side by side

FiguredstackOpenPBS
Price fromFreeFree
Free planYesYes
Free trial——
Open source——
WebYes—
WindowsYes—
macOSYesYes
LinuxYesYes
APIYesYes
Self-hostedYesYes
Plans published21
Spec score · GPU Cluster Management Software8.9 (#1)7.6 (#9)
Purposedstack is an open-source orchestration layer for AI workloads on heterogeneous accelerators, including GPU clouds, Kubernetes, VMs, and bare-metal clusters.OpenPBS optimizes job scheduling and workload management in high-performance computing environments.

Plans

dstack

  • dstack OSSFree
  • dstack Sky GPU MarketplacePriced on request

dstack pricing →

OpenPBS

  • OpenPBS open-source editionFree

OpenPBS pricing →

In their own words

dstack

dstack is an open-source orchestration layer for AI workloads across GPU clouds, Kubernetes, virtual machines, and bare-metal clusters. YAML configurations define fleets, development environments, tasks, services, presets, and volumes, while dstack handles provisioning and job scheduling, including auto-scaling, port forwarding, and ingress. Supported accelerators include NVIDIA, AMD, TPU, and Tenstorrent. Documented backends include AWS, Azure, GCP, Kubernetes, GPU cloud providers, remote SSH hosts, and experimental Slurm. Tasks can use frameworks such as accelerate, torchrun, Ray, and Spark. Users manage resources through the CLI or HTTP API, and the server can run on a laptop or another environment that can access the clusters in use. Services can publish inference endpoints through gateways with HTTPS, custom domains, auto-scaling, and rate limits. The self-hosted open-source stack is free. Server data and project secrets are stored in plaintext by default unless administrators configure AES-256-GCM encryption. TPU support is limited to single-host instances with up to eight cores. GPU Marketplace usage is prepaid, with prices that vary by GPU and provider and appear in the console before provisioning.

Visit dstack.ai

OpenPBS

OpenPBS schedules jobs and manages workloads in high-performance computing environments, including clusters, clouds, and supercomputers. Its policy-driven scheduling balances job turnaround time and system utilization while selecting job placements. The system is designed for millions of cores and has been tested beyond 50,000 nodes. A plugin framework provides administration visibility and supports customized extensions. Health checks monitor faults and can mitigate them automatically; the fail-over architecture is designed to avoid a single point of failure and keep jobs running through failures. OpenPBS is self-hosted and free under the AGPL 3.0 open-source license, while PBS Pro is also dual licensed commercially. Public-sector organizations such as academic and research facilities generally choose the open-source license. Community help comes through a volunteer forum, without a guarantee of answers or bug fixes. OpenPBS is integrated into the OpenHPC software stack. The installation guide states that SELinux is not supported, and critical and high security fixes are delivered in the next major release.

Visit openpbs.org