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TORQUE Resource Manager

Free#18 of 21 in GPU Cluster Management Software

TORQUE Resource Manager: A free, Linux-only resource manager for GPU batch and interactive cluster workloads. Ranked #18 of 21 in GPU Cluster Management Software by our editors (7.3/10); pricing: Free plan; best for traditional Linux batch clusters with GPUs.

7.3/10Editor score
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TORQUE Resource Manager7.3 Visit TORQUE

At a glance

  • Editor score
    7.3 / 10
  • Pricing
    Free plan
  • Best for
    Traditional Linux batch clusters with GPUs
  • Free plan
    Yes
  • Paid from
    Free
  • Deployment model
    Self_hosted
  • Facts checked
    22 Sep 2026
TORQUE Resource Manager screenshot

  • Where it wins

    • Supports batch, interactive jobs, queues, job arrays, and GPU requests
    • Cgroups manage CPU, memory, cpuset, and GPU device resources
    • Open source, self-hosted, and free to deploy

  • Where it doesn't

    • Linux is the only listed platform
    • Moab is the listed integration for scheduling and administration
    • No AI features or verified Kubernetes support

Our verdict on TORQUE Resource Manager

TORQUE Resource Manager is an open-source, self-hosted resource manager for distributed computing clusters. It is designed for teams operating traditional Linux infrastructure that need to submit and control batch workloads, provide interactive execution, route jobs through queues, and allocate GPU resources. Batch submission and execution use qsub, while qsub -I supports interactive jobs. Compute-node configuration, resource properties, queue defaults, and resource limits give administrators control over how cluster capacity is assigned.

The published model is open source with a free plan, so TORQUE fits organizations that prefer to operate cluster software on their own infrastructure rather than adopt a hosted service. Its workload coverage includes both batch and interactive execution, with job arrays and concurrent slot limits for repeated workloads. Queue-based routing and administration, GPU requests, and resource limits support structured scheduling policies. Cgroups-based controls extend that management to CPU, memory, cpuset, and GPU devices, making the product a focused option for resource governance inside Linux clusters.

TORQUE’s ecosystem is narrow: Moab Workload Manager is the listed integration, adding scheduling and administration capabilities, while Moab integration can also collect GPU metrics. That combination suits teams already centered on Linux cluster operations and queue-based scheduling. It is less suitable for organizations seeking broad platform integrations, a hosted deployment, AI-specific features, or a Kubernetes-centered operating model. Choose TORQUE when open-source control and traditional cluster resource management are priorities; consider an alternative when broader ecosystem coverage or a different deployment platform matters more.

Your product? Our editors can test TORQUE Resource Manager in depth and publish a review, labelled as paid · from $149/mo →

TORQUE Resource Manager pricing

Plans Free planFree Free to use — no paid tier required for the core job.
See plans on github.com

TORQUE Resource Manager fact sheet

Free planYes
Paid fromFree
Deployment modelSelf_hosted
Workload schedulingBoth
Kubernetes supportNot verified
Quota controlsYes
GPU utilization metricsYes
Cloud GPU supportNot verified
DeploymentSelf-hosted
PlatformsLinux
SupportCommunity, Docs
Built forMid-market, Enterprise (editorial estimate)
Integrations1 integrations: Moab Workload Manager
PricingFree plan
Websitegithub.com
Facts checked22 Sep 2026

TORQUE Resource Manager integrations

TORQUE Resource Manager lists 1 integrations on its own site.

  • Moab Workload Manager

Alternatives to TORQUE Resource Manager

See all TORQUE Resource Manager alternatives →

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Featured on iTechGuides

Featured on iTechGuides — TORQUE Resource Manager 7.3/10

TORQUE Resource Manager is listed in our GPU Cluster Management Software directory. Add the badge to your site — it links back to this page.

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Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026

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