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SkyPilot vs Slurm Workload Manager

SkyPilot

skypilot.ai

Slurm Workload Manager

slurm.schedmd.com

Side by side

FigureSkyPilotSlurm Workload Manager
Price from—Free
Free plan—Yes
Free trial——
Open source——
WebYes—
LinuxYesYes
APIYesYes
Self-hostedYesYes
Plans published01
Spec score · GPU Cluster Management Software6.9 (#16)7.5 (#11)
PurposeSkyPilot is an AI compute platform for managing Kubernetes, Slurm, VMs, on-premises systems, and cloud resources through one interface.Slurm is an open-source, fault-tolerant, highly scalable cluster management and job scheduling system for large and small Linux clusters.

Plans

SkyPilot

No plans published.

SkyPilot pricing →

Slurm Workload Manager

  • SlurmFree

Slurm Workload Manager pricing →

In their own words

SkyPilot

SkyPilot is an AI compute platform that manages Kubernetes, Slurm, virtual machines, on-premises systems and cloud resources through one interface. Listed workloads include development, pre-training, post-training and reinforcement learning, batch inference, sandboxes and inference endpoints. Scheduling provides priority queues, GPU sharing, quotas and intelligent placement across workloads. Fleet health checks can run proactively or reactively, with automatic remediation for GPU and NCCL faults. Integrations include AWS, GCP, Azure, Nebius, CoreWeave, Lambda, RunPod, Kubernetes, Slurm and on-premises infrastructure. SkyPilot can run standalone or connect to a remote API server for multi-user collaboration. Enterprise controls include SSO onboarding, RBAC, workspaces, policy enforcement, a unified dashboard, idle-compute stopping and cost reporting. Deployment options include BYOC, BYOK, private VPC and air-gapped environments. The project began as open source at UC Berkeley's Sky Computing Lab and is offered as open source. Documentation says Slurm support remains under active development and SkyServe on Slurm is not supported.

Visit skypilot.ai

Slurm Workload Manager

Slurm Workload Manager is free, open-source software for allocating compute resources and scheduling work across Linux clusters. It starts and monitors jobs on allocated nodes and manages queues of pending work. Optional plugins add accounting, advanced reservations, gang and backfill scheduling, topology-aware resource selection, resource limits, and multifactor job prioritization. The system uses a central slurmctld manager and slurmd daemons on compute nodes; accounting and REST components are optional. GPU plugins support NVIDIA, AMD, Intel, AWS Trainium, and AWS Inferentia accelerators, along with NVIDIA MPS and GPU sharing. Accounting can use MySQL or MariaDB and can record data in a text file, directly in a database, or through slurmdbd for multiple clusters. Slurmrestd provides REST access, but the API is not designed for direct internet exposure and supports only unencrypted HTTP. Linux is thoroughly tested on arm64, ppc64, and x86_64; FreeBSD and NetBSD support is limited, and macOS is unsupported. Deployment is self-hosted.

Visit slurm.schedmd.com