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Author: SkyPilot Team

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Programming Language

Python :: 3.9
Python :: 3.10
Python :: 3.11
Python :: 3.12
Python :: 3.13

License

OSI Approved :: Apache Software License

Operating System

OS Independent

Topic

Software Development :: Libraries :: Python Modules
System :: Distributed Computing

SkyPilot

Manage all your AI compute

SkyPilot is a system to run, manage, and scale AI workloads on any AI infrastructure.

SkyPilot gives AI teams a simple interface to run jobs on any infra. Infra teams get a unified control plane to manage any AI compute — with advanced scheduling, scaling, and orchestration.

:fire: News :fire:

[Jun 2026] Announcing SkyPilot Sandboxes: run untrusted, LLM-generated code on the Kubernetes clusters you already own. Learn more, join early access
[May 2026] How Multiverse doubled their GPU utilization with SkyPilot: case study
[Apr 2026] Introducing GPU Compass: One dashboard to browse, compare pricing, and launch across every GPU cloud. Try it at gpus.skypilot.co.
[Apr 2026] Research-Driven Agents: Agents read arxiv papers before coding, landed 5 llama.cpp kernel fusions and +15% faster flash attention in ~3 hours for ~$29: blog, HackerNews
[Mar 2026] Scaling Karpathy's Autoresearch: Autoresearch runs 1 experiment at a time. We gave it 16 GPUs and let it run in parallel: blog, HackerNews
[Mar 2026] How H Company Unlocked Online RL and Unified their AI Platform: case study
[Mar 2026] SkyPilot v0.12 released: Slurm Support, Job Groups for RL, Agent Skill, Recipes, Pool Autoscaling for Batch Inference, 7x Data Mounting, and More: Release notes
[Mar 2026] SkyPilot Agent Skills: GPU access and job management for AI agents: docs
[Jan 2026] Shopify case study: Shopify runs all AI training workloads on SkyPilot: case study

Overview

SkyPilot is easy to use for AI users:

Quickly spin up compute on your own infra
Environment and job as code — simple and portable
Easy job management: queue, run, and auto-recover many jobs

SkyPilot makes Kubernetes easy for AI & Infra teams:

Slurm-like ease of use, cloud-native robustness
Local dev experience on K8s: SSH into pods, sync code, or connect IDE
Turbocharge your clusters: gang scheduling, multi-cluster, and scaling

SkyPilot unifies multiple clusters, clouds, and hardware:

One interface to use reserved GPUs, Kubernetes clusters, Slurm clusters, or 20+ clouds
Flexible provisioning of GPUs, TPUs, CPUs, with smart failover
Team deployment and resource sharing

SkyPilot maximizes GPU fleet utilization:

Autostop: automatic cleanup of idle resources
Binpacking: workload binpacking on shared clusters
Intelligent scheduler: automatically schedule on the most available infra

SkyPilot supports your existing GPU, TPU, and CPU workloads, with no code changes.

Install with uv (also supported: pip, nightly, from source)

# Choose your clouds:
uv pip install "skypilot[kubernetes,aws,gcp,azure,oci,nebius,lambda,runpod,fluidstack,paperspace,cudo,ibm,scp,seeweb,shadeform,verda]"

To use SkyPilot directly with your agent (Claude Code, Codex, etc.), install the SkyPilot Skill. Tell your agent:

Fetch and follow https://github.com/skypilot-org/skypilot/blob/HEAD/agent/INSTALL.md to install the skypilot skill

SkyPilot

Current supported infra: Kubernetes, Slurm, AWS, GCP, Azure, OCI, CoreWeave, Nebius, Lambda Cloud, RunPod, Fluidstack, Cudo, Digital Ocean, Paperspace, Cloudflare, Samsung, IBM, Vast.ai, VMware vSphere, Seeweb, Prime Intellect, Shadeform, Verda Cloud, VastData, Crusoe.

SkyPilot

Getting started

Install SkyPilot in 1 minute. Then, launch your first cluster in 2 minutes in Quickstart.

SkyPilot is BYOC: Everything is launched within your cloud accounts, VPCs, and clusters.

Benefits of SkyPilot on Kubernetes

SkyPilot makes Kubernetes AI-native.

It turbocharges your existing Kubernetes clusters by accelerating AI/ML velocity:

AI-friendly interface to launch jobs and deployments
Much simplified interactive dev for K8s (SSH / sync code / connect IDE to pods)

...and optimizing GPU scheduling, utilization, and scaling:

Advanced scheduling: Gang scheduling, multi-node jobs, and queueing
Multi-cluster support: Bring all your clusters under one control plane
Multi-cloud support: One consistent interface to manage many providers

See SkyPilot vs Vanilla Kubernetes and this blog post for more details.

SkyPilot in 1 minute

A SkyPilot task specifies: resource requirements, data to be synced, setup commands, and the task commands.

Once written in this unified interface (YAML or Python API), the task can be launched on any available infra (Kubernetes, Slurm, cloud, etc.). This avoids vendor lock-in, and allows easily moving jobs to a different provider.

Task	Examples
Training	Verl, Finetune Llama 4, TorchTitan, PyTorch, DeepSpeed, NeMo, Ray, Unsloth, Jax/TPU, OpenRLHF
Serving	vLLM, SGLang, Ollama
Models	DeepSeek-R1, Llama 4, Llama 3, CodeLlama, Qwen, Kimi-K2, Kimi-K2-Thinking, Mixtral
AI apps	RAG, vector databases (ChromaDB, CLIP)
Common frameworks	Airflow, Jupyter, marimo

skypilot-nightly 1.0.0.dev20260731

Programming Language

License

Operating System

Topic

Manage all your AI compute

Overview

Getting started

Benefits of SkyPilot on Kubernetes

SkyPilot in 1 minute

Runnable examples

Learn more

Questions and feedback

Contributing

Wheel compatibility matrix

Files in release