--- title: "dstack vs skypilot" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/dstackai-dstack-vs-skypilot-org-skypilot" tools: ["dstackai-dstack", "skypilot-org-skypilot"] --- # dstack vs skypilot *GraphCanon updated Aug 24, 2026* ## Verdict Pick dstack if vendor-agnostic AI workload orchestration tool supports GPU providers like NVIDIA and AMD across cloud, Kubernetes, and bare metal; pick skypilot if skyPilot is a Python-based platform for managing AI workloads across diverse cloud and on-premises environments. It supports deep learning tasks such as distributed training, hyperparameter tuning, and model serving. [dstack](https://dstack.ai/docs) reports 2.2k GitHub stars, 250 forks, and 66 open issues, last pushed Aug 23, 2026. [skypilot](https://skypilot.ai/) has 10k stars, 1.2k forks, and 344 open issues, last pushed Aug 7, 2026. Figures are from public GitHub metadata via [dstack's repository](https://github.com/dstackai/dstack) and [skypilot's repository](https://github.com/skypilot-org/skypilot). | | [dstack](/tools/dstackai-dstack.md) | [skypilot](/tools/skypilot-org-skypilot.md) | | --- | --- | --- | | Tagline | Vendor-agnostic orchestration for AI workloads | Run, manage, and scale AI workloads on any AI infrastructure. | | Stars | 2,219 | 10,456 | | Forks | 250 | 1,175 | | Open issues | 66 | 344 | | Language | Python | Python | | Adopt for | Vendor-agnostic AI workload orchestration tool supports GPU providers like NVIDIA and AMD across cloud, Kubernetes, and bare metal. | SkyPilot is a Python-based platform for managing AI workloads across diverse cloud and on-premises environments. It supports deep learning tasks such as distributed training, hyperparameter tuning, and model serving. | | Persona | - | - | | Runtime | - | - | | License | MPL-2.0 | Apache-2.0 | | Categories | AI Agents, Inference & Serving, Model Training | Developer Tools, Inference & Serving, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [dstack](/tools/dstackai-dstack.md) | [skypilot](/tools/skypilot-org-skypilot.md) | | --- | --- | --- | | Open issues (now) | 66 | 344 | | Stars delta | +27 (30d) | Unknown | | Open issues delta | +5 (30d) | Unknown | | Full report | [trust report](/tools/dstackai-dstack/trust.md) | [trust report](/tools/skypilot-org-skypilot/trust.md) | ## Decision facts: dstack - **Adopt for:** Vendor-agnostic AI workload orchestration tool supports GPU providers like NVIDIA and AMD across cloud, Kubernetes, and bare metal. ## Decision facts: skypilot - **Pricing:** freemium - SkyPilot operates under an open-source license (Apache-2.0) with core features available freely, while advanced optimizations and integrations may drive usage towards higher costs based on underlying云 - **Adopt for:** SkyPilot is a Python-based platform for managing AI workloads across diverse cloud and on-premises environments. It supports deep learning tasks such as distributed training, hyperparameter tuning, and model serving. ## Choose when ### Choose dstack if… - License: dstack is MPL-2.0, skypilot is Apache-2.0. - Tags unique to dstack: agent-skills, agentic-orchestration, amd, cloud. - Also covers AI Agents. - If your project requires support for multiple hardware vendors such as NVIDIA, AMD, TPU, or Tenstorrent ### Choose skypilot if… - License: skypilot is Apache-2.0, dstack is MPL-2.0. - Pricing: SkyPilot operates under an open-source license (Apache-2.0) with core features available freely, while advanced optimizations and integrations may drive usage towards higher costs based on underlying云. - Tags unique to skypilot: cloud-computing, cloud-management, cost-optimization, deep-learning. - Also covers Developer Tools. - skypilot ships Docker support for self-hosted deployment. - When you need to manage multiple cloud resources including Kubernetes clusters, Slurm, and over 20 different clouds along with on-premise servers. ## When NOT to use dstack - When sticking to single-vendor solutions where tightly integrated proprietary tools are preferred - If the project strictly avoids open-source components with Mozilla Public License (MPL-2.0) ## When NOT to use skypilot - Avoid SkyPilot if you are working exclusively on a single cloud platform without a need for multi-cloud resource management or optimization. - Not recommended if your primary requirement is a specialized training algorithm that lacks support within the Python environment or the limitations of existing SkyPilot capabilities. ## Common questions ### What is the difference between dstack and skypilot? dstack: Vendor-agnostic orchestration for AI workloads. skypilot: Run, manage, and scale AI workloads on any AI infrastructure.. See the comparison table for live GitHub stats and shared categories. ### When should I choose dstack over skypilot? Choose dstack over skypilot when License: dstack is MPL-2.0, skypilot is Apache-2.0; Tags unique to dstack: agent-skills, agentic-orchestration, amd, cloud; Also covers AI Agents; If your project requires support for multiple hardware vendors such as NVIDIA, AMD, TPU, or Tenstorrent. ### When should I choose skypilot over dstack? Choose skypilot over dstack when License: skypilot is Apache-2.0, dstack is MPL-2.0; Pricing: SkyPilot operates under an open-source license (Apache-2.0) with core features available freely, while advanced optimizations and integrations may drive usage towards higher costs based on underlying云; Tags unique to skypilot: cloud-computing, cloud-management, cost-optimization, deep-learning; Also covers Developer Tools; skypilot ships Docker support for self-hosted deployment; When you need to manage multiple cloud resources including Kubernetes clusters, Slurm, and over 20 different clouds along with on-premise servers. ### When should I avoid dstack? When sticking to single-vendor solutions where tightly integrated proprietary tools are preferred If the project strictly avoids open-source components with Mozilla Public License (MPL-2.0) ### When should I avoid skypilot? Avoid SkyPilot if you are working exclusively on a single cloud platform without a need for multi-cloud resource management or optimization. Not recommended if your primary requirement is a specialized training algorithm that lacks support within the Python environment or the limitations of existing SkyPilot capabilities. ### Is dstack or skypilot more popular on GitHub? skypilot has more GitHub stars (10,456 vs 2,219). Stars measure visibility, not whether either tool fits your constraints. ### Are dstack and skypilot open source? Yes - both are open-source projects on GitHub (dstack: MPL-2.0, skypilot: Apache-2.0). ### Where can I find alternatives to dstack or skypilot? GraphCanon lists graph-backed alternatives at [dstack alternatives](/tools/dstackai-dstack/alternatives) and [skypilot alternatives](/tools/skypilot-org-skypilot/alternatives) ([dstack markdown twin](/tools/dstackai-dstack/alternatives.md), [skypilot markdown twin](/tools/skypilot-org-skypilot/alternatives.md)), ranked by typed relationship edges rather than popularity votes. ### Is there a machine-readable version of this comparison? Yes. The markdown twin at [this comparison](/compare/dstackai-dstack-vs-skypilot-org-skypilot.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, dstack or skypilot? dstack: Very active. skypilot: Very active. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance. ### Where are the full trust reports for dstack and skypilot? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [dstack trust report](/tools/dstackai-dstack/trust); [skypilot trust report](/tools/skypilot-org-skypilot/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=dstackai-dstack`](/api/graphcanon/graph?tool=dstackai-dstack) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_