--- title: "dstack vs dstack" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/dstack-tee-dstack-vs-dstackai-dstack" tools: ["dstack-tee-dstack", "dstackai-dstack"] --- # dstack vs dstack *GraphCanon updated Sep 20, 2026* ## Verdict Pick dstack if dstack is an open-source framework for confidential AI, offering secure execution environments using Intel TDX and AMD SEV-SNP technologies; pick dstack if dstack is a vendor-agnostic orchestration tool for AI workloads, including training, inference, and agentic tasks, across various hardware and environments. [dstack](https://dstack.org) reports 546 GitHub stars, 96 forks, and 79 open issues, last pushed Sep 18, 2026. [dstack](https://dstack.ai/docs) has 2.3k stars, 262 forks, and 64 open issues, last pushed Sep 17, 2026. Figures are from public GitHub metadata via [dstack's repository](https://github.com/Dstack-TEE/dstack) and [dstack's repository](https://github.com/dstackai/dstack). | | [dstack](/tools/dstack-tee-dstack.md) | [dstack](/tools/dstackai-dstack.md) | | --- | --- | --- | | Tagline | Open framework for confidential AI | Vendor-agnostic orchestration for training, inference and agentic workloads | | Stars | 546 | 2,253 | | Forks | 96 | 262 | | Open issues | 79 | 64 | | Language | Rust | Python | | Adopt for | Dstack is an open-source framework for confidential AI, offering secure execution environments using Intel TDX and AMD SEV-SNP technologies. | dstack is a vendor-agnostic orchestration tool for AI workloads, including training, inference, and agentic tasks, across various hardware and environments. | | Persona | - | - | | Runtime | - | - | | License | Dstack is licensed under Apache-2.0, with embedded and third-party components retaining their own licenses. | dstack is licensed under the Mozilla Public License 2.0, which is an open-source license. | | Categories | Developer Tools, Model Training | AI Agents, Inference & Serving, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [dstack](/tools/dstack-tee-dstack.md) | [dstack](/tools/dstackai-dstack.md) | | --- | --- | --- | | Open issues (now) | 79 | 64 | | Stars delta | +27 (30d) | +61 (30d) | | Open issues delta | -99 (30d) | +3 (30d) | | Full report | [trust report](/tools/dstack-tee-dstack/trust.md) | [trust report](/tools/dstackai-dstack/trust.md) | ## Decision facts: dstack - **Hosting:** self hosted - Supports self-hosted TDX machines and managed infrastructure via Phala Cloud. - **Requirements:** Requires Docker; Requires TEE hardware for full functionality, but offers a no-TEE mode for development. - **Adopt for:** Dstack is an open-source framework for confidential AI, offering secure execution environments using Intel TDX and AMD SEV-SNP technologies. - **License detail:** Dstack is licensed under Apache-2.0, with embedded and third-party components retaining their own licenses. ## Decision facts: dstack - **Pricing:** freemium - The core functionality of dstack is free and open-source under the Mozilla Public License 2.0. Additional services or support may be available for a fee. - **Requirements:** Requires Docker; Requires Git and OpenSSH for CLI installation and configuration. - **Adopt for:** dstack is a vendor-agnostic orchestration tool for AI workloads, including training, inference, and agentic tasks, across various hardware and environments. - **License detail:** dstack is licensed under the Mozilla Public License 2.0, which is an open-source license. ## Choose when ### Choose dstack if… - dstack is primarily Rust; dstack is Python. - License: dstack is Apache-2.0, dstack is MPL-2.0. - Supports self-hosted TDX machines and managed infrastructure via Phala Cloud. - Requirements: Requires Docker; Requires TEE hardware for full functionality, but offers a no-TEE mode for development.. - Tags unique to dstack: confidential-ai, confidential-computing, intel-tdx, private-ai. - Also covers Developer Tools. - When you need to ensure secure execution environments for AI models using Intel TDX or AMD SEV-SNP technologies. ### Choose dstack if… - dstack is primarily Python; dstack is Rust. - License: dstack is MPL-2.0, dstack is Apache-2.0. - Pricing: The core functionality of dstack is free and open-source under the Mozilla Public License 2.0. Additional services or support may be available for a fee.. - Requirements: Requires Docker; Requires Git and OpenSSH for CLI installation and configuration.. - Tags unique to dstack: agent-skills, agentic-orchestration, amd, cloud. - Also covers AI Agents, Inference & Serving. - When you need orchestration for AI workloads that can run on a variety of hardware like NVIDIA, AMD, TPU, and Tenstorrent, and across different environments such as clouds, Kubernetes, and bare metal. ## When NOT to use dstack - If your project does not require confidential computing and you are looking for a more general-purpose AI development tool. - When you do not have access to TEE hardware and are unwilling to use the no-TEE mode with swtpm for development. - If you prefer a framework that does not require setting up a secure execution environment and can operate without Intel TDX or AMD SEV-SNP. ## When NOT to use dstack - If you are looking for a tool that is tightly integrated with a specific cloud provider or hardware vendor, as dstack is designed to be vendor-agnostic. - When your project strictly requires proprietary licensing, as dstack is licensed under the Mozilla Public License 2.0, which is open source. - If your team does not have the capability to install and configure the dstack CLI, which requires Git and OpenSSH, and involves setting up a server and configuring it with a user token and project URL ## Common questions ### What is the difference between dstack and dstack? dstack: Open framework for confidential AI. dstack: Vendor-agnostic orchestration for training, inference and agentic workloads. See the comparison table for live GitHub stats and shared categories. ### When should I choose dstack over dstack? Choose dstack over dstack when dstack is primarily Rust; dstack is Python; License: dstack is Apache-2.0, dstack is MPL-2.0; Supports self-hosted TDX machines and managed infrastructure via Phala Cloud; Requirements: Requires Docker; Requires TEE hardware for full functionality, but offers a no-TEE mode for development.; Tags unique to dstack: confidential-ai, confidential-computing, intel-tdx, private-ai; Also covers Developer Tools; When you need to ensure secure execution environments for AI models using Intel TDX or AMD SEV-SNP technologies. ### When should I choose dstack over dstack? Choose dstack over dstack when dstack is primarily Python; dstack is Rust; License: dstack is MPL-2.0, dstack is Apache-2.0; Pricing: The core functionality of dstack is free and open-source under the Mozilla Public License 2.0. Additional services or support may be available for a fee.; Requirements: Requires Docker; Requires Git and OpenSSH for CLI installation and configuration.; Tags unique to dstack: agent-skills, agentic-orchestration, amd, cloud; Also covers AI Agents, Inference & Serving; When you need orchestration for AI workloads that can run on a variety of hardware like NVIDIA, AMD, TPU, and Tenstorrent, and across different environments such as clouds, Kubernetes, and bare metal. ### When should I avoid dstack? If your project does not require confidential computing and you are looking for a more general-purpose AI development tool. When you do not have access to TEE hardware and are unwilling to use the no-TEE mode with swtpm for development. If you prefer a framework that does not require setting up a secure execution environment and can operate without Intel TDX or AMD SEV-SNP. ### When should I avoid dstack? If you are looking for a tool that is tightly integrated with a specific cloud provider or hardware vendor, as dstack is designed to be vendor-agnostic. When your project strictly requires proprietary licensing, as dstack is licensed under the Mozilla Public License 2.0, which is open source. If your team does not have the capability to install and configure the dstack CLI, which requires Git and OpenSSH, and involves setting up a server and configuring it with a user token and project URL ### Is dstack or dstack more popular on GitHub? dstack has more GitHub stars (2,253 vs 546). Stars measure visibility, not whether either tool fits your constraints. ### Are dstack and dstack open source? Yes - both are open-source projects on GitHub (dstack: Apache-2.0, dstack: MPL-2.0). ### Where can I find alternatives to dstack or dstack? GraphCanon lists graph-backed alternatives at [dstack alternatives](/tools/dstack-tee-dstack/alternatives) and [dstack alternatives](/tools/dstackai-dstack/alternatives) ([dstack markdown twin](/tools/dstack-tee-dstack/alternatives.md), [dstack markdown twin](/tools/dstackai-dstack/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/dstack-tee-dstack-vs-dstackai-dstack.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, dstack or dstack? dstack: Very active. dstack: 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 dstack? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [dstack trust report](/tools/dstack-tee-dstack/trust); [dstack trust report](/tools/dstackai-dstack/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=dstack-tee-dstack`](/api/graphcanon/graph?tool=dstack-tee-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/_