--- title: "dstack vs aqueduct" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/dstackai-dstack-vs-runllm-aqueduct" tools: ["dstackai-dstack", "runllm-aqueduct"] --- # dstack vs aqueduct *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 aqueduct if aqueduct is a deprecated Go-based tool for orchestrating LLM and ML workloads across various cloud infrastructures with Kubernetes support. [dstack](https://dstack.ai/docs) reports 2.2k GitHub stars, 250 forks, and 66 open issues, last pushed Aug 23, 2026. [aqueduct](https://aqueducthq.com) has 517 stars, 20 forks, and 11 open issues, last pushed Jun 7, 2023. Figures are from public GitHub metadata via [dstack's repository](https://github.com/dstackai/dstack) and [aqueduct's repository](https://github.com/RunLLM/aqueduct). | | [dstack](/tools/dstackai-dstack.md) | [aqueduct](/tools/runllm-aqueduct.md) | | --- | --- | --- | | Tagline | Vendor-agnostic orchestration for AI workloads | Orchestrate LLM and ML workloads on any cloud infrastructure using Go. | | Stars | 2,219 | 517 | | Forks | 250 | 20 | | Open issues | 66 | 11 | | Language | Python | Go | | Adopt for | Vendor-agnostic AI workload orchestration tool supports GPU providers like NVIDIA and AMD across cloud, Kubernetes, and bare metal. | Aqueduct is a deprecated Go-based tool for orchestrating LLM and ML workloads across various cloud infrastructures with Kubernetes support. | | Persona | - | - | | Runtime | - | - | | License | MPL-2.0 | Apache-2.0 | | Categories | AI Agents, Inference & Serving, Model Training | Inference & Serving, LLM Frameworks, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [dstack](/tools/dstackai-dstack.md) | [aqueduct](/tools/runllm-aqueduct.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Dormant (18%) | | Days since push | 0d | 1152d | | Open issues (now) | 66 | 11 | | Stars delta | +27 (30d) | Unknown | | Open issues delta | +5 (30d) | Unknown | | Full report | [trust report](/tools/dstackai-dstack/trust.md) | [trust report](/tools/runllm-aqueduct/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: aqueduct - **Adopt for:** Aqueduct is a deprecated Go-based tool for orchestrating LLM and ML workloads across various cloud infrastructures with Kubernetes support. ## Choose when ### Choose dstack if… - dstack is primarily Python; aqueduct is Go. - License: dstack is MPL-2.0, aqueduct 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 aqueduct if… - aqueduct is primarily Go; dstack is Python. - License: aqueduct is Apache-2.0, dstack is MPL-2.0. - Tags unique to aqueduct: ai, data, data-science, kubernetes. - Also covers LLM Frameworks. - When you need to deploy legacy workflows that depend on Aqueduct's specific implementation of custom ops for resource allocation and training. ## 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 aqueduct - Avoid if active project maintenance or community support is required as Aqueduct is no longer maintained. - Skip this tool for new projects focusing on state-of-the-art ML orchestration, opting instead for actively supported alternatives. ## Common questions ### What is the difference between dstack and aqueduct? dstack: Vendor-agnostic orchestration for AI workloads. aqueduct: Orchestrate LLM and ML workloads on any cloud infrastructure using Go.. See the comparison table for live GitHub stats and shared categories. ### When should I choose dstack over aqueduct? Choose dstack over aqueduct when dstack is primarily Python; aqueduct is Go; License: dstack is MPL-2.0, aqueduct 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 aqueduct over dstack? Choose aqueduct over dstack when aqueduct is primarily Go; dstack is Python; License: aqueduct is Apache-2.0, dstack is MPL-2.0; Tags unique to aqueduct: ai, data, data-science, kubernetes; Also covers LLM Frameworks; When you need to deploy legacy workflows that depend on Aqueduct's specific implementation of custom ops for resource allocation and training. ### 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 aqueduct? Avoid if active project maintenance or community support is required as Aqueduct is no longer maintained. Skip this tool for new projects focusing on state-of-the-art ML orchestration, opting instead for actively supported alternatives. ### Is dstack or aqueduct more popular on GitHub? dstack has more GitHub stars (2,219 vs 517). Stars measure visibility, not whether either tool fits your constraints. ### Are dstack and aqueduct open source? Yes - both are open-source projects on GitHub (dstack: MPL-2.0, aqueduct: Apache-2.0). ### Where can I find alternatives to dstack or aqueduct? GraphCanon lists graph-backed alternatives at [dstack alternatives](/tools/dstackai-dstack/alternatives) and [aqueduct alternatives](/tools/runllm-aqueduct/alternatives) ([dstack markdown twin](/tools/dstackai-dstack/alternatives.md), [aqueduct markdown twin](/tools/runllm-aqueduct/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-runllm-aqueduct.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, dstack or aqueduct? dstack: Very active. aqueduct: Dormant. 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 aqueduct? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [dstack trust report](/tools/dstackai-dstack/trust); [aqueduct trust report](/tools/runllm-aqueduct/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/_