by dstackai · Agent Tool · ★ 2.2k
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is a unified control plane for GPU provisioning and orchestration that works with any GPU cloud, Kubernetes, or on-prem clusters. It streamlines development, training, and inference, and is compatible with any hardware, open-source tools, and frameworks. Accelerators supports , , , , and accelerators out of the box. Latest news ✨ [2025/12] dstack 0.20.0: Fleet-first UX, Events, and more [2025/11] dstack 0.19.38: Routers, SGLang Model Gateway integration [2
| Stars | 2,208 |
| Forks | 244 |
| Language | Python |
| Category | Agent Tool |
| License | MPL-2.0 |
| Quality Score | 67.8345946037712/100 |
| Open Issues | 66 |
| Last Updated | 2026-08-07 |
| Created | 2022-01-04 |
| Platforms | docker, k8s, python |
| Est. Tokens | ~14k |
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dstack is Vendor-agnostic orchestration for training, inference and agentic workloads across NVIDIA, AMD, TPU, and Tenstorrent on clouds, Kubernetes, and bare metal.. It is categorized as a Agent Tool with 2.2k GitHub stars.
dstack is primarily written in Python. It covers topics such as agent-skills, agentic-orchestration, amd.
You can find installation instructions and usage details in the dstack GitHub repository at github.com/dstackai/dstack. The project has 2.2k stars and 244 forks, indicating an active community.
dstack is released under the MPL-2.0 license, making it free to use and modify according to the license terms.
The top alternatives to dstack on Agent Skills Hub include mirrord, Kiln, mcp-context-forge. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.