#16 in Orchestration & SchedulingUpdated 2026-08

dstack

by dstack · Open-source orchestration for GPU clouds, Kubernetes and on-prem clusters

45.9 — BenchRank score out of 100

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Overview

dstack is an open-source control plane for AI workloads that runs them across GPU clouds, Kubernetes clusters and bare-metal or VM hosts reached over SSH. You run the server, add backend credentials in a config file, and manage fleets, dev environments, tasks, services and volumes through a CLI, UI and API. A hosted option, dstack Sky, provides marketplace GPUs.

Best for: AI teams running training and inference across mixed GPU clouds, Kubernetes and on-prem hosts.
Pricing: No plan prices are published: the core is open source and self-installed, while the Enterprise edition and hosted dstack Sky are handled via demo or contact, with marketplace GPU rates shown from $0.80–1.40/hr for an L40S 48GB up to $6.00–12.00/hr for a B300 288GB.
Runs on: Self-hostedCLI

Strengths and trade-offs

Strengths

Open source; runs in your own cloud accounts or on your hardware
One control plane for fleets, dev envs, tasks, services, volumes
Works with NVIDIA, AMD, Tenstorrent and TPU accelerators
Hosted dstack Sky marketplace if you have no cloud accounts

Trade-offs

No prices published for the Enterprise edition or dstack Sky
SSO and air-gapped setup are Enterprise-only, not open source
Built for containerised workloads only
You install and run the dstack server yourself

How this score is made up

Each dimension is scored out of 100 and combined into the headline score using fixed weights.

MCP support: 0 out of 100
API quality: 30 out of 100
Documentation: 90 out of 100
Agent friendliness: 59 out of 100
Changelog: 100 out of 100
Marketing site structure: 45 out of 100
Operational trust: 15 out of 100

Measured, but not part of the score

Useful to know, but not a mark for or against the product — so these do not affect the ranking.

Openness: 85 out of 100
Maintenance: 100 out of 100

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