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Try NowWhat is dstack?
dstack is an open-source control plane for provisioning compute and running AI workloads across clouds, Kubernetes, and bare-metal clusters. Built for both engineers and AI agents, it simplifies infrastructure orchestration for training, inference, and sandbox environments. The tool supports NVIDIA, AMD, TPU, and Tenstorrent GPUs, and integrates natively with major cloud providers and open-source frameworks. dstack eliminates the need for Kubernetes or Slurm by providing a lightweight, container-first interface. Users can define fleets, dev environments, tasks, and services using simple YAML configurations. It is designed to reduce GPU costs through smart orchestration, right-sizing, and support for spot and reserved instances. dstack is trusted by over 100 AI-first companies and is ideal for teams that need to scale ML experiments without infrastructure overhead.
AI Tool Review Summary
4.5/5
High, consistent, and on-brand
Clean and minimal
LLMNLPComputer Vision
Unified control plane for provisioning compute and running AI workloads across diverse GPU infrastructure.
Works with any cloud, Kubernetes, or bare-metal cluster; integrates with VS Code, Cursor, Windsurf, and OpenAI-compatible endpoints.
Freemium with paid tiers
Features with the highest value for users are highlighted here.
Multi-GPU vendor support (NVIDIA, AMD, TPU, Tenstorrent)
Cloud, Kubernetes, and bare-metal provisioning
Fleet management with auto-scaling and idle deprovisioning
Dev environments with VS Code, Cursor, Windsurf integration
Distributed training and batch job scheduling
High-performance inference serving with OpenAI-compatible API
Cost optimization via spot and reserved capacity
SSH fleets for on-prem GPU clusters
How It Works
1
Install dstack
Install dstack on your laptop using uv or deploy the Docker image anywhere.
2
Configure backends
Connect your cloud accounts, Kubernetes clusters, or SSH fleets via simple YAML.
3
Define workloads
Create YAML configurations for dev environments, tasks, or services.
4
Run and scale
Apply the configuration to provision compute and run workloads with automatic scaling.
AI Engineers
ML Researchers
DevOps Teams
Data Scientists
Startups
Enterprise AI Teams
AI Agents
Academic Researchers
MLE Teams
Infrastructure Managers
Open Source
$0/free
Self-hosted All core features Community support
Sky Free
$0/monthly
Hosted by dstack $5 GPU credits Bring your own clouds
Popular
Sky Pro
Usage-based/monthly
Hosted by dstack GPU marketplace access Priority support
Enterprise
Custom/yearly
Self-hosted SSO Air-gapped Dedicated support
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Pros & Cons
Simplifies AI infrastructure orchestration without requiring Kubernetes or Slurm expertise. Supports a wide range of GPU vendors and deployment options, enabling flexibility and cost savings.
May have a learning curve for users unfamiliar with YAML configuration. Advanced features like disaggregated inference may require additional setup.
FAQs
Just Launched
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Rating
5.0
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Quick dstack Comparision
Side-by-side with top alternatives in this category.
| Tool | Rating | Visits / mo | Global rank | Category rank | Engagement | Bounce | Top market | Starts at | Free tier | Integrations | Action |
|---|---|---|---|---|---|---|---|---|---|---|---|
 dstackAI Code Assistant | 9.4K | #2,433,667 | #21,310 | 14s1.5 pages | US(29%)#1,527,758 | $0 | 2+ | View | |||
 GitHub CopilotAI Code Assistant | 631.0M | #47 | #4 | 6m 32s6.1 pages | US(20%)#70 | $0 | 1 | View | |||
 Blackbox AIAI Code Assistant | 5.1M | #9,015 | #123 | 4m 1s5.0 pages | IN(19%)#3,193 | $0 | 1 | View | |||
 CoddyAI Code Assistant | 2.4M | #17,103 | #57 | 5m 42s7.0 pages | US(12%)#1,453 | $0 | — | View | |||
 AnacondaAI Code Assistant | 2.2M | #18,878 | #393 | 4m 12s5.9 pages | US(17%)#17,989 | $0 | 1 | View |
Analytics of Agentic orchestration for AI infrastructure
Website traffic and keyword analysis.
Live dataFeb 2026 – Apr 2026
Monthly visits
9.41K
↓ -20.4% vs prior month
Avg. visit duration
00:00:13
M 4 2026 snapshot
Pages / visit
1.48
M 4 2026 snapshot
Bounce rate
54.85%
Lower is better
All traffic · Worldwide
Weekly estimate · Feb 1, 2026 – Apr 29, 2026
Peak week: 4.93K (Feb 1, 2026)Low week: 1.88K (Apr 1, 2026)WoW: 0.0%Derived from monthly estimates · SimilarWeb-equivalent
Release History
0 releases published
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