Unify GPU orchestration for AI development and deployment
dstack helps AI and machine learning teams manage their GPU resources across cloud, Kubernetes, and on-prem environments. It streamlines everything from coding and debugging to training and deploying models, reducing costs and avoiding vendor lock-in. With easy setup and open-source options, it lets you focus on building AI solutions instead of wrestling with infrastructure.
Connect desktop IDEs to cloud or on-prem GPUs for development.
Run single-node and distributed ML jobs with simple configuration.
Deploy models as auto-scaling, secure endpoints easily.
Integrate with various GPU providers and avoid lock-in.
Reduce GPU costs by 3-7x through efficient orchestration.
dstack fully replaces Slurm by handling job submission, queuing, retries, GPU health checks, and scheduling for single-node and distributed runs, while adding dev environments, services, and fleets for a unified ML platform.
dstack is purpose-built for ML with a lightweight interface, whereas Kubernetes is general-purpose; dstack simplifies ML workflows with specific configurations for dev environments, tasks, and services, and can run on Kubernetes if needed.
Yes, you can connect existing Kubernetes clusters using the Kubernetes backend to run dev environments, tasks, and services on them.
Use dstack to accelerate ML development with a simple interface for spinning up dev environments, running tasks, and deploying services without infrastructure overhead, while reducing costs and ensuring interoperability.
This tool is best for:
Explore more niche AI tool websites by clicking on a tag* (works only if it has enough tools).
dstack can be integrated with these apps and services:
Recent data shows that dstack has 4.7K monthly visits (8.6% increase from the previous month), 46.0% bounce rate, and average 1.57 pages per visit.
Traffic is primarily driven by 6 different sources, with users from 5 countries worldwide, led by United States contributing 39% of total traffic. SEO performance is shown by 5 tracked keywords, with "dstack" being the top-performing keyword with 510 monthly searches. See below for more info.
Monthly Visits
4.7K
Pages per Visit
1.57
Bounce Rate
46.0%
Average Time on Site
12s
| SEO Keyword | Volume | CPC |
|---|---|---|
| dstack | 510 | - |
| dstack mount volume | 70 | - |
| dstack project setup | 60 | - |
| dstack volume data size | 60 | - |
| dstack volumes size | 60 | - |
| Source | Traffic Share |
|---|---|
| Direct | 41% |
| Search | 32% |
| Social | 6% |
| Referrals | 20% |
| Paid Referrals | 1% |
| Country Name | Traffic Share |
|---|---|
 | 39% |
 | 24% |
 | 15% |
 | 14% |
 | 8% |
Promote your Toolbit Launch by using the badge on your website. It can be inserted on your home page or footer easily.
How to use: Simply copy and paste the embed code into your homepage or footer HTML to display it instantly and build community support.
Stay updated with the latest insights, tutorials, and news about AI tools and technology.
Google's Nano Banana (Gemini 2.5 Flash Image) makes AI photo editing as easy as talking! Transform images with simple text commands while keeping faces consistent. Free through Google AI Studio - no technical skills needed. Perfect for creators, students & businesses.
Best 2025 Comparison Guide - After months of testing ChatGPT, Perplexity, and Claude, here's when to use each AI tool. Complete comparison with pricing, strengths, and real-world examples to help you choose the right AI assistant.
Compare Suno AI vs ElevenLabs in 2025: Suno is good at music generation ($8-30/month), while ElevenLabs leads voice synthesis ($5-99/month). Both offer free tiers and serve different content creation needs.
GitHub Copilot, Cursor, and Claude Code have Changed AI coding in 2025. Compare features, pricing, and real-world performance to choose the best AI coding assistant for your development workflow.
