Powered by advanced AMD accelerators
and NVIDIA-accelerated computing
32 cloud data center regions
Create GPU-accelerated Kubernetes clusters that will power your most resource-intensive workloads anywhere in the world. This powerful combination empowers developers and innovators to build sophisticated AI and machine learning systems that can handle even the most complex challenges.
Deploy and scale Generative AI (GenAI) models quickly and efficiently, with the ability to use your proprietary data or trained model powered by the simple-to-manage Vultr Serverless Inference’s global acceleration.
Harness a wide variety of plug-and-play SaaS applications to make developing and deploying your cloud applications easier.
Visit Vultr MarketplaceBrowse the PaaS and SaaS offerings in our marketplace of pre-built Kubernetes containers to accelerate application development, deployment and optimization.
Read the datasheetVultr's strategic partnerships with leading IaaS, PaaS, and SaaS providers empower customers to build enterprise-grade cloud solutions without the cost, complexity, or lock-in of hyperscalers.
Learn more about the Vultr Cloud AllianceSchedule automatic backups, create server snapshots, set up flexible networking, and secure compute instances with on-demand firewall protection.
Review our FAQ and Vultr Cloud GPU Doc for more information.
A Cloud GPU works by providing access to GPU instances hosted in data centers. This enables users to run intensive computing tasks such as AI training, gaming, and rendering without needing a physical GPU.
When selecting a cloud GPU service, consider factors like GPU power, memory, pricing, and the specific workload (e.g., AI, rendering, or gaming).
A traditional GPU is a physical graphics card installed in a local machine, while a Cloud GPU is accessed remotely via cloud infrastructure, offering more scalability and flexibility.
Vultr offers some of the most competitive pricing in the industry for GPU-as-a-service, with transparent pay-as-you-go rates and no long-term contracts required. Unlike the hyperscalers, Vultr avoids complex, multi-layered pricing structures. Vultr makes it easy to deploy high-performance infrastructure without breaking your budget.
Vultr delivers bare metal access to the latest AMD and NVIDIA GPUs – without vendor lock-in, high egress costs, and hyperscaler billing complexity. Vultr also offers global availability, pre-configured AI/ML templates, and integration with industry-leading model training and inference tools. With a focus on performance, simplicity, and price predictability, Vultr is purpose-built for next-generation AI workloads.
Vultr Serverless Inference automatically provisions, scales, and shuts down GPU resources based on real-time demand. This lets developers deploy GenAI models – like LLMs and vision transformers – without managing infrastructure. With private GPU clusters, OpenAI-compatible APIs, and inference-optimized GPUs, Vultr provides a cost-effective, scalable platform for low-latency AI application delivery.
Reserved GPU servers on Vultr offer consistent, full-performance access to the entire GPU – ideal for training large models or running latency-sensitive inference. In contrast, on-demand instances may share resources and can be better suited for bursty, less intensive workloads. Reserved access gives users maximum control, stability, and throughput – key factors for enterprise AI operations.
A Cloud GPU works by providing access to GPU instances hosted in data centers. This enables users to run intensive computing tasks such as AI training, gaming, and rendering without needing a physical GPU.
Start your GPU-accelerated project now by signing up for a free Vultr account. Or, if you’d like to speak with us regarding your needs, please reach out.