VULTR Review 2025: Affordable Cloud Computing With a Practical Twist

Vultr appeals to builders who want root access and the freedom to choose their own operating system, install software, attach storage and automate deployments. There’s no proprietary control panel locking you in. If you like to script and configure servers yourself, that autonomy is a big advantage.

Vultr now provides the NVIDIA HGX B200, which is currently available for highly powerful and efficient AI training and inference.

The new VX1™ Cloud Compute line, introduced in 2024, delivers up to 82 % better price‑performance than similar plans from major clouds. Each instance boots from NVMe storage and provides dedicated CPU time. Networking speeds between 15 and 50 Gbps per host help reduce latency. These improvements make VX1 the default option for most new deployments.

All services are billed hourly up to a monthly cap. You can create a server for a few hours and pay only for those hours. Optional extras are clearly priced and because there are no long‑term contracts, scaling up or down is simple.

With over 30 data centres spread across North America, South America, Europe, Asia, Australia and even Africa, Vultr lets you locate your servers near your visitors. That matters because proximity lowers latency and improves user experience — your website loads quicker when it’s hosted closer to the people who use it. Each deployment allows you to pick from these locations in the control panel, giving you fine control over where your resources live. High‑end providers like AWS and GCP offer similar reach but at far higher cost.

Core services and features

VX1 Cloud Compute is Vultr’s main compute option and the one most users gravitate toward. It runs on fast NVMe storage, gives dedicated CPU power, and keeps networking consistent, which makes it a strong match for everyday websites, SaaS projects, APIs and growing online stores. Memory-optimised plans work better for data-heavy applications like analytics tools and busy databases.

Vultr still offers its older High-Frequency Compute tier, but because those CPUs are shared across users, VX1 generally delivers smoother performance for new deployments. Bare-metal servers are available when you need complete physical control or extremely predictable performance, though keep in mind that Windows licences add an extra fee.

For application data and expandable disk space, Block Storage fits naturally with most VPS setups — you can start small and increase volume size as your app grows without migrating servers.

Object Storage is better suited for large media libraries, backups, logs and static files. Every plan includes 1 TB of storage and 1 TB outbound bandwidth, which is a convenient starting point for content-heavy sites or apps with frequent asset downloads. Extra storage is billed per GB, and outbound bandwidth beyond the included limit is inexpensive at $0.01 per GB, making storage scaling relatively predictable.

Vultr’s Container Registry integrates directly with its Kubernetes Engine, so teams working with Docker and microservices can store, version and deploy images effortlessly. The free tier is a handy way for developers to experiment, while the paid tiers offer more room for production workloads. Vultr also provides managed MySQL, PostgreSQL and Redis databases along with a managed Kubernetes control plane, which helps small teams adopt container-based architectures without taking on full DevOps overhead.

Load Balancers ($10/month) make it simple to build reliable, redundant setups — handy when your traffic grows or uptime becomes more critical. Features like SSL termination, sticky sessions and health checks help keep busy applications stable. DDoS Protection ($10/month) adds a layer of safety for public-facing apps, especially e-commerce sites or anything dealing with sign-ins.

Automatic Backups increase your server cost by 20%, but they’re valuable insurance once your data becomes meaningful. Vultr also includes floating IPs, private networking, BGP peering, API key rotation, and firewall rules by default. These tools give developers fine-grained control over routing, isolation and security policies, though they still require careful configuration and routine maintenance.

GPU instances are available for workloads that genuinely benefit from parallel processing — machine learning, rendering, simulations or heavy video processing. Because GPU billing uses a 730-hour month and costs more than CPU instances, it only makes sense when your software can fully take advantage of GPU acceleration.