About Vultr
Vultr is a well-established cloud infrastructure provider that expanded into GPU computing in recent years. Founded in 2014, Vultr has grown to operate 32 data centers worldwide, offering a full suite of cloud services including compute, storage, and networking.
Vultr's GPU cloud is built on their global infrastructure, providing consistent performance and reliability. They focus on simplicity and ease of use, making it accessible for developers and businesses of all sizes.
While not as specialized as Lambda Labs or RunPod for AI workloads, Vultr offers a solid general-purpose GPU cloud with the backing of a larger, financially stable company.
Vultr Pricing
Vultr GPU pricing is straightforward:
ā¢ A100 80GB: From $3.50/hour
ā¢ A10G: From $0.70/hour
ā¢ L40S: From $2.00/hour
ā¢ RTX 6000 Ada: From $1.50/hour
Monthly pricing available with 20% discount. No hidden fees - includes standard storage and network.
Key Features
Global Network
32 data centers across 6 continents
Cloud Platform
Full suite of cloud services beyond GPU
High Performance
NVMe storage and high-speed networking
API Access
Complete API for automation
One-Click Apps
Marketplace with pre-configured applications
Best Use Cases
- āGeneral GPU Computing - Versatile GPU instances for various workloads
- āAI Inference - Deploy ML models with global coverage
- āRendering - 3D rendering and video encoding
- āVirtual Workstations - Remote desktop with GPU acceleration
Compare Providers
| Provider | Price (A100) | GPUs | Regions | Best For |
|---|---|---|---|---|
| Vultr | $3.50/hr (A100) | 180+ | 32 | Global coverage |
| Lambda Labs | $2.89/hr (A100) | 150+ | 3 | AI/ML focus |
| RunPod | $2.75/hr (A100) | 200+ | 31 | Best value |
Frequently Asked Questions
Is Vultr good for AI workloads?
Vultr works well for AI inference and smaller training jobs. For large-scale LLM training, consider Lambda Labs or RunPod.
Does Vultr offer GPU instances in all regions?
GPU availability varies by region. Check their control panel for current availability in your preferred location.