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RunPod vs Vultr

A detailed comparison to help you choose between RunPod and Vultr.

Quick Verdict

3.9/5

RunPod

374 reviews

4.2/5

Vultr

499 reviews

Vultr is rated higher (4.2 vs 3.9). RunPod is a GPU cloud marketplace with community and secure cloud options. Deploy Docker containers on RTX, A100, and H100 GPUs. Serverless inference endpoints and network volumes for persistent storage. Vultr is a cloud platform offering VPS, bare metal servers, and Kubernetes hosting across 32 data centers worldwide. Built for developers and businesses needing scalable, reliable compute resources with transparent billing.

RunPod

RunPod

Community GPU cloud with on-demand pods

Vultr

Vultr

High-performance cloud infrastructure with global data centers and competitive pricing

Overview
Rating3.9 (374 reviews)4.2 (499 reviews)
Pricing modelusage-basedpaid
Starting priceFree tier availableFrom €5/mo
Best forML developers who want affordable GPU compute with serverless inference endpoints for deploying AI modelsDevelopers and DevOps teams building applications requiring low latency across multiple regions or those prioritizing cost-effective, API-first infrastructure management.
Specifications (entry plan)
CPU cores1 vCPU
RAM1 GB
Storage25 GB
Bandwidth1 TB/mo
SLA uptime99.99%
Data-center count32
€/vCPU/mo€5.00
€/GB RAM/mo€5.00
Performance
CPU score (sysbench)4,100
Disk read (fio)1,800 MB/s
Disk IOPS (4K random)38,000
Network out1 Gbps
Latency (TTFB)24 ms
Features
IPv6
DDoS protection
Automated backups
Snapshots
Managed option
Bare metal
GPU available
S3-compatible
Hourly billing
Free tier
Data-center locations
Regions
United StatesUnited KingdomGermanyNetherlandsFranceAustralia+6
Tags
Tags
hourly billinggpu availableeu datacenterus datacenter
hourly billingnvme storageipv6ddos protectionbackups includedsnapshotsbare metalgpu availables3 compatibleeu datacenterus datacenterapac datacenterterraform providerapi accesswindows available
Visit RunPod →Visit Vultr →

RunPod

Pros

  • + Affordable GPU pricing with community options
  • + Serverless inference endpoints built-in
  • + Network volumes for persistent data

Cons

  • - Community pods less reliable than secure cloud
  • - UI could be improved
View full RunPodreview →

Vultr

Pros

  • + Deploy servers in 32 global locations with minimal latency
  • + Access affordable pricing with hourly billing and no setup fees
  • + Manage infrastructure via intuitive dashboard or REST API
  • + Scale resources on-demand without contract commitments

Cons

  • - Smaller ecosystem of pre-built applications compared to AWS or DigitalOcean
  • - Support limited to ticketing system; no phone support on lower plans
View full Vultrreview →

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