Lambda vs Vultr
A detailed comparison to help you choose between Lambda and Vultr.
Quick Verdict
3.7/5
Lambda
0 reviews
4.0/5
Vultr
0 reviews
Vultr is rated higher (4.0 vs 3.7). Lambda is a GPU cloud for training and running AI models, offering on-demand NVIDIA GPU instances and reserved clusters for AI teams and researchers. 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.
Lambda On-demand GPU cloud for ML training and inference | Vultr High-performance cloud infrastructure with global data centers and competitive pricing | |
|---|---|---|
| Overview | ||
| Rating | 3.7 (0 reviews) | 4.0 (0 reviews)✓ |
| Pricing model | usage-based | paid |
| Starting price | From $0.69/mo✓ | From $2.5/mo |
| Best for | ML researchers and engineering teams optimizing cost per GPU-hour for training, fine-tuning, and batch inference who can tolerate best-effort capacity. | Teams needing low-latency compute across multiple continents, API-first fleets, and self-serve GPU or bare metal with predictable billing |
| Specifications (entry plan) | ||
| CPU cores | 14 vCPU✓ | 1 vCPU |
| RAM | 46 GB✓ | 1 GB |
| Storage | — | 10 GB |
| Bandwidth | — | 1 TB/mo |
| SLA uptime | — | 100% |
| Data-center count | 14 | 34✓ |
| €/vCPU/mo | €0.05✓ | €2.50 |
| €/GB RAM/mo | €0.01✓ | €2.50 |
| Performance | ||
| CPU score (sysbench) | — | 4,100 |
| Disk read (fio) | — | 1,800 MB/s |
| Disk IOPS (4K random) | — | 38,000 |
| Network out | — | 1 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 | [US x10 regions, Tokyo, Osaka, India, Germany, Israel] | 34 regions across North/South America, Europe, Asia, Australia, Africa (see locations page) |
| Tags | ||
| Tags | hourly billinggpu availableus datacenterapi access | hourly billingnvme storageipv6ddos protectionbackups includedsnapshotsbare metalgpu availables3 compatibleeu datacenterus datacenterapac datacenterterraform providerapi accesswindows available |
| Visit Lambda → | Visit Vultr → | |
Lambda
Pros
- + Published per-minute GPU pricing with no egress fees
- + Preinstalled ML stack (Lambda Stack) on all images
- + Full cloud API for instance automation
- + Free egress keeps large checkpoint downloads cheap
- + Cluster tier scales from 16 to 2,000+ GPUs for distributed training
Cons
- - No published uptime SLA for on-demand instances
- - Popular H100 configurations sell out regularly
- - One European region (Germany); no Latin America or Australia
- - No managed databases, snapshots, or backup products
- - Filesystem billing continues after instance deletion
Vultr
Pros
- + Truly global: 34 regions on six continents from one console, one API, one price list - with per-region test IPs published
- + Fully published hourly and monthly pricing from $2.50/mo, mature REST API and Terraform provider
- + 100% network and host-node uptime SLA with credits; standardized platform behavior across every region
- + Broad self-serve catalog: NVMe optimized VMs, NVIDIA/AMD GPUs, bare metal, managed databases/Kafka, S3-compatible object storage, VKE
Cons
- - Price-performance trails European leaders: our measured HF 2GB (Amsterdam) had the slowest NVMe storage of six tested providers at a mid-range price
- - Backups cost 20% of instance price, snapshots bill per GB, Windows and extra egress are add-ons
- - No refunds in the terms of service; support is ticket-only for self-serve customers
- - Overlapping instance families (Cloud Compute, VX1, Optimized) make it easy to pick a stale SKU; region count differs across Vultr's own pages (32/33/34)
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