GPU Providers
HQ
Billing
Actions
Cloud GPU Providers with Kubernetes Support
Kubernetes has become the standard for orchestrating ML training and inference workloads at scale. GPU-aware Kubernetes clusters enable automated scheduling, resource management, and integration with MLOps tools like Kubeflow and Ray. This guide lists cloud GPU providers that offer managed Kubernetes support or GPU-enabled Kubernetes clusters for production AI deployments.
Trustpilot Reviews
143
+0
(7d)
+3
(30d)
HQ
Lithuania Starting Price
$0.16/hr
Max VRAM
80 GB
Max GPUs
2
Billing
Per-hour
Trustpilot Reviews
2,362
+13
(7d)
+62
(30d)
HQ
United States Starting Price
$0.76/hr
Max VRAM
192 GB
Max GPUs
8
Billing
Per-second
Trustpilot Reviews
550
+2
(7d)
+9
(30d)
HQ
United States Starting Price
$0.47/hr
Max VRAM
288 GB
Max GPUs
16
Billing
Per-hour
Cherry Servers vs DigitalOcean - Comparison of Top Firms in This Guide
Cherry Servers vs DigitalOcean - GPU Provider Comparison (May 2026)
Head-to-head comparison of Cherry Servers and DigitalOcean. Compare GPU models, hourly pricing, billing granularity, spot instances, VRAM, infrastructure, developer tools, Kubernetes support, and compliance before choosing a provider. Data refreshed May 2026.
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Cherry Servers
Bare metal GPU servers with 24 years of hosting experience and full hardware-level control.
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DigitalOcean
Simple, scalable GPU cloud for AI/ML
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|---|---|---|
| Overview | ||
| Trustpilot Rating | 4.6 | 4.6 |
| Headquarters | Lithuania | United States |
| Provider Type | N/A | N/A |
| Best For | AI training inference fine-tuning rendering research HPC generative AI deep learning | AI training inference fine-tuning LLM deployment LLM serving computer vision startups generative AI research |
| GPU Hardware | ||
| GPU Models | A100 A40 A16 A10 A2 Tesla P4 | RTX 4000 Ada RTX 6000 Ada L40S MI300X H100 SXM H200 |
| Max VRAM (GB) | 80 | 192 |
| Max GPUs/Instance | 2 | 8 |
| Interconnect | PCIe | NVLink |
| Pricing | ||
| Starting Price ($/hr) | $0.16/hr | $0.76/hr |
| Billing Granularity | Per-hour | Per-second |
| Spot/Preemptible | No | No |
| Reserved Discounts | N/A | N/A |
| Free Credits | None | $200 free credit for 60 days |
| Egress Fees | N/A | None (included in plan) |
| Storage | NVMe SSD, Elastic Block Storage ($0.071/GB/mo) | 500-720 GiB NVMe boot (included), 5 TiB NVMe scratch on larger configs, Volumes at $0.10/GiB/mo |
| Infrastructure | ||
| Regions | Lithuania, Netherlands, Germany, Sweden, US, Singapore (6 locations) | New York (NYC2), Toronto (TOR1), Atlanta (ATL1), Richmond (RIC1), Amsterdam (AMS3) |
| Uptime SLA | 99.97% | 99% |
| Developer Experience | ||
| Frameworks | PyTorch TensorFlow CUDA (bare metal — full stack control) | PyTorch TensorFlow Jupyter Miniconda CUDA ROCm Hugging Face |
| Docker Support | Yes | Yes |
| SSH Access | Yes | Yes |
| Jupyter Notebooks | No | Yes |
| API / CLI | Yes | Yes |
| Setup Time | Minutes | Minutes |
| Kubernetes Support | Yes | Yes |
| Business Terms | ||
| Min Commitment | None | None |
| Compliance | ISO 27001 ISO 20000-1 GDPR PCI DSS | SOC 2 Type II SOC 3 HIPAA (with BAA) CSA STAR Level 1 |
Cherry Servers
DigitalOcean
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