Does DigitalOcean offer serverless GPU inference?
💡 Answer
Serverless GPU at DigitalOcean: No
Serverless GPU inference allows you to deploy models that automatically scale up when requests arrive and scale down to zero when idle, eliminating the cost of keeping GPUs running during quiet periods. This is particularly cost-effective for applications with variable or unpredictable traffic patterns.
DigitalOcean standard GPU pricing starts at $0.76/hr with Per-second billing.
For serverless GPU endpoint setup guides and pricing, see DigitalOcean official website.
More FAQs about DigitalOcean
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- What is DigitalOcean pricing and how does billing work?
Guides Where DigitalOcean Is Featured
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- Cloud GPU Providers with Spot / Preemptible Instances
- Cloud GPU Providers with SSH Access
- Cloud GPU Providers with Zero Egress Fees
These guides include DigitalOcean alongside other cloud GPU providers, grouped by hardware, pricing, features, and infrastructure.
DigitalOcean GPU Provider Review & Key Facts (May 2026)
Snapshot of DigitalOcean: GPU models, pricing, billing granularity, infrastructure, developer tools, support channels, and compliance. Data verified May 2026.
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DigitalOcean
Simple, scalable GPU cloud for AI/ML
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|---|---|
| Overview | |
| Trustpilot Rating | 4.6 |
| Headquarters | United States |
| Provider Type | N/A |
| Best For | AI training inference fine-tuning LLM deployment LLM serving computer vision startups generative AI research |
| GPU Hardware | |
| GPU Models | RTX 4000 Ada RTX 6000 Ada L40S MI300X H100 SXM H200 |
| Max VRAM (GB) | 192 |
| Max GPUs/Instance | 8 |
| Interconnect | NVLink |
| Pricing | |
| Starting Price ($/hr) | $0.76/hr |
| Billing Granularity | Per-second |
| Spot/Preemptible | No |
| Reserved Discounts | N/A |
| Free Credits | $200 free credit for 60 days |
| Egress Fees | None (included in plan) |
| Storage | 500-720 GiB NVMe boot (included), 5 TiB NVMe scratch on larger configs, Volumes at $0.10/GiB/mo |
| Infrastructure | |
| Regions | New York (NYC2), Toronto (TOR1), Atlanta (ATL1), Richmond (RIC1), Amsterdam (AMS3) |
| Uptime SLA | 99% |
| Developer Experience | |
| Frameworks | PyTorch TensorFlow Jupyter Miniconda CUDA ROCm Hugging Face |
| Docker Support | Yes |
| SSH Access | Yes |
| Jupyter Notebooks | Yes |
| API / CLI | Yes |
| Setup Time | Minutes |
| Kubernetes Support | Yes |
| Business Terms | |
| Min Commitment | None |
| Compliance | SOC 2 Type II SOC 3 HIPAA (with BAA) CSA STAR Level 1 |
DigitalOcean