What machine learning frameworks does DigitalOcean support?
💡 Answer
DigitalOcean provides the following pre-installed frameworks and tools:
PyTorch, TensorFlow, Jupyter, Miniconda, CUDA, ROCm, Hugging Face
Custom images: Yes
Jupyter notebooks: Yes
Persistent storage: Yes
Having popular frameworks pre-installed means you can start training or inference immediately without spending time on environment setup. If you need a specific CUDA version or custom dependencies, custom image support lets you bring your own Docker container.
For pre-built templates and framework compatibility details, see DigitalOcean official website.
More FAQs about DigitalOcean
- What is DigitalOcean best for?
- What is the current Trustpilot rating and number of reviews for DigitalOcean?
- How fast can I deploy a GPU instance on DigitalOcean?
- Does DigitalOcean offer serverless GPU inference?
- Where are DigitalOcean data centers located?
- Does DigitalOcean support multi-GPU instances with NVLink or InfiniBand?
- Does DigitalOcean offer spot or preemptible GPU instances?
- Does DigitalOcean charge egress or data transfer fees?
- Does DigitalOcean offer free credits or a free trial?
- What GPU models does DigitalOcean offer?
- What is DigitalOcean pricing and how does billing work?
Guides Where DigitalOcean Is Featured
- Best Cloud GPU Providers with NVIDIA H100
- Best Cloud GPUs for Video Rendering & VFX
- Cheapest Cloud GPUs Under $0.50/hr
- Cloud GPU Providers with API & CLI Management
- Cloud GPU Providers with Docker & Custom Images
- Cloud GPU Providers with Free Credits
- Cloud GPU Providers with Jupyter Notebook Support
- Cloud GPU Providers with Kubernetes Support
- Cloud GPU Providers with Multi-Node GPU Clusters
- Cloud GPU Providers with NVLink or InfiniBand
- Cloud GPU Providers with Per-Second Billing
- Cloud GPU Providers with Persistent Storage
- Cloud GPU Providers with Serverless GPU Inference
- Cloud GPU Providers with Spot / Preemptible Instances
- Cloud GPU Providers with SSH Access
- Cloud GPU Providers with Zero Egress Fees
These guides include DigitalOcean alongside other cloud GPU providers, grouped by hardware, pricing, features, and infrastructure.
DigitalOcean GPU Provider Review & Key Facts (May 2026)
Snapshot of DigitalOcean: GPU models, pricing, billing granularity, infrastructure, developer tools, support channels, and compliance. Data verified May 2026.
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DigitalOcean
Simple, scalable GPU cloud for AI/ML
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|---|---|
| Overview | |
| Trustpilot Rating | 4.6 |
| Headquarters | United States |
| Provider Type | N/A |
| Best For | AI training inference fine-tuning LLM deployment LLM serving computer vision startups generative AI research |
| GPU Hardware | |
| GPU Models | RTX 4000 Ada RTX 6000 Ada L40S MI300X H100 SXM H200 |
| Max VRAM (GB) | 192 |
| Max GPUs/Instance | 8 |
| Interconnect | NVLink |
| Pricing | |
| Starting Price ($/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