Does DigitalOcean support multi-GPU instances with NVLink or InfiniBand?
💡 Answer
DigitalOcean supports multi-GPU configurations with the following specifications:
Interconnect technology: NVLink
Maximum GPUs per instance: 8
Multi-node training: 1
The choice of interconnect is critical for distributed training performance. NVLink provides up to 900 GB/s bidirectional bandwidth between GPUs, while InfiniBand enables high-speed communication across nodes. PCIe-only setups are suitable for inference but may bottleneck multi-GPU training.
Available GPU models: RTX 4000 Ada, RTX 6000 Ada, L40S, MI300X, H100 SXM, H200
For detailed interconnect specs and multi-GPU topology diagrams, see DigitalOcean official website.
More FAQs about DigitalOcean
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- What is the current Trustpilot rating and number of reviews for DigitalOcean?
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- Where are DigitalOcean data centers located?
- 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 B200
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- Cloud GPU Providers with Spot / Preemptible Instances
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- Cloud GPU Providers with Zero Egress Fees
These guides include DigitalOcean alongside other cloud GPU providers, grouped by hardware, pricing, features, and infrastructure.
DigitalOcean vs RunPod vs Latitude.sh - GPU Provider Comparison (April 2026)
Side-by-side comparison of DigitalOcean vs RunPod vs Latitude.sh. Quickly scan maximum funding, profit splits, risk rules, leverage, platforms, instruments, payout schedules, payment options, trading permissions and KYC restrictions to narrow down your prop trading firm shortlist. Data updated April 2026.
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DigitalOcean
Simple, scalable GPU cloud for AI/ML
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RunPod
The cloud built for AI — deploy and scale GPU workloads from serverless inference to instant multi-node clusters on demand.
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Latitude.sh
Bare metal GPU cloud across 23 global locations
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|---|---|---|---|
| Overview | |||
| Trustpilot Rating | 4.6 | 3.8 | 3.7 |
| Headquarters | United States | United States | Brazil |
| Provider Type | N/A | GPU-Focused | Bare Metal |
| Best For | AI training inference fine-tuning LLM deployment LLM serving computer vision startups generative AI research | AI training inference fine-tuning Stable Diffusion batch processing rendering research LLM serving generative AI | AI training inference bare metal GPU fine-tuning research dedicated workloads generative AI |
| GPU Hardware | |||
| GPU Models | RTX 4000 Ada RTX 6000 Ada L40S MI300X H100 SXM H200 | B300 B200 H200 H100 SXM H100 PCIe H100 NVL MI300X A100 SXM A100 PCIe RTX 5090 RTX PRO 6000 L40S L40 RTX 6000 Ada RTX 5000 Ada RTX A6000 RTX A5000 RTX 4090 RTX 4080 SUPER RTX 4080 RTX 4070 Ti RTX 3090 Ti RTX 3090 RTX 3080 Ti RTX 3080 RTX 3070 A40 A30 A2 L4 | A30 RTX A5000 RTX A6000 L40S RTX 6000 Ada A100 SXM H100 SXM GH200 RTX PRO 6000 |
| Max VRAM (GB) | 192 | 288 | 96 |
| Max GPUs/Instance | 8 | 8 | 8 |
| Interconnect | NVLink | NVLink | NVLink |
| Pricing | |||
| Starting Price ($/hr) | $0.76/hr | $0.06/hr | $0.35/hr |
| Billing Granularity | Per-second | Per-second | Per-hour |
| Spot/Preemptible | 0 | 1 | 0 |
| Reserved Discounts | N/A | 15-29% (1-month to 1-year plans) | N/A |
| Free Credits | $200 free credit for 60 days | $5-$500 bonus after first $10 spend | $200 via referral program |
| Egress Fees | None (included in plan) | None (Free) | None |
| Storage | 500-720 GiB NVMe boot (included), 5 TiB NVMe scratch on larger configs, Volumes at $0.10/GiB/mo | Container/Volume ($0.10/GB/mo), Idle Volume ($0.20/GB/mo), Network Storage ($0.07/GB/mo 1TB) | Local NVMe included (up to 4x 3.8TB), Block Storage $0.10/GB/mo, Filesystem Storage $0.05/GB/mo |
| Infrastructure | |||
| Regions | New York (NYC2), Toronto (TOR1), Atlanta (ATL1), Richmond (RIC1), Amsterdam (AMS3) | 31 global regions | 23 locations: US (8 cities), LATAM (5), Europe (5), APAC (4), Mexico City. GPU in Dallas, Frankfurt, Sydney, Tokyo |
| Uptime SLA | 99% | 99.99% | 99.9% |
| Developer Experience | |||
| Frameworks | PyTorch TensorFlow Jupyter Miniconda CUDA ROCm Hugging Face | PyTorch TensorFlow JAX ONNX CUDA | ML-optimized images PyTorch TensorFlow (user-installed) CUDA |
| Docker Support | 1 | 1 | 1 |
| SSH Access | 1 | 1 | 1 |
| Jupyter Notebooks | 1 | 1 | 0 |
| API / CLI | 1 | 1 | 1 |
| Setup Time | Minutes | Instant | Seconds |
| Kubernetes Support | 1 | 0 | 0 |
| Business Terms | |||
| Min Commitment | None | None | None |
| Compliance | SOC 2 Type II SOC 3 HIPAA (with BAA) CSA STAR Level 1 | SOC 2 Type II | Single-tenant isolation DPA available |
DigitalOcean
RunPod
Latitude.sh