Provider Comparison

DigitalOcean vs Nebius

Q: Which provider offers spot instances for cost savings?

Nebius offers spot/preemptible instances, which can significantly reduce costs (typically 50-80% off on-demand prices) for interruptible workloads like batch processing and training with checkpoints. DigitalOcean does not currently offer spot instances, so all usage is billed at on-demand rates. If cost optimization through spot instances is important for your workflow, Nebius would be the better choice.

Q: What is the minimum billing increment for each provider?

DigitalOcean bills per-hour, while Nebius bills per-second. Per-second billing from Nebius offers better cost efficiency for short experiments and iterative development, as you only pay for exactly what you use.

Q: Which provider has better compliance certifications for enterprise use?

DigitalOcean holds SOC 2, HIPAA, GDPR, ISO 27001 certifications. Nebius holds SOC 2, HIPAA, GDPR, ISO 27001 certifications. Both providers have similar compliance postures. Check with each provider directly for the most current certification status and specific compliance documentation.

Q: Which provider offers better development tools like Jupyter notebooks?

Both DigitalOcean and Nebius offer built-in Jupyter notebook support, making it easy to start experimenting without additional setup. This is particularly valuable for data scientists and researchers who prefer interactive development environments. Additionally, both providers offer web-based terminal access for quick debugging.

Q: Which provider has better Kubernetes support for orchestration?

Both DigitalOcean and Nebius support Kubernetes for container orchestration, enabling you to deploy scalable ML pipelines, manage distributed training jobs, and integrate with MLOps tools like Kubeflow. This is essential for teams running production workloads at scale.

Q: What is each provider best suited for?

DigitalOcean is best suited for Developers and startups wanting simple, predictable GPU pricing; Teams already on the DigitalOcean ecosystem needing to add GPU capacity. Nebius excels at Enterprises needing EU/US compliance and managed K8s. Understanding these specializations helps you choose the provider that aligns with your primary use case, though both can handle a variety of GPU computing needs.

Q: Which provider offers reserved instances for long-term savings?

Both DigitalOcean and Nebius offer reserved instance pricing for committed usage, typically providing 20-40% discounts compared to on-demand rates. Reserved instances are ideal for predictable, steady-state workloads like always-on inference services. For variable workloads, on-demand or spot instances may offer better flexibility.

Q: Which provider offers better enterprise support?

Both DigitalOcean and Nebius offer enterprise support tiers with dedicated assistance, faster response times, and potentially custom SLAs. Regarding SLAs: DigitalOcean offers SLA guarantees (99.99% uptime); Nebius offers SLA guarantees.

Q: Which provider has better API and automation support?

DigitalOcean provides a comprehensive API for programmatic control, while Nebius may require more manual management. If automation is a priority, DigitalOcean's API support will streamline your infrastructure-as-code workflows.

Q: Which provider has better container and Docker support?

DigitalOcean offers native container support for running Docker images, while Nebius may require additional configuration. Container support is valuable for reproducible ML pipelines and easy deployment of pre-built environments.

DigitalOcean and Nebius represent distinct approaches in the GPU cloud market for AI/ML workloads. DigitalOcean, a developer-centric provider, emphasizes simplicity and predictability with NVIDIA H100 and H200 GPU Droplets, integrating seamlessly with its ecosystem including DOKS Kubernetes, Spaces storage, and the 1-Click Models marketplace acquired via Paperspace's Gradient. It's ideal for developers and startups seeking straightforward per-hour pricing without hyperscaler complexity, though limited by smaller GPU inventory and H100/H200-only options. Nebius, an AI-focused infrastructure player, targets enterprises with managed Kubernetes services and strong EU/US compliance (SOC 2, HIPAA, GDPR, ISO 27001). As a public company, it offers transparency and a startup-like agility, with per-second billing and spot instances for cost optimization. However, detailed GPU specs and inventory are less publicized, potentially limiting visibility for planning. Key differentiators include DigitalOcean's ease-of-use and ecosystem integration versus Nebius's granular billing and enterprise-grade managed services. DigitalOcean suits rapid prototyping and teams embedded in its platform, delivering value through simplicity. Nebius appeals to compliance-driven organizations running variable workloads, potentially lowering costs for bursty usage. Both share compliance certifications, but choice hinges on scale, billing flexibility, and operational maturity—DigitalOcean for agility, Nebius for enterprise reliability and savings on intermittent jobs. (238 words)

Visit DigitalOcean Visit Nebius

Our Recommendation

Choose DigitalOcean for small-to-medium teams (1-50 members) or startups prioritizing simplicity, predictable per-hour costs, and tight integration with existing Droplets, Kubernetes, or storage. It's optimal for quick experiments, fine-tuning, or inference where H100/H200 GPUs suffice and GPU availability isn't a bottleneck—especially if already in the DO ecosystem to leverage 1-Click Models and Gradient. Opt for Nebius if you're an enterprise with compliance needs (EU/US data sovereignty), variable workloads, or cost-sensitive scaling via per-second billing and spot instances. It's better for managed K8s environments, larger training runs with potential discounts, or production deployments requiring transparency from a public company. Budget-wise, Nebius favors intermittent use; DigitalOcean suits steady, predictable spends. For hybrid needs, evaluate GPU inventory—DO's limitations may push hyperscale alternatives. (142 words)

Live Pricing

Compare real-time GPU offers from DigitalOcean and Nebius

21 offers available

Provider	GPU Model	VRAM	Host Specs	Region	Price	Status
QuantaCloud Partner	H100 / H200 · B200 / B300 32–1024+ GPUs · InfiniBand	∞	Custom configs	Multiple DCs	Reserved / cluster Get a quote in 24h	Available
DigitalOcean	NVIDIA RTX 4000 Ada Generation 20GB VRAM	20GB	8 vCPU 32GB RAM 500GB Storage	Toronto	$0.76/GPU/hr	Sold Out
Nebius	NVIDIA L40S 48GB VRAM	48GB	8 vCPU 32GB RAM	🌍Europe	$1.55/GPU/hr
DigitalOcean	NVIDIA L40S 48GB VRAM	48GB	8 vCPU 64GB RAM 500GB Storage	Toronto	$1.57/GPU/hr	Available
DigitalOcean	NVIDIA RTX 6000 Ada Generation 48GB VRAM	48GB	8 vCPU 64GB RAM 500GB Storage	Toronto	$1.57/GPU/hr	Sold Out
Nebius	NVIDIA L40S 48GB VRAM	48GB	16 vCPU 96GB RAM	🌍Europe	$1.82/GPU/hr

QuantaCloud

Partner

Available

H100 / H200 · B200 / B300

32–1024+ GPUs · InfiniBand

Reserved / cluster

Get a quote in 24h

DigitalOcean

Toronto

Sold Out

NVIDIA RTX 4000 Ada Generation

20GB VRAM

8 vCPU

32GB RAM

500GB Storage

$0.76/GPU/hr

Nebius

🌍Europe

NVIDIA L40S

48GB VRAM

8 vCPU

32GB RAM

$1.55/GPU/hr

DigitalOcean

Toronto

Available

NVIDIA L40S

48GB VRAM

8 vCPU

64GB RAM

500GB Storage

$1.57/GPU/hr

DigitalOcean

Toronto

Sold Out

NVIDIA RTX 6000 Ada Generation

48GB VRAM

8 vCPU

64GB RAM

500GB Storage

$1.57/GPU/hr

Nebius

🌍Europe

NVIDIA L40S

48GB VRAM

16 vCPU

96GB RAM

$1.82/GPU/hr

View all 21 offers

QuantaCloud

Comparing providers? We broker across all of them.

Stop tab-switching between pricing pages. Tell us what you need — 16+ GPUs, reserved or cluster capacity — and we return one quote at partner rates within 24 hours.

No waitlist24hr quote turnaroundInfiniBand fabric

DigitalOcean(Est. 2011)

A developer-focused cloud provider offering simple, predictable GPU Droplets for AI/ML workloads, bringing NVIDIA H100 and H200 accelerators to its global developer community with the same simplicity its CPU droplets are known for.

Best For

Developers and startups wanting simple, predictable GPU pricingTeams already on the DigitalOcean ecosystem needing to add GPU capacity

Unique Features

1-Click Models marketplace for rapid model deployment
Integrated with DigitalOcean Kubernetes (DOKS) and Spaces object storage
Acquired Paperspace to bolster AI/ML platform (Gradient)

Limitations

Smaller GPU inventory compared to hyperscalers
Limited to NVIDIA H100/H200-class offerings

Nebius(Est. 2023)

An AI-centric infrastructure company providing managed services for EU/US compliant workloads.

Best For

Enterprises needing EU/US compliance and managed K8s

Unique Features

Public company with transparency
Startup-like focus on AI

Feature Comparison

Access Methods

Feature	DigitalOcean	Nebius
SSH
Jupyter Notebooks
Web Terminal
API
Kubernetes
Containers

Billing Options

Feature	DigitalOcean	Nebius
Billing Increment	per-hour	per-second
Spot Instances
Reserved Instances
Prepaid Credits

Compliance

Certification	DigitalOcean	Nebius
SOC 2
HIPAA
GDPR
ISO 27001

Support

Feature	DigitalOcean	Nebius
SLA
Enterprise Support
Discord Community

Pricing Analysis

Pricing Overview

DigitalOcean employs per-hour billing for GPU Droplets, offering predictable costs without minimum commitments, aligned with its developer-friendly model—no spot or reserved options mentioned, emphasizing on-demand simplicity. Nebius differentiates with per-second billing and spot instances, enabling precise cost control for short or interruptible jobs, alongside potential on-demand rates. Implications vary by usage: per-hour suits steady, long-running workloads (e.g., multi-day training) minimizing billing granularity overhead, but incurs costs during idle minutes. Per-second excels for bursty patterns like experiments or batch jobs under an hour, reducing waste—spots further discount non-critical tasks by up to 90% potentially, though with preemption risk. Without public reserved pricing details for either, Nebius favors flexible, cost-optimized users; DigitalOcean steady-state reliability. Enterprises should model via calculators, noting Nebius's transparency as a public firm aids forecasting. (152 words)

Value Assessment

For small experiments or fine-tuning (<1 hour), Nebius provides superior value via per-second/spot billing, minimizing costs for frequent short runs—ideal for prototyping teams. DigitalOcean's per-hour model is less efficient here, charging full hours. Large LLM training (days-long) favors DigitalOcean's predictability, avoiding spot interruptions on H100/H200 clusters, though smaller inventory risks wait times. Nebius shines if spots are viable for fault-tolerant jobs, offering savings. Production inference: steady real-time suits DigitalOcean's reliable on-demand; batch inference leans Nebius for spot economics. Overall, Nebius wins cost-sensitive, variable loads (20-50% savings potential); DigitalOcean for consistent usage where simplicity trumps granularity, especially ecosystem users. Factor GPU rates—assume comparable H100 pricing (~$3-5/hr), but verify via DO console/Nebius quotes. (148 words)

Use Case Comparison

LLM Training

Either works

DigitalOcean

DigitalOcean fits well for mid-scale training with H100/H200 Droplets, offering simple multi-GPU setups via DOKS and predictable per-hour pricing. 1-Click Models accelerate setup, but smaller inventory may delay large-cluster access (8+ GPUs), suiting startups over massive runs. Gradient integration aids workflows. (62 words)

Nebius

Nebius suits enterprise-scale training via managed K8s and spot instances for cost savings on long jobs, with EU/US compliance. Per-second billing optimizes variable durations; however, GPU types/inventory details are sparse, potentially requiring verification for H100-scale needs. Public transparency aids planning. (64 words)

Batch Inference

Nebius recommended

DigitalOcean

DigitalOcean handles batch inference effectively with H100 Droplets and Spaces storage integration, per-hour billing fine for scheduled runs. DOKS enables orchestration, but lacks spots, making it costlier for infrequent batches versus interruptible alternatives. (58 words)

Nebius

Nebius excels with spot instances and per-second billing, ideal for cost-optimized, interruptible batch jobs on managed K8s. Compliance supports enterprise data flows; GPU scaling assumed robust, though specifics limited—strong for high-volume, sporadic inference. (60 words)

Real-time Inference

DigitalOcean recommended

DigitalOcean

DigitalOcean's predictable H100/H200 Droplets and Gradient platform support low-latency inference, with DOKS for scaling and 1-Click deployments. Per-hour stability ensures SLAs; ecosystem simplifies serving models reliably for production apps. (56 words)

Nebius

Nebius's managed K8s and per-second billing enable efficient real-time serving, with spots less viable due to uptime needs. Compliance aids regulated apps; performance depends on unconfirmed GPU/networking, but AI focus suggests optimization. (58 words)

Fine-tuning & Experimentation

Nebius recommended

DigitalOcean

DigitalOcean shines for rapid iteration via 1-Click Models and simple Droplets, H100 access for devs. Per-hour suits short sessions, DOKS/Gradient streamline; inventory limits parallel expts but fine for solo/small teams. (54 words)

Nebius

Nebius's per-second/spot pricing maximizes value for bursty experiments, managed K8s eases multi-node tuning. Enterprise compliance for sensitive data; GPU details uncertain, but flexibility favors frequent, low-commitment trials. (56 words)

Technical Comparison

Infrastructure

DigitalOcean uses virtualized GPU Droplets (NVIDIA H100/H200) with global data centers, DOKS-managed Kubernetes, and Spaces object storage for seamless AI workflows. Networking via VPCs; bare-metal absent, focusing VM simplicity. Nebius emphasizes managed Kubernetes for AI, likely hybrid bare-metal/virtualized (details sparse), with EU/US regions for compliance. Both support standard storage/networking, but DO's Paperspace acquisition bolsters ML tools; Nebius prioritizes enterprise orchestration. (98 words)

Performance

DigitalOcean's H100/H200 deliver top-tier training/inference (FP8/FP16 optimized), with DOKS multi-GPU scaling via NVLink/SLURM-like; availability constrained by inventory. Nebius offers comparable NVIDIA GPUs (assumed H100-class, unconfirmed), spot-enabled scaling on K8s; public status implies reliable clusters, but lacks benchmark data. DO edges prototyping speed; Nebius potentially better large-scale via spots. Both handle ML perf, but verify interconnects—DO's ecosystem may reduce latency overhead. (96 words)

Frequently Asked Questions

Which provider offers spot instances for cost savings?▾

Nebius offers spot/preemptible instances, which can significantly reduce costs (typically 50-80% off on-demand prices) for interruptible workloads like batch processing and training with checkpoints. DigitalOcean does not currently offer spot instances, so all usage is billed at on-demand rates. If cost optimization through spot instances is important for your workflow, Nebius would be the better choice.

What is the minimum billing increment for each provider?▾

DigitalOcean bills per-hour, while Nebius bills per-second. Per-second billing from Nebius offers better cost efficiency for short experiments and iterative development, as you only pay for exactly what you use.

Which provider has better compliance certifications for enterprise use?▾

DigitalOcean holds SOC 2, HIPAA, GDPR, ISO 27001 certifications. Nebius holds SOC 2, HIPAA, GDPR, ISO 27001 certifications. Both providers have similar compliance postures. Check with each provider directly for the most current certification status and specific compliance documentation.

Which provider offers better development tools like Jupyter notebooks?▾

Both DigitalOcean and Nebius offer built-in Jupyter notebook support, making it easy to start experimenting without additional setup. This is particularly valuable for data scientists and researchers who prefer interactive development environments. Additionally, both providers offer web-based terminal access for quick debugging.

Which provider has better Kubernetes support for orchestration?▾

Both DigitalOcean and Nebius support Kubernetes for container orchestration, enabling you to deploy scalable ML pipelines, manage distributed training jobs, and integrate with MLOps tools like Kubeflow. This is essential for teams running production workloads at scale.

What is each provider best suited for?▾

DigitalOcean is best suited for Developers and startups wanting simple, predictable GPU pricing; Teams already on the DigitalOcean ecosystem needing to add GPU capacity. Nebius excels at Enterprises needing EU/US compliance and managed K8s. Understanding these specializations helps you choose the provider that aligns with your primary use case, though both can handle a variety of GPU computing needs.

Which provider offers reserved instances for long-term savings?▾

Both DigitalOcean and Nebius offer reserved instance pricing for committed usage, typically providing 20-40% discounts compared to on-demand rates. Reserved instances are ideal for predictable, steady-state workloads like always-on inference services. For variable workloads, on-demand or spot instances may offer better flexibility.

Which provider offers better enterprise support?▾

Both DigitalOcean and Nebius offer enterprise support tiers with dedicated assistance, faster response times, and potentially custom SLAs. Regarding SLAs: DigitalOcean offers SLA guarantees (99.99% uptime); Nebius offers SLA guarantees.

Which provider has better API and automation support?▾

DigitalOcean provides a comprehensive API for programmatic control, while Nebius may require more manual management. If automation is a priority, DigitalOcean's API support will streamline your infrastructure-as-code workflows.

Which provider has better container and Docker support?▾

DigitalOcean offers native container support for running Docker images, while Nebius may require additional configuration. Container support is valuable for reproducible ML pipelines and easy deployment of pre-built environments.

What unique features differentiate these providers?▾

DigitalOcean's standout features include: 1-Click Models marketplace for rapid model deployment; Integrated with DigitalOcean Kubernetes (DOKS) and Spaces object storage; Acquired Paperspace to bolster AI/ML platform (Gradient). Nebius's standout features include: Public company with transparency; Startup-like focus on AI. These differentiators may be decisive factors depending on your specific technical requirements and workflow preferences.

How do I get started with each provider?▾

To get started with DigitalOcean, visit their website at https://www.digitalocean.com/products/gpu-droplets to create an account and explore available GPU options. For Nebius, visit https://nebius.com?utm_source=gpuperhour&utm_medium=referral to sign up. Both providers typically offer some form of free credits or trial period for new users. We recommend starting with a small experiment to evaluate the platform's ease of use, instance launch times, and overall fit for your workflow before committing to larger workloads.