Provider Comparison

Nebius vs Vultr

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. Vultr 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?

Nebius bills per-second, while Vultr bills per-hour. 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?

Nebius holds SOC 2, HIPAA, GDPR, ISO 27001 certifications. Vultr 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?

Nebius offers built-in Jupyter notebook support for interactive development, while Vultr requires you to set up your own notebook environment. If quick iteration and experimentation are priorities, Nebius's integrated notebooks provide a smoother experience. Additionally, both providers offer web-based terminal access for quick debugging.

Q: Which provider has better Kubernetes support for orchestration?

Both Nebius and Vultr 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?

Nebius is best suited for Enterprises needing EU/US compliance and managed K8s. Vultr excels at Global deployments across 32+ regions. 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 Nebius and Vultr 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?

Nebius offers dedicated enterprise support options, while Vultr may have more limited support tiers. Regarding SLAs: Nebius offers SLA guarantees; Vultr has no published SLA.

Q: Which provider has better API and automation support?

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

Q: Which provider has better container and Docker support?

Container support details are not prominently listed for either provider. Check their documentation for Docker and container runtime compatibility.

Nebius and Vultr are both capable GPU cloud providers for ML/AI workloads, but they cater to distinct needs. Nebius positions itself as an AI-centric infrastructure specialist, emphasizing managed Kubernetes services and strict compliance for EU/US-regulated enterprises. As a public company with a startup-like AI focus, it offers transparency and tailored services for large-scale AI training and inference, with per-second billing and spot instances enabling cost efficiency for variable workloads. Its strengths lie in SOC 2, HIPAA, GDPR, and ISO 27001 compliance, making it ideal for sensitive data processing in regulated industries. Vultr, conversely, excels as a global cloud provider with over 32 regions, supporting diverse deployments from edge to core data centers. It provides integrated cloud services like object storage and load balancers alongside GPUs, appealing to teams needing low-latency global inference or multi-region redundancy. Hourly billing suits steady-state production, though it lacks Nebius's per-second granularity. Key differentiators include Nebius's AI-native managed K8s and spot pricing for bursty AI jobs versus Vultr's expansive footprint for distributed applications. Nebius suits compliance-focused enterprises with dedicated AI infra needs, while Vultr offers versatility for global-scale devs. Overall, Nebius provides superior value for regulated, AI-intensive workloads; Vultr shines in geographic flexibility and broad ecosystem integration, though both deliver high-performance GPUs like H100s where available.

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Our Recommendation

Choose Nebius for enterprise teams (50+ engineers) handling regulated workloads like healthcare AI or financial ML models, where managed K8s, EU/US data residency, and per-second/spot billing minimize costs for intermittent large training runs. It's ideal for budgets prioritizing compliance over global scale, with technical needs like HIPAA/GDPR and seamless multi-GPU orchestration. Opt for Vultr when global low-latency is critical, such as for teams deploying real-time inference across continents or running distributed fine-tuning in 32+ regions. It's better for smaller/mid-sized teams (under 50) or cost-sensitive startups with steady hourly usage, leveraging integrated services like CDN for edge AI. Vultr favors budgets avoiding managed service premiums, but may require more DevOps for K8s compared to Nebius's turnkey AI focus.

Live Pricing

Compare real-time GPU offers from Nebius and Vultr

55 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
Vultr	8×NVIDIA A16 64GB VRAM	64GB	48 vCPU 496GB RAM 1500GB Storage	Atlanta	$0.47/GPU/hr $3.77/hr total (8×)	Sold Out
Vultr	8×NVIDIA A16 64GB VRAM	64GB	48 vCPU 496GB RAM 1500GB Storage	Bangalore	$0.47/GPU/hr $3.77/hr total (8×)	Sold Out
Vultr	16×NVIDIA A16 64GB VRAM	64GB	96 vCPU 960GB RAM 1700GB Storage	Atlanta	$0.47/GPU/hr $7.53/hr total (16×)	Sold Out
Vultr	16×NVIDIA A16 64GB VRAM	64GB	96 vCPU 960GB RAM 1700GB Storage	Singapore	$0.47/GPU/hr $7.53/hr total (16×)	Sold Out
Vultr	8×NVIDIA A16 64GB VRAM	64GB	48 vCPU 496GB RAM 1500GB Storage	Atlanta	$0.47/GPU/hr $3.77/hr total (8×)	Sold Out

QuantaCloud

Partner

Available

H100 / H200 · B200 / B300

32–1024+ GPUs · InfiniBand

Reserved / cluster

Get a quote in 24h

Vultr

Atlanta

Sold Out

NVIDIA A168x

64GB VRAM

48 vCPU

496GB RAM

1500GB Storage

$0.47/GPU/hr

$3.77/hr total (8×)

Vultr

Bangalore

Sold Out

NVIDIA A168x

64GB VRAM

48 vCPU

496GB RAM

1500GB Storage

$0.47/GPU/hr

$3.77/hr total (8×)

Vultr

Atlanta

Sold Out

NVIDIA A1616x

64GB VRAM

96 vCPU

960GB RAM

1700GB Storage

$0.47/GPU/hr

$7.53/hr total (16×)

Vultr

Singapore

Sold Out

NVIDIA A1616x

64GB VRAM

96 vCPU

960GB RAM

1700GB Storage

$0.47/GPU/hr

$7.53/hr total (16×)

Vultr

Atlanta

Sold Out

NVIDIA A168x

64GB VRAM

48 vCPU

496GB RAM

1500GB Storage

$0.47/GPU/hr

$3.77/hr total (8×)

View all 55 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

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

Vultr(Est. 2014)

A global cloud provider with a massive footprint for deployments across numerous regions.

Best For

Global deployments across 32+ regions

Unique Features

Massive global footprint
Integrated cloud services

Feature Comparison

Access Methods

Feature	Nebius	Vultr
SSH
Jupyter Notebooks
Web Terminal
API
Kubernetes
Containers

Billing Options

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

Compliance

Certification	Nebius	Vultr
SOC 2
HIPAA
GDPR
ISO 27001

Support

Feature	Nebius	Vultr
SLA
Enterprise Support
Discord Community

Pricing Analysis

Pricing Overview

Nebius employs per-second billing with spot instances, offering granular cost control ideal for bursty ML workloads—e.g., spin up H100 clusters for hours-long training and pay precisely, potentially saving 50-70% via spots during low-demand periods. No long-term commitments are required, and reserved options may exist for steady use. Vultr uses per-hour billing for on-demand and reserved instances, with minimum 1-hour charges suiting predictable loads but penalizing short experiments (e.g., a 10-minute job costs a full hour). Vultr lacks native spots but offers discounts for reservations. Implications: Nebius excels for variable/dev workloads; Vultr for production stability, though per-hour can inflate costs for sporadic AI prototyping.

Value Assessment

Nebius delivers superior value for small experiments and fine-tuning, where per-second billing avoids hourly waste—e.g., $5-10/hour H100 equivalents become pennies for quick tests. For large training runs (days-long), spots amplify savings. Vultr offers better value in production inference with reserved hourly rates locking in 20-40% discounts for sustained loads, plus global storage synergies reducing egress costs. For batch inference, Nebius edges out on flexibility; real-time favors Vultr's regional density. Overall, Nebius wins for R&D budgets (<$10k/month bursty); Vultr for scale-out prod (> $50k/month steady).

Use Case Comparison

LLM Training

Nebius recommended

Nebius

Nebius excels with AI-optimized bare-metal H100/A100 clusters, managed K8s for multi-node scaling, and spot instances slashing costs for multi-day runs. EU/US compliance suits enterprise models; per-second billing fits variable epochs without overpaying idle time. Strong for 8x+ GPU jobs with low-latency InfiniBand networking.

Vultr

Vultr supports H100 training across 32 regions with good multi-GPU via high-speed networks, but hourly billing inflates short trials. Global footprint aids data locality; integrated storage helps datasets, though less AI-specific orchestration than managed K8s.

Batch Inference

Either works

Nebius

Nebius handles batch jobs efficiently via autoscaling K8s and spots for cost-effective queuing. Compliance ensures secure processing; per-second granularity optimizes sporadic batches, with fast NVLink for GPU parallelism in large payloads.

Vultr

Vultr's global regions minimize data transfer for distributed batches, with object storage integration streamlining pipelines. Hourly on-demand suits predictable volumes; reserved instances cut costs for high-throughput steady batches.

Real-time Inference

Vultr recommended

Nebius

Nebius supports low-latency inference with managed services and EU/US edges, but limited regions may increase cold-start times for global users. Strong compliance for prod; autoscaling K8s aids traffic spikes.

Vultr

Vultr dominates with 32+ regions for edge deployment, reducing latency (<50ms globally). Integrated CDN/load balancers enhance real-time serving; hourly billing stable for always-on endpoints with GPU acceleration.

Fine-tuning & Experimentation

Nebius recommended

Nebius

Per-second billing and spots make Nebius ideal for rapid iterations—prototype on single GPUs cheaply. Managed K8s simplifies env setup; AI focus ensures latest frameworks pre-installed for quick LoRA/PEFT experiments.

Vultr

Vultr's broad regions support geo-distributed testing; hourly suits longer tunes but wastes on failures. Marketplace images speed setup, though more manual scaling than Nebius's managed AI tools.

Technical Comparison

Infrastructure

Nebius focuses on AI-grade bare-metal servers with NVIDIA H100/A100 GPUs, managed Kubernetes (via Nebius AI Cloud), InfiniBand/RoCE networking up to 400Gbps, and block/object storage optimized for ML datasets. EU/US data centers ensure compliance residency. Vultr offers virtualized and bare-metal GPUs across 32+ regions, with Kubernetes support via marketplace but less managed depth; 100Gbps networks, integrated S3-compatible storage, and broader instance types including CPUs/ARM for hybrid workloads.

Performance

Both provide H100s with strong multi-GPU scaling via NVLink/SLI; Nebius reports 90%+ efficiency in K8s-distributed training, aided by AI-tuned stacks. Vultr matches on single-node perf but may lag in cluster-scale due to virtualization overhead in some regions; global availability reduces queuing, though peak H100 stock varies. Nebius edges in managed perf consistency; Vultr in regional GPU diversity. Benchmarks show comparable TFLOPS, but Nebius's spots enable faster experimentation cycles.

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. Vultr 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?▾

Nebius bills per-second, while Vultr bills per-hour. 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?▾

Nebius holds SOC 2, HIPAA, GDPR, ISO 27001 certifications. Vultr 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?▾

Nebius offers built-in Jupyter notebook support for interactive development, while Vultr requires you to set up your own notebook environment. If quick iteration and experimentation are priorities, Nebius's integrated notebooks provide a smoother experience. Additionally, both providers offer web-based terminal access for quick debugging.

Which provider has better Kubernetes support for orchestration?▾

Both Nebius and Vultr 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?▾

Nebius is best suited for Enterprises needing EU/US compliance and managed K8s. Vultr excels at Global deployments across 32+ regions. 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 Nebius and Vultr 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?▾

Nebius offers dedicated enterprise support options, while Vultr may have more limited support tiers. Regarding SLAs: Nebius offers SLA guarantees; Vultr has no published SLA.

Which provider has better API and automation support?▾

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

Which provider has better container and Docker support?▾

Container support details are not prominently listed for either provider. Check their documentation for Docker and container runtime compatibility.

What unique features differentiate these providers?▾

Nebius's standout features include: Public company with transparency; Startup-like focus on AI. Vultr's standout features include: Massive global footprint; Integrated cloud services. 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 Nebius, visit their website at https://nebius.com?utm_source=gpuperhour&utm_medium=referral to create an account and explore available GPU options. For Vultr, visit https://www.vultr.com/?ref=9847371&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.