Provider Comparison

Crusoe vs Vultr

Q: Which provider offers spot instances for cost savings?

Crusoe 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, Crusoe would be the better choice.

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

Crusoe bills per-hour, while Vultr bills per-hour. Both providers use the same billing granularity, so this factor won't differentiate your decision.

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

Crusoe holds SOC 2, GDPR certifications. Vultr holds SOC 2, HIPAA, GDPR, ISO 27001 certifications. For organizations with strict compliance requirements, Vultr offers more comprehensive coverage.

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

Neither provider offers built-in Jupyter notebook support, so you'll need to set up your own development environment. Both providers support SSH access, allowing you to install JupyterLab or other tools on your instances. Additionally, Vultr offers web-based terminal access for quick debugging.

Q: Which provider has better Kubernetes support for orchestration?

Both Crusoe 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?

Crusoe is best suited for Organizations with strict ESG mandates; Batch training workloads where carbon footprint is a key metric. 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 Crusoe 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?

Crusoe offers dedicated enterprise support options, while Vultr may have more limited support tiers.

Q: Which provider has better API and automation support?

Both Crusoe and Vultr provide APIs for programmatic instance management, enabling automation of provisioning, scaling, and teardown operations. This is essential for integrating GPU resources into CI/CD pipelines and automated ML workflows.

Q: Which provider has better container and Docker support?

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

Crusoe and Vultr represent distinct approaches in the GPU cloud market for AI/ML workloads. Crusoe positions itself as a climate-aligned provider, leveraging stranded energy sources like flared natural gas to power high-performance computing with a reduced carbon footprint. This appeals to organizations prioritizing ESG compliance, particularly for batch-oriented training where sustainability metrics matter. Its vertically integrated model from energy to cloud enables efficient, cost-effective GPU access via per-hour billing and spot instances, though its geographic footprint is limited, primarily in the US. Vultr, conversely, is a global cloud provider with over 32 regions, offering broad deployment flexibility and integrated services like Kubernetes and storage. Ideal for latency-sensitive or distributed workloads, Vultr emphasizes scalability and compliance (SOC 2, HIPAA, GDPR, ISO 27001), but lacks Crusoe's sustainability focus. Key differentiators include Crusoe's environmental edge and spot pricing for cost savings on interruptible jobs, versus Vultr's extensive global reach for production-scale inference. Both support SOC 2 and GDPR, but Vultr adds HIPAA and ISO. For ML engineers, Crusoe suits eco-conscious batch training, while Vultr excels in multi-region deployments. Overall, value hinges on priorities: sustainability and cost for Crusoe, or ubiquity and services for Vultr. (218 words)

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Our Recommendation

Choose Crusoe for teams with ESG mandates, focusing on large-scale batch training or inference where carbon tracking is required; it's ideal for mid-sized teams (10-50 engineers) running interruptible workloads on spot instances to minimize costs, especially if US-centric locations suffice. Budget-conscious users benefit from its energy-efficient pricing, but avoid if low-latency global access is needed due to limited regions. Opt for Vultr when global low-latency inference, multi-region data residency, or integrated services like managed Kubernetes are priorities; suits larger teams (50+) with diverse workloads, production environments needing HIPAA compliance, or frequent small-scale experiments across continents. Vultr's scale favors steady-state usage without spot risks, though it may cost more for pure GPU bursts. For hybrid needs, evaluate total cost including data transfer—Crusoe for green batch, Vultr for distributed prod. (142 words)

Live Pricing

Compare real-time GPU offers from Crusoe and Vultr

65 offers available

Provider	GPU Model	VRAM	Host Specs	Region	Price	Status
QuantaCloud Partner	A100 · H100 / H200 32–1024+ GPUs · InfiniBand	∞	Custom configs	Multiple DCs	Reserved / cluster Get a quote in 24h	Available
Crusoe	NVIDIA A40 48GB VRAM	48GB	0 vCPU 0GB RAM	United States	$0.40/GPU/hr
Vultr	8×NVIDIA A16 64GB VRAM	64GB	48 vCPU 496GB RAM 1500GB Storage	New Jersey	$0.47/GPU/hr $3.77/hr total (8×)	Sold Out
Vultr	8×NVIDIA A16 64GB VRAM	64GB	48 vCPU 496GB RAM 1500GB Storage	Frankfurt	$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	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

A100 · H100 / H200

32–1024+ GPUs · InfiniBand

Reserved / cluster

Get a quote in 24h

Crusoe

United States

NVIDIA A40

48GB VRAM

0 vCPU

0GB RAM

$0.40/GPU/hr

Vultr

New Jersey

Sold Out

NVIDIA A168x

64GB VRAM

48 vCPU

496GB RAM

1500GB Storage

$0.47/GPU/hr

$3.77/hr total (8×)

Vultr

Frankfurt

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

Atlanta

Sold Out

NVIDIA A168x

64GB VRAM

48 vCPU

496GB RAM

1500GB Storage

$0.47/GPU/hr

$3.77/hr total (8×)

View all 65 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

Crusoe(Est. 2018)

A climate-aligned computing provider powering high-performance computing using stranded energy sources to mitigate environmental impact.

Best For

Organizations with strict ESG mandatesBatch training workloads where carbon footprint is a key metric

Unique Features

Vertically integrated energy-to-cloud model
Use of stranded energy sources

Limitations

Smaller geographic footprint compared to hyperscalers

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	Crusoe	Vultr
SSH
Jupyter Notebooks
Web Terminal
API
Kubernetes
Containers

Billing Options

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

Compliance

Certification	Crusoe	Vultr
SOC 2
HIPAA
GDPR
ISO 27001

Support

Feature	Crusoe	Vultr
SLA
Enterprise Support
Discord Community

Pricing Analysis

Pricing Overview

Both providers use per-hour billing for GPUs, minimizing short-job overhead compared to per-second models elsewhere. Crusoe differentiates with spot instances, offering deep discounts (up to 70-90% off on-demand) for interruptible workloads, ideal for fault-tolerant ML training but risky for stateful jobs due to preemption. Vultr sticks to on-demand hourly rates without native spot, providing predictability but potentially higher costs for sporadic use; no reserved instances mentioned for either, though Crusoe's energy model may yield inherent savings. Implications: Spot suits bursty, checkpointable patterns like hyperparameter sweeps, saving 50%+ vs Vultr's steady rates. Steady production favors Vultr's reliability, while long-running jobs benefit from either's hourly granularity over monthly commitments. Data egress fees apply similarly, but Crusoe's US focus may lower internal transfers. (152 words)

Value Assessment

Crusoe delivers superior value for large training runs and batch inference via spot pricing, potentially halving costs for 100+ GPU hours on A100/H100 clusters, especially for ESG-aligned budgets under $10k/month. Small experiments see less edge without spot scale. Vultr offers better value for real-time inference needing global regions, avoiding spot interruptions; consistent pricing suits production at $5-20k/month scales. For fine-tuning/experimentation, Vultr's multi-region access justifies 10-20% premium over Crusoe's spots if latency <50ms matters. Overall, Crusoe wins cost/value for interruptible batch (e.g., 80% savings on failed jobs), Vultr for reliable, distributed inference. Teams blending both should hybrid via spot for dev, on-demand for prod. (148 words)

Use Case Comparison

LLM Training

Crusoe recommended

Crusoe

Crusoe excels for large-scale LLM training with spot instances enabling cost-effective multi-GPU clusters (A100/H100) using stranded energy for low-carbon batch jobs. Vertical integration ensures high availability for sustained runs, suiting checkpointed workflows tolerant of rare preemptions. ESG reporting appeals to enterprise teams, though limited regions constrain data locality.

Vultr

Vultr supports LLM training via global GPU access, facilitating distributed setups across 32+ regions for data-parallelism. On-demand stability avoids spot risks, with integrated storage/K8s easing orchestration, but lacks sustainability metrics and may cost more for prolonged high-utilization runs.

Batch Inference

Crusoe recommended

Crusoe

Ideal for batch inference on Crusoe: spot pricing slashes costs for high-throughput jobs on efficient GPUs, with energy model reducing footprint. Handles variable loads well via autoscaling, perfect for periodic scoring where interruptions are manageable via queuing.

Vultr

Vultr handles batch inference reliably across regions, leveraging global storage for input/output distribution. Predictable billing suits scheduled jobs, but without spots, value dips for infrequent bursts compared to Crusoe.

Real-time Inference

Vultr recommended

Crusoe

Crusoe is less optimal for real-time inference due to smaller footprint, potentially higher latency outside US. Spot unreliability disrupts SLAs; better for non-latency-critical serving but lacks global edge presence.

Vultr

Vultr shines with 32+ regions for low-latency real-time inference, enabling edge deployments near users. Managed services and networking support autoscaling for production traffic, ensuring <100ms responses globally.

Fine-tuning & Experimentation

Either works

Crusoe

Crusoe suits experimentation with affordable spot GPUs for rapid iterations on smaller models/datasets. Sustainability tracking aids grant-funded or green projects, though regional limits may slow data syncing.

Vultr

Vultr's global scale and quick provisioning favor fast experimentation across teams/timezones, with integrated tools reducing setup. Hourly billing fits short runs without commitment.

Technical Comparison

Infrastructure

Crusoe emphasizes bare-metal GPUs with high-speed NVLink for multi-node scaling, vertically integrated for low-latency energy delivery; supports Kubernetes but focuses on raw HPC perf. Limited to ~5 US/Western regions. Vultr offers virtualized/managed GPUs (A100/H100) across 32+ global DCs, with robust networking (up to 100Gbps), block/object storage, and native Kubernetes/orchestration. Both provide high I/O NVMe storage, but Vultr's edge in managed services eases ops. (102 words)

Performance

Both deliver strong GPU perf with H100/A100 availability; Crusoe's bare-metal yields peak FLOPS for training (e.g., 2x inter-node bandwidth via custom fab), excelling in batch scaling. Vultr matches single-node but may lag multi-GPU due to virtualization overhead (~5-10%); global redundancy ensures higher uptime/availability. Known: Crusoe faster for sustained batch (energy efficiency), Vultr better for diverse workloads. Preemptions on Crusoe spots noted, Vultr more consistent. (98 words)

Frequently Asked Questions

Which provider offers spot instances for cost savings?▾

Crusoe 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, Crusoe would be the better choice.

What is the minimum billing increment for each provider?▾

Crusoe bills per-hour, while Vultr bills per-hour. Both providers use the same billing granularity, so this factor won't differentiate your decision.

Which provider has better compliance certifications for enterprise use?▾

Crusoe holds SOC 2, GDPR certifications. Vultr holds SOC 2, HIPAA, GDPR, ISO 27001 certifications. For organizations with strict compliance requirements, Vultr offers more comprehensive coverage.

Which provider offers better development tools like Jupyter notebooks?▾

Neither provider offers built-in Jupyter notebook support, so you'll need to set up your own development environment. Both providers support SSH access, allowing you to install JupyterLab or other tools on your instances. Additionally, Vultr offers web-based terminal access for quick debugging.

Which provider has better Kubernetes support for orchestration?▾

Both Crusoe 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?▾

Crusoe is best suited for Organizations with strict ESG mandates; Batch training workloads where carbon footprint is a key metric. 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 Crusoe 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?▾

Crusoe offers dedicated enterprise support options, while Vultr may have more limited support tiers.

Which provider has better API and automation support?▾

Both Crusoe and Vultr provide APIs for programmatic instance management, enabling automation of provisioning, scaling, and teardown operations. This is essential for integrating GPU resources into CI/CD pipelines and automated ML workflows.

Which provider has better container and Docker support?▾

Crusoe offers native container support for running Docker images, while Vultr 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?▾

Crusoe's standout features include: Vertically integrated energy-to-cloud model; Use of stranded energy sources. 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 Crusoe, visit their website at https://crusoe.ai?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.