Provider Comparison

Crusoe vs Latitude.sh

Q: Which provider offers better spot instance pricing?

Both Crusoe and Latitude.sh offer spot/preemptible instances, which can reduce costs by 50-80% compared to on-demand pricing. Spot instances are ideal for fault-tolerant workloads like batch inference, hyperparameter tuning, and distributed training with checkpointing. The actual savings depend on current demand and GPU availability, so we recommend comparing real-time spot prices for your specific GPU requirements on both platforms.

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

Crusoe bills per-hour, while Latitude.sh 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. Latitude.sh holds SOC 2, GDPR 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?

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.

Q: Which provider has better Kubernetes support for orchestration?

Both Crusoe and Latitude.sh 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. Latitude.sh excels at Latency-sensitive edge applications; Latin American market. 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 Latitude.sh 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 Crusoe and Latitude.sh offer enterprise support tiers with dedicated assistance, faster response times, and potentially custom SLAs. Regarding SLAs: Crusoe has no published SLA; Latitude.sh offers SLA guarantees (100% uptime).

Q: Which provider has better API and automation support?

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

Q: Which provider has better container and Docker support?

Both Crusoe and Latitude.sh support containerized workloads, allowing you to deploy Docker images with your ML frameworks, dependencies, and models pre-configured. This ensures reproducibility and simplifies deployment across development, staging, and production environments.

Crusoe and Latitude.sh are specialized GPU cloud providers catering to machine learning and AI workloads, but they differ significantly in focus and capabilities. Crusoe positions itself as a climate-aligned computing provider, leveraging stranded energy sources for high-performance computing with a strong emphasis on sustainability. It excels for organizations prioritizing ESG compliance and batch-oriented workloads like model training, where carbon footprint metrics are critical. Its vertically integrated energy-to-cloud model ensures efficient power usage, though its smaller geographic footprint limits global latency options compared to hyperscalers. In contrast, Latitude.sh offers global bare-metal infrastructure optimized for latency-sensitive edge applications, with a strong presence in Latin America. Its Metal-as-Code platform integrates seamlessly with Terraform, enabling rapid provisioning of dedicated hardware for production environments. This makes it ideal for real-time inference and edge computing where low latency and bare-metal performance are paramount. Key differentiators include Crusoe's sustainable energy sourcing and ESG alignment versus Latitude.sh's global reach and developer-friendly automation. Both provide per-hour billing with spot instances and SOC 2/GDPR compliance, appealing to cost-conscious ML teams. Crusoe delivers value for environmentally conscious, compute-intensive batch jobs, while Latitude.sh shines in distributed, low-latency deployments. ML engineers should evaluate based on workload type, latency needs, and sustainability goals for optimal fit.

Visit Crusoe Visit Latitude.sh

Our Recommendation

Choose Crusoe for large-scale batch training or inference workloads where ESG mandates and carbon efficiency are priorities, especially for teams of 10+ engineers managing sustained GPU clusters (e.g., LLM pre-training). Its sustainable model suits budgets focused on long-term cost-per-flop with spot savings, but verify regional availability for data sovereignty. Opt for Latitude.sh when latency-sensitive real-time inference or edge AI is key, particularly for Latin American markets or global deployments requiring sub-10ms latencies. It's ideal for smaller teams (5-15 members) using Terraform for IaC, with flexible bare-metal scaling. Budget-wise, both offer competitive per-hour spot pricing, but Latitude.sh provides better value for interruptible short bursts or production uptime. For hybrid needs, start with pilots to assess networking and GPU interconnects.

Live Pricing

Compare real-time GPU offers from Crusoe and Latitude.sh

30 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
Crusoe	NVIDIA L40S 48GB VRAM	48GB	0 vCPU 0GB RAM	United States	$0.50/GPU/hr
Latitude.sh	NVIDIA L40S 48GB VRAM	48GB	16 vCPU 128GB RAM 500GB Storage	United States	$0.74/GPU/hr	Sold Out
Latitude.sh	NVIDIA L40S 48GB VRAM	48GB	16 vCPU 128GB RAM 500GB Storage	United States	$0.74/GPU/hr	Sold Out
Latitude.sh	NVIDIA L40S 48GB VRAM	48GB	16 vCPU 128GB RAM 500GB Storage	Germany	$0.87/GPU/hr	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

Crusoe

United States

NVIDIA L40S

48GB VRAM

0 vCPU

0GB RAM

$0.50/GPU/hr

Latitude.sh

United States

Sold Out

NVIDIA L40S

48GB VRAM

16 vCPU

128GB RAM

500GB Storage

$0.74/GPU/hr

Latitude.sh

United States

Sold Out

NVIDIA L40S

48GB VRAM

16 vCPU

128GB RAM

500GB Storage

$0.74/GPU/hr

Latitude.sh

Germany

Sold Out

NVIDIA L40S

48GB VRAM

16 vCPU

128GB RAM

500GB Storage

$0.87/GPU/hr

View all 30 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

Latitude.sh(Est. 2001)

A global bare-metal cloud infrastructure provider offering latency-sensitive edge applications.

Best For

Latency-sensitive edge applicationsLatin American market

Unique Features

Metal-as-Code platform integrating with Terraform
Global bare-metal infrastructure

Feature Comparison

Access Methods

Feature	Crusoe	Latitude.sh
SSH
Jupyter Notebooks
Web Terminal
API
Kubernetes
Containers

Billing Options

Feature	Crusoe	Latitude.sh
Billing Increment	per-hour	per-hour
Spot Instances
Reserved Instances
Prepaid Credits

Compliance

Certification	Crusoe	Latitude.sh
SOC 2
HIPAA
GDPR
ISO 27001

Support

Feature	Crusoe	Latitude.sh
SLA
Enterprise Support
Discord Community

Pricing Analysis

Pricing Overview

Both Crusoe and Latitude.sh employ per-hour billing with spot instances, diverging from per-second models of hyperscalers like AWS or GCP. This suits longer ML workloads (e.g., >2 hours) by minimizing billing granularity overhead, but can lead to overcharges for quick experiments. Spot instances enable 50-70% discounts versus on-demand, ideal for fault-tolerant batch jobs, though interruptions require checkpointing. Neither prominently advertises reserved instances, focusing on flexible pay-as-you-go. Crusoe's energy-efficient model may indirectly lower costs via optimized power usage, while Latitude.sh's bare-metal avoids virtualization overhead, potentially reducing effective pricing for high-utilization runs. Implications: Spot favors preemptible training; on-demand suits production inference. Teams should monitor spot availability patterns, as Crusoe's stranded energy might yield more consistent pricing in energy-abundant regions.

Value Assessment

Crusoe offers superior value for large training runs (e.g., multi-day LLM jobs) due to sustainable energy reducing operational costs and spot reliability for batch workloads, potentially 20-30% cheaper on total flops for ESG-aligned budgets. Latitude.sh excels in small experiments and fine-tuning, where bare-metal provisioning speed and global spots minimize setup time, delivering better $/hour for <4-hour jobs. For production inference, Latitude.sh's edge locations provide higher value via low-latency without premium pricing. Both are cost-competitive against CoreWeave/Lambda for A100/H100s, but Crusoe edges batch scale; Latitude.sh wins intermittent use. Uncertainty exists on exact spot rates—benchmark via consoles for current pricing.

Use Case Comparison

LLM Training

Crusoe recommended

Crusoe

Crusoe excels for LLM training with scalable GPU clusters optimized for batch HPC, leveraging stranded energy for cost-efficient, sustainable multi-node scaling. Ideal for large-scale pre-training where ESG reporting is needed; supports high-bandwidth interconnects for efficient all-reduce. Limitations include fewer regions, potentially increasing data transfer costs.

Latitude.sh

Latitude.sh suits LLM training via bare-metal GPUs with Terraform automation for quick cluster spins, but its edge focus may limit massive-scale interconnects compared to dedicated HPC. Strong for distributed training in LatAm, though less emphasis on sustained batch efficiency.

Batch Inference

Either works

Crusoe

Crusoe's energy-efficient infrastructure handles large batch inference reliably with spot instances, minimizing carbon impact for offline scoring jobs. Vertically integrated model ensures stable power for long queues, fitting ESG-driven enterprises processing petabyte-scale datasets.

Latitude.sh

Latitude.sh provides bare-metal for high-throughput batch inference, with global spots reducing costs; Terraform eases scaling across regions. Better for distributed batches needing low-latency aggregation, but lacks Crusoe's sustainability edge.

Real-time Inference

Latitude.sh recommended

Crusoe

Crusoe supports real-time inference but its limited geo-footprint hinders ultra-low latency; better for regional services where sustainability trumps edge proximity. GPU scaling works, but not optimized for sub-ms responses.

Latitude.sh

Latitude.sh is purpose-built for real-time inference with edge bare-metal deployments, offering <10ms latencies globally, especially LatAm. Metal-as-Code enables fast autoscaling for production traffic spikes.

Fine-tuning & Experimentation

Latitude.sh recommended

Crusoe

Crusoe fits experimentation with spot GPUs for cost-effective LoRA/PEFT runs, but hourly billing may inflate short-job costs. Sustainability appeals for iterative green ML dev.

Latitude.sh

Latitude.sh shines for rapid prototyping via instant bare-metal + Terraform, ideal for bursty fine-tuning. Global availability accelerates testing across models/locations.

Technical Comparison

Infrastructure

Crusoe emphasizes virtualized GPU clusters for AI/HPC with Kubernetes support, high-speed NVLink/InfiniBand for multi-GPU/node scaling, and durable block storage. Its energy-to-cloud integration prioritizes compute density over broad networking. Latitude.sh delivers dedicated bare-metal servers (no hypervisor overhead) with Terraform-native provisioning, global data centers including edge PoPs, and flexible storage/NIC options; strong Kubernetes compatibility via Metal-as-Code for custom stacks.

Performance

Both offer A100/H100 GPUs with strong single-node perf; Crusoe optimizes multi-node training via efficient scaling (e.g., 100+ GPU clusters) and low-jitter from stable energy. Latitude.sh provides raw bare-metal speeds (<1% overhead), excelling in low-latency networking (e.g., 100Gbps+) for inference. GPU availability is comparable, but Crusoe reports better batch throughput; Latitude.sh faster provisioning (minutes). Limited public benchmarks—test NVMe IOPS and inter-node bandwidth for workloads.

Frequently Asked Questions

Which provider offers better spot instance pricing?▾

Both Crusoe and Latitude.sh offer spot/preemptible instances, which can reduce costs by 50-80% compared to on-demand pricing. Spot instances are ideal for fault-tolerant workloads like batch inference, hyperparameter tuning, and distributed training with checkpointing. The actual savings depend on current demand and GPU availability, so we recommend comparing real-time spot prices for your specific GPU requirements on both platforms.

What is the minimum billing increment for each provider?▾

Crusoe bills per-hour, while Latitude.sh 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. Latitude.sh holds SOC 2, GDPR 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?▾

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.

Which provider has better Kubernetes support for orchestration?▾

Both Crusoe and Latitude.sh 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. Latitude.sh excels at Latency-sensitive edge applications; Latin American market. 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 Latitude.sh 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 Crusoe and Latitude.sh offer enterprise support tiers with dedicated assistance, faster response times, and potentially custom SLAs. Regarding SLAs: Crusoe has no published SLA; Latitude.sh offers SLA guarantees (100% uptime).

Which provider has better API and automation support?▾

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

Which provider has better container and Docker support?▾

Both Crusoe and Latitude.sh support containerized workloads, allowing you to deploy Docker images with your ML frameworks, dependencies, and models pre-configured. This ensures reproducibility and simplifies deployment across development, staging, and production environments.

What unique features differentiate these providers?▾

Crusoe's standout features include: Vertically integrated energy-to-cloud model; Use of stranded energy sources. Latitude.sh's standout features include: Metal-as-Code platform integrating with Terraform; Global bare-metal infrastructure. 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 Latitude.sh, visit https://www.latitude.sh/r/C98A392A?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.