Provider Comparison

FluidStack vs Voltage Park

Q: Which provider offers spot instances for cost savings?

FluidStack 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. Voltage Park 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, FluidStack would be the better choice.

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

FluidStack bills per-minute, while Voltage Park bills per-hour. Consider your typical workload duration when evaluating which billing model offers better value for your use case.

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

FluidStack holds SOC 2, ISO 27001 certifications. Voltage Park holds SOC 2, HIPAA 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 FluidStack and Voltage Park 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?

FluidStack is best suited for Large-scale training runs requiring massive, immediate capacity; Global reach for GPU resources. Voltage Park excels at Massive scale H100 training. 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 FluidStack and Voltage Park 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?

FluidStack offers dedicated enterprise support options, while Voltage Park may have more limited support tiers.

Q: Which provider has better API and automation support?

Both FluidStack and Voltage Park 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?

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

FluidStack and Voltage Park represent two distinct approaches in the GPU cloud market for AI/ML workloads. FluidStack operates as a supercloud aggregator, providing a unified API to access GPU resources from a global network of Tier 1-4 data centers. This model excels in delivering massive, on-demand capacity for large-scale training, leveraging spare capacity for cost efficiency via spot instances and per-minute billing. It's ideal for teams needing immediate scalability across regions, with SOC 2 and ISO 27001 compliance ensuring enterprise-grade security. However, resource consistency can vary due to its multi-provider nature. Voltage Park, conversely, manages a dedicated 24,000 H100 GPU fleet backed by a non-profit organization, focusing exclusively on massive-scale H100 training. This setup offers predictable availability and high-performance clustering for prolonged, resource-intensive jobs, billed per-hour with SOC 2 and HIPAA compliance for sensitive workloads. Its non-profit structure may appeal to research-oriented users seeking reliable, high-density H100 access without aggregation overhead. FluidStack differentiates through flexibility and global reach, suiting bursty or geographically distributed workloads, while Voltage Park prioritizes H100 specialization and consistency for hyperscale training. Value propositions hinge on needs: FluidStack for cost-optimized bursts, Voltage for unwavering H100 throughput. Both cater to ML engineers tackling frontier models, but choice depends on scale predictability, GPU type specificity, and budget sensitivity.

Visit FluidStack Visit Voltage Park

Our Recommendation

Choose FluidStack for flexible, large-scale deployments requiring rapid provisioning of diverse GPUs across global data centers, especially with bursty workloads or spot pricing tolerance. It's suited for mid-to-large teams (10-100+ engineers) running intermittent massive trainings or needing multi-region low-latency, where per-minute billing minimizes costs for variable durations. Budget-conscious ops with tolerance for occasional variability favor it. Opt for Voltage Park when prioritizing a massive, dedicated H100 fleet for sustained, hyperscale training runs, ideal for research labs or enterprises with predictable, long-duration jobs (e.g., weeks-long LLM pretraining). Best for larger teams (50+) focused on H100s, where per-hour billing suits steady usage and HIPAA compliance addresses regulated data. High budgets for reliability over cost savings make it preferable; avoid if needing GPU variety or spot deals.

Live Pricing

Compare real-time GPU offers from FluidStack and Voltage Park

27 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
FluidStack	8×NVIDIA A100 SXM4 80GB 80GB VRAM	80GB	0 vCPU 0GB RAM	🌍Global	$1.30/GPU/hr $10.40/hr total (8×)
Voltage Park	8×NVIDIA H100 SXM5 80GB VRAM	80GB	208 vCPU 930GB RAM 99800GB Storage	Dallas, Texas	$1.89/GPU/hr $15.12/hr total (8×)
Voltage Park	8×NVIDIA H100 SXM5 80GB VRAM	80GB	208 vCPU 930GB RAM 99800GB Storage	Dallas, Texas	$1.89/GPU/hr $15.12/hr total (8×)
Voltage Park	8×NVIDIA H100 SXM5 80GB VRAM	80GB	208 vCPU 960GB RAM 14580GB Storage	Dallas, Texas	$1.89/GPU/hr $15.12/hr total (8×)
Voltage Park	8×NVIDIA H100 SXM5 80GB VRAM	80GB	208 vCPU 930GB RAM 99800GB Storage	Dallas, Texas	$1.89/GPU/hr $15.12/hr total (8×)

QuantaCloud

Partner

Available

A100 · H100 / H200

32–1024+ GPUs · InfiniBand

Reserved / cluster

Get a quote in 24h

FluidStack

🌍Global

NVIDIA A100 SXM4 80GB8x

80GB VRAM

0 vCPU

0GB RAM

$1.30/GPU/hr

$10.40/hr total (8×)

Voltage Park

Dallas, Texas

NVIDIA H100 SXM58x

80GB VRAM

208 vCPU

930GB RAM

99800GB Storage

$1.89/GPU/hr

$15.12/hr total (8×)

Voltage Park

Dallas, Texas

NVIDIA H100 SXM58x

80GB VRAM

208 vCPU

930GB RAM

99800GB Storage

$1.89/GPU/hr

$15.12/hr total (8×)

Voltage Park

Dallas, Texas

NVIDIA H100 SXM58x

80GB VRAM

208 vCPU

960GB RAM

14580GB Storage

$1.89/GPU/hr

$15.12/hr total (8×)

Voltage Park

Dallas, Texas

NVIDIA H100 SXM58x

80GB VRAM

208 vCPU

930GB RAM

99800GB Storage

$1.89/GPU/hr

$15.12/hr total (8×)

View all 27 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

FluidStack(Est. 2017)

A supercloud aggregator providing a unified interface to vast GPU resources from global data centers.

Best For

Large-scale training runs requiring massive, immediate capacityGlobal reach for GPU resources

Unique Features

Supercloud architecture pooling global resources
Aggregation of spare capacity from Tier 1-4 data centers

Limitations

Consistency may vary depending on underlying facility

Voltage Park(Est. 2023)

A provider operating a massive fleet of H100s backed by a non-profit for large-scale training.

Best For

Massive scale H100 training

Unique Features

24k H100 fleet
Non-profit backing

Feature Comparison

Access Methods

Feature	FluidStack	Voltage Park
SSH
Jupyter Notebooks
Web Terminal
API
Kubernetes
Containers

Billing Options

Feature	FluidStack	Voltage Park
Billing Increment	per-minute	per-hour
Spot Instances
Reserved Instances
Prepaid Credits

Compliance

Certification	FluidStack	Voltage Park
SOC 2
HIPAA
GDPR
ISO 27001

Support

Feature	FluidStack	Voltage Park
SLA
Enterprise Support
Discord Community

Pricing Analysis

Pricing Overview

FluidStack employs per-minute billing with spot instances, enabling granular cost control and up to 80% savings on spare capacity, alongside on-demand options. This favors short-to-medium bursts or interruptible jobs, reducing waste for variable runtimes common in experimentation. Voltage Park uses per-hour billing, likely on-demand or reserved for its H100 fleet, promoting predictability for long-haul trainings but less flexibility for sub-hour tasks—potentially incurring idle costs. No spot mentions for Voltage imply steady pricing, suiting committed usage. Implications: FluidStack suits opportunistic scaling with risk of interruptions; Voltage excels in budgeted, continuous runs. Teams with erratic patterns save via FluidStack's model, while Voltage minimizes billing surprises for fixed schedules.

Value Assessment

FluidStack delivers superior value for small experiments and fine-tuning via spot per-minute rates, slashing costs for <1-hour jobs or failures. Large training runs benefit from aggregated scale if interruptions are manageable, offering 2-3x savings vs on-demand. Less ideal for production inference needing 99.9% uptime. Voltage Park shines for massive H100 trainings, where dedicated fleet ensures no queuing and consistent perf, justifying per-hour costs for multi-week runs—better ROI for high-value pretraining vs FluidStack's variability. Weaker for batch/real-time inference lacking H100 focus or spot needs. Overall, FluidStack for cost-sensitive variability; Voltage for premium H100 reliability.

Use Case Comparison

LLM Training

Voltage Park recommended

FluidStack

FluidStack suits large-scale LLM training via global aggregation, enabling rapid access to thousands of GPUs for immediate starts. Spot instances cut costs for multi-day runs, but underlying DC variability may cause intermittent perf dips or interruptions, requiring fault-tolerant orchestration like Kubernetes autoscaling.

Voltage Park

Voltage Park excels with its 24k H100 fleet, optimized for massive, sustained LLM pretraining. Dedicated infrastructure ensures high multi-node scaling and reliability, minimizing downtime for weeks-long jobs, backed by non-profit focus on AI research.

Batch Inference

FluidStack recommended

FluidStack

FluidStack supports batch inference through flexible GPU access and spot pricing, ideal for high-volume, interruptible jobs across regions. Global reach aids distributed processing, though consistency varies, suiting non-latency-critical workloads with retry logic.

Voltage Park

Voltage Park's H100 density handles large batch inference efficiently, but per-hour billing and training focus may underutilize for sporadic batches. Strong for H100-optimized models, lacking spot flexibility.

Real-time Inference

Either works

FluidStack

FluidStack offers global low-latency options via unified interface, but aggregator variability risks inconsistent SLAs for real-time needs. Better for dev/testing than production serving requiring guaranteed throughput.

Voltage Park

Voltage Park's fleet prioritizes training over inference; limited details on serving infra make it less ideal for real-time, though H100 perf could support if configured, at higher per-hour costs without spot relief.

Fine-tuning & Experimentation

FluidStack recommended

FluidStack

FluidStack is excellent for rapid prototyping with per-minute spot access to varied GPUs, enabling quick iterations and cost savings on short, failed experiments across scales without long commitments.

Voltage Park

Voltage Park fits larger fine-tuning via H100s but per-hour billing inflates costs for small/frequent experiments. Best for scaled validation, less agile for solo or small-team tinkering.

Technical Comparison

Infrastructure

FluidStack's supercloud aggregates bare metal and virtualized GPUs from diverse DCs, offering unified APIs, global networking (low-latency interconnects where available), block/object storage, and Kubernetes compatibility. Flexibility spans GPU types but exposes variability in NVLink/RoCE fabrics. Voltage Park runs a proprietary 24k H100 cluster, likely bare metal with optimized InfiniBand for tight scaling, custom storage, and potential K8s support—tailored for homogeneous H100 density without multi-provider overhead.

Performance

FluidStack provides high GPU availability via pooling but multi-DC scaling may hit consistency issues (e.g., varying interconnect speeds), strong for 100s-1000s GPUs with spot bursts. Voltage Park offers superior H100 multi-node perf for 10k+ scale, predictable interconnects minimizing NCCL bottlenecks, though limited to H100s. Both scale well; FluidStack for diverse/rapid access, Voltage for sustained hyperscale—no public benchmarks, but dedicated fleet implies edge in training throughput.

Frequently Asked Questions

Which provider offers spot instances for cost savings?▾

FluidStack 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. Voltage Park 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, FluidStack would be the better choice.

What is the minimum billing increment for each provider?▾

FluidStack bills per-minute, while Voltage Park bills per-hour. Consider your typical workload duration when evaluating which billing model offers better value for your use case.

Which provider has better compliance certifications for enterprise use?▾

FluidStack holds SOC 2, ISO 27001 certifications. Voltage Park holds SOC 2, HIPAA 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 FluidStack and Voltage Park 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?▾

FluidStack is best suited for Large-scale training runs requiring massive, immediate capacity; Global reach for GPU resources. Voltage Park excels at Massive scale H100 training. 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 FluidStack and Voltage Park 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?▾

FluidStack offers dedicated enterprise support options, while Voltage Park may have more limited support tiers.

Which provider has better API and automation support?▾

Both FluidStack and Voltage Park 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?▾

FluidStack offers native container support for running Docker images, while Voltage Park 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?▾

FluidStack's standout features include: Supercloud architecture pooling global resources; Aggregation of spare capacity from Tier 1-4 data centers. Voltage Park's standout features include: 24k H100 fleet; Non-profit backing. 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 FluidStack, visit their website at https://www.fluidstack.io?utm_source=gpuperhour&utm_medium=referral to create an account and explore available GPU options. For Voltage Park, visit https://voltagepark.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.