Provider Comparison

Cirrascale vs Vast.ai

Cirrascale and Vast.ai represent contrasting approaches in the GPU cloud market for ML/AI workloads. Cirrascale positions itself as an AI Innovation Cloud, emphasizing dedicated, non-virtualized bare-metal servers optimized for deep learning and HPC research. It targets research teams requiring consistent multi-GPU performance for extended training jobs, offering a diverse hardware portfolio including NVIDIA, AMD, and Qualcomm accelerators. Its monthly billing model ensures predictable costs for long-term commitments but limits flexibility for bursty usage, with no spot instances available. In contrast, Vast.ai operates as a decentralized peer-to-peer marketplace, prioritizing absolute lowest costs through granular bidding on hourly rentals, including spot instances. Ideal for cost-sensitive users and distributed experiments, it provides advanced search filters like DLPerf/$ for performance-per-dollar optimization and supports GDPR compliance. However, its virtualized, crowd-sourced nature can introduce variability in reliability and performance consistency. Key differentiators include Cirrascale's bare-metal reliability versus Vast.ai's marketplace-driven cost savings. Cirrascale excels in production-grade stability for resource-intensive tasks, while Vast.ai offers unmatched affordability for prototyping and experimentation. Overall, Cirrascale delivers premium value for mission-critical workloads, whereas Vast.ai maximizes ROI for budget-constrained, intermittent needs, making the choice dependent on workload duration, consistency requirements, and cost tolerance.

Visit Cirrascale Visit Vast.ai

Our Recommendation

Choose Cirrascale for large research teams (10+ members) running prolonged, multi-GPU training jobs like LLMs, where bare-metal consistency and diverse accelerators (e.g., AMD MI300X or NVIDIA H100s) outweigh higher costs. It's ideal for budgets with stable monthly allocations exceeding $10K, prioritizing uptime over elasticity. Opt for Vast.ai when budget is paramount (<$5K/month), for solo developers or small teams (1-5 members) focused on rapid experimentation, fine-tuning, or distributed tasks. Its per-hour spot pricing suits bursty workloads, though expect potential interruptions. For hybrid needs, start with Vast.ai for proofs-of-concept before scaling to Cirrascale for production. Technical teams should evaluate based on tolerance for variability versus need for dedicated networking and storage.

Live Pricing

Compare real-time GPU offers from Cirrascale and Vast.ai

99 offers available

Provider	GPU Model	VRAM	Host Specs	Region	Price	Status
Vast.ai	8×NVIDIA GeForce RTX 3060 12GB VRAM	12GB	24 vCPU 126GB RAM 738GB Storage	Quebec	$0.00/GPU/hr $0.01/hr total (8×)	Sold Out
Vast.ai	6×NVIDIA GeForce RTX 3080 Ti 12GB VRAM	12GB	8 vCPU 94GB RAM 1527GB Storage	Ukraine	$0.01/GPU/hr $0.04/hr total (6×)	Sold Out
Vast.ai	6×NVIDIA GeForce RTX 3080 Ti 12GB VRAM	12GB	8 vCPU 94GB RAM 1660GB Storage	Ukraine	$0.01/GPU/hr $0.04/hr total (6×)	Sold Out
Vast.ai	NVIDIA GeForce RTX 3060 12GB VRAM	12GB	4 vCPU 23GB RAM 670GB Storage	Turkey	$0.01/GPU/hr	Sold Out
Vast.ai	NVIDIA GeForce RTX 2080 Ti 11GB VRAM	11GB	16 vCPU 31GB RAM 1549GB Storage	Georgia	$0.01/GPU/hr	Sold Out

Vast.ai

Quebec

Sold Out

NVIDIA GeForce RTX 30608x

12GB VRAM

24 vCPU

126GB RAM

738GB Storage

625 Mbps ↑

626 Mbps ↓

$0.00/GPU/hr

$0.01/hr total (8×)

Vast.ai

Ukraine

Sold Out

NVIDIA GeForce RTX 3080 Ti6x

12GB VRAM

8 vCPU

94GB RAM

1527GB Storage

$0.01/GPU/hr

$0.04/hr total (6×)

Vast.ai

Ukraine

Sold Out

NVIDIA GeForce RTX 3080 Ti6x

12GB VRAM

8 vCPU

94GB RAM

1660GB Storage

394 Mbps ↑

689 Mbps ↓

$0.01/GPU/hr

$0.04/hr total (6×)

Vast.ai

Turkey

Sold Out

NVIDIA GeForce RTX 3060

12GB VRAM

4 vCPU

23GB RAM

670GB Storage

21 Mbps ↑

99 Mbps ↓

$0.01/GPU/hr

Vast.ai

Georgia

Sold Out

NVIDIA GeForce RTX 2080 Ti

11GB VRAM

16 vCPU

31GB RAM

1549GB Storage

722 Mbps ↑

388 Mbps ↓

$0.01/GPU/hr

View all 99 offers

Cirrascale(Est. 2010)

An AI Innovation Cloud targeting deep learning and HPC research with dedicated performance on non-virtualized hardware.

Best For

Research teams needing consistent, non-virtualized multi-GPU performance for long-training jobs

Unique Features

Diverse hardware stack including Qualcomm, AMD, and NVIDIA accelerators
Bare-metal dedicated servers

Limitations

Lack of spot elasticity
Monthly billing model prohibiting short-term burst usage

Vast.ai(Est. 2018)

A decentralized marketplace for absolute lowest costs and distributed experiments.

Best For

Absolute lowest costsDistributed experiments

Unique Features

Granular search filters like DLPerf/$
Decentralized marketplace

Feature Comparison

Access Methods

Feature	Cirrascale	Vast.ai
SSH
Jupyter Notebooks
Web Terminal
API
Kubernetes
Containers

Billing Options

Feature	Cirrascale	Vast.ai
Billing Increment	monthly	per-hour
Spot Instances
Reserved Instances
Prepaid Credits

Compliance

Certification	Cirrascale	Vast.ai
SOC 2
HIPAA
GDPR
ISO 27001

Support

Feature	Cirrascale	Vast.ai
SLA
Enterprise Support
Discord Community

Pricing Analysis

Pricing Overview

Cirrascale employs a monthly billing model for dedicated bare-metal servers, requiring upfront commitments (e.g., 1-month minimums) without spot or on-demand options. This suits sustained usage but penalizes short-term needs, potentially leading to overprovisioning for bursts. Vast.ai uses per-hour billing with spot instances (interruptible for ~30-70% discounts) and on-demand rentals, enabling granular control via marketplace bidding. No reserved instances are standard, but dynamic pricing reflects supply/demand. Implications: Cirrascale favors predictable long-run costs (e.g., $5-20/hr effective for H100s over months), while Vast.ai excels for variable patterns, minimizing idle spend but risking bid competition during peaks.

Value Assessment

Vast.ai offers superior value for small experiments and fine-tuning, where spot H100s can drop below $1/hr, yielding 2-5x savings versus Cirrascale's $4-10/hr equivalents. For large training runs (>100 GPU-hours), Cirrascale provides better value through consistent bare-metal scaling, avoiding Vast.ai's reliability overhead. Production inference favors Cirrascale's dedicated uptime, while Vast.ai shines for batch inference with cost-per-token optimization via DLPerf/$. Budgets under $1K/month tilt to Vast.ai; sustained >$20K/month workloads favor Cirrascale's efficiency despite premiums.

Use Case Comparison

LLM Training

Cirrascale recommended

Cirrascale

Cirrascale excels with bare-metal multi-GPU servers (e.g., 8x H100 or AMD MI300X), ensuring consistent NVLink scaling and no virtualization overhead for week-long jobs. Diverse hardware supports specialized models, ideal for research stability.

Vast.ai

Vast.ai provides cheap multi-GPU rigs via marketplace, but spot interruptions and host variability can disrupt long trainings. DLPerf/$ filtering helps select performant hosts, suiting cost-optimized runs under 24 hours.

Batch Inference

Vast.ai recommended

Cirrascale

Dedicated servers offer reliable throughput for large batches, with fast local NVMe storage minimizing latency. Monthly model efficient for recurring jobs, though less flexible for sporadic volumes.

Vast.ai

Spot instances enable massive parallelism at low cost, with easy scaling via marketplace. Granular filters optimize for inference perf/$, perfect for variable, high-volume non-real-time tasks.

Real-time Inference

Cirrascale recommended

Cirrascale

Bare-metal low-latency networking and dedicated resources ensure sub-100ms responses, suitable for production APIs with consistent QoS. Lacks auto-scaling but guarantees isolation.

Vast.ai

On-demand rentals work for low-latency needs, but decentralized hosts introduce jitter and uptime risks. Better for dev/testing than mission-critical serving.

Fine-tuning & Experimentation

Vast.ai recommended

Cirrascale

Stable environment good for iterative tuning on premium hardware, but monthly billing inflates costs for short 1-4 hour runs, limiting burst experimentation.

Vast.ai

Ideal for rapid, cheap trials with per-hour spots under $0.50/hr for A100s. Marketplace variety and filters enable quick hardware swaps for hyperparameter sweeps.

Technical Comparison

Infrastructure

Cirrascale delivers non-virtualized bare-metal servers with high-speed InfiniBand/RoCE networking, local NVMe storage (up to 100TB+), and no Kubernetes native but supports container orchestration. Vast.ai virtualizes crowd-sourced hardware, offering varied networking (1-100Gbps), block storage attachments, and Docker/K8s compatibility via hosts. Cirrascale ensures isolation; Vast.ai provides flexibility but potential single-tenant variability.

Performance

Cirrascale guarantees consistent multi-GPU scaling (e.g., full NVLink on 8x GPUs) with low jitter for long jobs; diverse options like Qualcomm AI100 suit edge models. Vast.ai GPUs (A100/H100 dominant) score via DLPerf benchmarks, enabling perf/$ selection, but scaling depends on host configs with occasional interconnect limits. Cirrascale edges in reliability; Vast.ai in availability/cost for singles.

Frequently Asked Questions

Which provider offers spot instances for cost savings?▾

Vast.ai 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. Cirrascale 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, Vast.ai would be the better choice.

What is the minimum billing increment for each provider?▾

Cirrascale bills monthly, while Vast.ai 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?▾

Cirrascale holds no publicly listed certifications. Vast.ai holds GDPR certification. For organizations with strict compliance requirements, Vast.ai offers more comprehensive coverage.

Which provider offers better development tools like Jupyter notebooks?▾

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

Which provider has better Kubernetes support for orchestration?▾

Cirrascale offers native Kubernetes support for container orchestration, while Vast.ai does not. If you're building production ML pipelines with Kubernetes-based tools like Kubeflow, Argo, or KServe, Cirrascale will integrate more seamlessly with your workflow.

What is each provider best suited for?▾

Cirrascale is best suited for Research teams needing consistent, non-virtualized multi-GPU performance for long-training jobs. Vast.ai excels at Absolute lowest costs; Distributed experiments. 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?▾

Cirrascale offers reserved instance pricing for long-term commitments, while Vast.ai does not currently offer this option. 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?▾

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

Which provider has better API and automation support?▾

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

Which provider has better container and Docker support?▾

Vast.ai offers native container support for running Docker images, while Cirrascale 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?▾

Cirrascale's standout features include: Diverse hardware stack including Qualcomm, AMD, and NVIDIA accelerators; Bare-metal dedicated servers. Vast.ai's standout features include: Granular search filters like DLPerf/$; Decentralized marketplace. 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 Cirrascale, visit their website at https://www.cirrascale.com?utm_source=gpuperhour&utm_medium=referral to create an account and explore available GPU options. For Vast.ai, visit https://cloud.vast.ai/?ref_id=375842&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.