Scientific Compute Kit

Accelerate simulations, analytics, and research pipelines with a deterministic, high memory workstation platform that is easy to deploy. Includes: high core CPU workstation, large ECC memory configuration, NVMe scratch storage, redundant bulk storage target, 10/25/100GbE networking option, UPS, surge protection, rugged transport.

Product photo of Skorppio rental kit
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WHAT'S INCLUDED

Complete Rental Workstation: Pre-Configured, Shipped & Ready to Deploy

Every Skorppio rental kit ships pre-configured with enterprise hardware, peripherals, and accessories — so your team can plug in and perform from day one.

Compute Devices
High-Core CPU Workstation

High core-count CPU workstation with large ECC memory for deterministic simulation and analytics pipelines.

Storage
NVMe Scratch + Redundant Bulk Storage

Fast NVMe scratch volume for active computation plus redundant bulk storage for datasets and results.

Networking
10/25/100GbE Networking Option

Flexible high-speed networking to connect to institutional clusters or move large datasets.

Power & Protection
UPS & Surge Protection

Uninterruptible power and surge protection to prevent data loss during long-running computations.

Transport
Rugged Transport Cases

Lab-to-site shipping in rugged transport cases with organized cable management.

Start Your Rental: Quote, Configure & Deploy in Days

Tell us what you need and we’ll build it. Custom configurations available.

RENT THIS KIT

Technical detail view of kit hardware

Use Cases

Rental Workstations for Every Professional Need

Purpose-built for the workflows that matter most to your team.

AI & Machine Learning

Train models, run inference, and process large datasets with GPU-accelerated workstations built for deep learning and high-performance compute workflows.

PyTorch · TensorFlow · CUDA · Jupyter · vLLM · Hugging Face · RAPIDS

Scientific Research

Accelerate computational research with workstations designed for large-scale data analysis, molecular modeling, and scientific visualization.

MATLAB · Python · R · GROMACS · OpenFOAM · ParaView · Gaussian

High-Speed Connections

Enterprise-Grade Rental Hardware: Specs & Reliability

High-speed connection ports and cabling detail

Thunderbolt 4 and 10GbE connectivity ensure maximum throughput for demanding production pipelines.

Enterprise-grade components and thermal management system

Enterprise-grade components rated for 24/7 operation with redundant power delivery and active thermal management.

Trusted by leading teams in AI, VFX, and innovation

How It Works

How Rental Works: From Quote to Deployment in 3 Steps

Step 01

Request a Quote

Tell us about your project requirements, timeline, and team size. We'll recommend the right kit configuration for your workload.

Step 02

We Configure & Ship

Your kit is assembled, tested, and pre-configured with your software stack. We handle logistics and deliver directly to your site.

Step 03

Plug In & Produce

Unbox, connect, and start working. Enterprise-grade support is included for the duration of your rental with same-day response times.

Questions? Answers.

Frequently Asked Questions

Is on-prem GPU rental cheaper than cloud computing?

For sustained workloads running four weeks or longer, on-prem rental typically costs 40 to 60 percent less than equivalent cloud GPU instances. Cloud billing compounds quickly — hourly instance fees plus egress charges on every data transfer, storage surcharges, and premium pricing for reserved capacity. A single A100 cloud instance can exceed $25,000 per month at sustained usage before egress and storage fees. On-prem rental gives you a flat weekly or monthly rate with no hidden surcharges. The rental price is the total price.

When should I use cloud GPUs instead of on-prem rental?

Cloud GPU is the right choice when you need massive elastic scale for short bursts. If your workload requires 500 GPUs for six hours, cloud delivers that flexibility better than any on-prem option. Cloud also makes sense for prototyping and experimentation where you need quick access to different GPU architectures without commitment, or for geographically distributed teams that need compute in multiple regions simultaneously. The crossover point is duration and predictability — once a workload runs steadily for weeks or months, on-prem rental almost always wins on cost and performance.

What workloads perform better on dedicated on-prem hardware than cloud?

Workloads that benefit most from on-prem rental share common traits: they run for weeks or months rather than hours, they move large datasets that would trigger cloud egress fees, they require deterministic latency that shared cloud tenancy cannot guarantee, or they fall under compliance frameworks like ITAR, HIPAA, or CMMC that mandate physical data control. Specific examples include sustained AI model training and fine-tuning, VFX rendering pipelines, real-time inference serving, large-scale simulation, and any workflow where GPU utilization stays above 50 percent for extended periods.

How does on-prem rental handle data sovereignty and compliance requirements?

On-prem rental hardware sits in your facility, on your network, behind your firewall. Your data never transits a third-party provider's infrastructure. This is a hard requirement for organizations operating under ITAR, HIPAA, CMMC, or internal data governance policies that prohibit shared cloud tenancy. Cloud providers offer compliance certifications, but the data still moves through shared infrastructure and provider-controlled networks. For air-gapped environments or workloads involving controlled unclassified information, on-prem rental is often the only deployment model that satisfies both the technical and regulatory requirements.

What is cloud repatriation and why are teams moving GPU workloads off cloud?

Cloud repatriation is the trend of organizations moving workloads from public cloud back to on-premise infrastructure. For GPU-intensive work, the drivers are consistent: unpredictable costs from egress fees and hourly billing, GPU scarcity on hyperscalers making H100 and A100 availability unreliable, performance variability from shared tenancy and noisy neighbors, and data sovereignty mandates that shared infrastructure cannot satisfy. Teams are not returning to traditional hardware ownership. They are choosing on-prem rental as a third option that delivers dedicated bare-metal performance and full data control without the capital burden of purchasing.

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