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.
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.
High core-count CPU workstation with large ECC memory for deterministic simulation and analytics pipelines.
Fast NVMe scratch volume for active computation plus redundant bulk storage for datasets and results.
Flexible high-speed networking to connect to institutional clusters or move large datasets.
Uninterruptible power and surge protection to prevent data loss during long-running computations.
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
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
Enterprise-Grade Rental Hardware: Specs & Reliability
Thunderbolt 4 and 10GbE connectivity ensure maximum throughput for demanding production pipelines.
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
How much VRAM do I need to fine-tune a large language model?
The amount of VRAM you need depends on the model size, precision format, and fine-tuning method. Full fine-tuning of a 70B-parameter model in FP16 can require 140 GB or more of VRAM, while techniques like LoRA and QLoRA significantly reduce that footprint — sometimes to under 48 GB.
For multi-GPU setups, frameworks like DeepSpeed ZeRO and FSDP allow you to shard model states across GPUs, distributing memory requirements efficiently.
Skorppio workstations come equipped with up to 384 GB of VRAM (4× A6000) or 768 GB (8× A6000) in server configurations, giving you room to fine-tune the largest open models without compromise.
How quickly can I get hardware?
Most Skorppio systems ship within 48 hours of order confirmation, and some configurations are available for next-day delivery depending on your location and inventory. We maintain ready-to-ship inventory specifically for AI and ML workloads so you’re not waiting weeks for provisioning.
Can I run PyTorch, Hugging Face, and CUDA without modification?
Yes. Every Skorppio workstation and server ships with the full CUDA toolkit, compatible NVIDIA drivers, and a clean Ubuntu environment ready for your stack. PyTorch, Hugging Face Transformers, JAX, TensorFlow — all run natively. You get full root access, so you can install and configure anything you need without restrictions.
What is the minimum rental period?
Our minimum rental period is one week. Monthly rentals are available at a reduced rate, and we offer flexible terms for longer engagements. Whether you need a system for a sprint, a quarter, or an ongoing project, we’ll match the term to your timeline.
How does multi-GPU distributed fine-tuning work on PCIe?
Skorppio’s multi-GPU workstations use PCIe 5.0 x16 lanes, delivering up to 128 GB/s of bidirectional bandwidth per GPU. For distributed fine-tuning, frameworks like PyTorch DDP, FSDP, and DeepSpeed handle gradient synchronization and model sharding efficiently over PCIe — no NVLink required for most workloads.
PCIe-based systems are ideal for data-parallel training, LoRA/QLoRA fine-tuning, and inference pipelines where each GPU processes independently or shares lightweight updates. You get the multi-GPU benefit without the premium of NVLink for workloads that don’t require ultra-high inter-GPU bandwidth.
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