SLYD
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The 5-step pipeline.

How energy turns into a deployed, financed, offtake-matched cluster, and what SLYD does at every step.

How SLYD works →
Hardware

New and recovered GPU systems.

NVIDIA and AMD systems through documented manufacturer and qualified channel supply, with financing and deployment coordinated on the same platform.

Explore GPU hardware →
Marketplace

Compute, hardware, and power in one book.

Browse available GPU capacity by accelerator, configuration, region, and price, or bring supply to qualified demand.

Open marketplace →
Pre-qualify

Start with an indicative structure.

Tell us deal size, structure, and offtake. Any range is preliminary and subject to underwriting, diligence, and documentation.

Open Configure →
From the blog

GPU market trends and deployment playbooks.

Infrastructure best practices, hardware comparisons, and industry analysis from the SLYD team.

Read the blog →

Library

Hardware & Infrastructure Marketplace

Enterprise Hardware Marketplace

Certified pre-owned and new AI infrastructure. Servers, GPUs, networking, data center equipment, and power infrastructure with competitive pricing and expert deployment support.

Products

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Pricing shown is indicative only, provided for budgeting purposes, and does not constitute a binding offer. Pricing and inventory availability are subject to change without notice and may fluctuate based on supplier availability, market conditions, currency movement, and end-user export-control review. Volume-based pricing applies; unit pricing varies depending on quantity purchased. Pricing shown is exclusive of shipping, freight, insurance, taxes, duties, tariffs, and any other transaction-related charges, all of which are the responsibility of the buyer unless otherwise agreed in writing. Final pricing, lead time, and terms will be confirmed by formal written quotation prior to order acceptance. Inventory is subject to prior sale.

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GPU Servers for AI Training & Inference

Complete systems from Dell, HPE, Supermicro, Lenovo, and Gigabyte — configured with NVIDIA and AMD accelerators. New and certified pre-owned inventory available.

What's Available

8-GPU Training Systems

DGX-style configurations with H100 SXM or MI300X for large model training

4-GPU Inference Servers

Balanced systems for production inference and fine-tuning workloads

PCIe Systems

Air-cooled servers with H100 PCIe, A100, or L40S for standard data center deployment

Liquid-Cooled Systems

High-density configurations for maximum performance per rack unit

Development Workstations

Single and dual-GPU systems for prototyping and experimentation

Selection Guide

GPU Type

H100/H200 for training large models, A100 for general-purpose AI, L40S or A10 for inference, MI300X for AMD-optimized workflows.

Memory

H200 offers 141GB HBM3e, H100 provides 80GB HBM3, A100 is available in 40GB and 80GB configurations.

Interconnect

NVLink provides 900GB/s GPU-to-GPU bandwidth for multi-GPU training. PCIe systems work well for inference.

Power & Cooling

An 8x H100 SXM system draws approximately 10.2kW under load. Verify your facility supports the TDP requirements.

Need help selecting the right configuration? Contact our infrastructure specialists for personalized guidance.

Common Questions

What types of GPU servers are available?

Complete systems from Dell, HPE, Supermicro, Lenovo, and Gigabyte configured with NVIDIA and AMD accelerators. Inventory spans 8-GPU training systems with H100 SXM or MI300X, 4-GPU inference servers, air-cooled PCIe systems with H100 PCIe, A100, or L40S, liquid-cooled high-density configurations, and single or dual-GPU development workstations. New and certified pre-owned units are available.

Which GPU should I choose for my workload?

H100 and H200 are suited to training large models, A100 covers general-purpose AI, L40S and A10 handle inference, and MI300X fits AMD-optimized workflows. On memory, H200 offers 141GB HBM3e, H100 provides 80GB HBM3, and A100 is available in 40GB and 80GB configurations.

Do I need NVLink or PCIe GPU servers?

NVLink provides 900GB/s GPU-to-GPU bandwidth, which matters for multi-GPU training where GPUs exchange data constantly. PCIe systems work well for inference and standard data center deployment.

How much power does an 8-GPU server need?

An 8x H100 SXM system draws approximately 10.2kW under load. Verify your facility supports the TDP requirements of any configuration before ordering, and consider liquid-cooled systems where density per rack unit is the priority.

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