Journal
Stories for builders
of the GPU future
Research-grade buying guides, benchmarks, and playbooks for teams building on accelerated compute.
Start with the question you are trying to answer
The blog is organized around the practical queries buyers and operators search before they commit to hardware: GPU comparisons, LLM VRAM sizing, rack power planning, financing, cooling, freight, and cluster design.
How much VRAM do I need?
Practical inference sizing for 7B to 405B models, including KV cache and context-window planning.
Read guideHow much power will this rack need?
Plan circuits, PDUs, and rack density before your H100, H200, or B200 deployment arrives.
Read guideShould we finance the hardware?
Use a clearer capex vs opex framework for GPU servers, racks, and hybrid cloud strategies.
Read guideDo we really need InfiniBand?
Network design guidance for distributed training, fine-tuning clusters, and scale-out planning.
Read guideLatest

Comparing Cloud GPU Providers in 2026
How to compare the exact GPU, region, capacity, billing terms, and cost per result across cloud providers.

QLoRA vs LoRA: Complete Fine-Tuning Guide for LLMs
Learn when to use LoRA vs QLoRA for LLM fine-tuning. Includes memory requirements, GPU recommendations, code examples, and cost analysis for fine-tuning Llama on different hardware.

H100 PCIe vs SXM: When Does Form Factor Matter?
The server compatibility and interconnect questions that matter when choosing H100 PCIe or SXM.

H100 vs H200: Choosing a Hopper Server
Compare H100 and H200 memory, bandwidth, server fit, and the details needed for current quotes.

Datacenter GPU Procurement Checklist (2026): Avoid Delays and Surprises
The product, facility, warranty, and delivery details to confirm when buying a datacenter GPU server.

H100 vs A100: An Upgrade Decision
How to compare H100 and A100 systems using your workload, server compatibility, and current quotes.

H100 vs MI300X: Hardware and Software Buying Guide
Compare H100 and MI300X memory, CUDA and ROCm requirements, OEM systems, and quote terms.

H200 vs B200: Which NVIDIA GPU is Right for Your AI Workload?
Compare H200 and B200 memory, interconnect, software, cooling, and current quote requirements.

How to Size a GPU Cluster for LLM Training
Size a training cluster from measured model memory, single-node benchmarks, network scaling, and OEM system requirements.

AMD MI300X for Generative AI: Where It Fits
MI300X memory, ROCm software fit, OEM server requirements, and how to compare current quotes.

Shipping GPU Servers and Racks
The packaging, site, delivery, and insurance details needed for a reliable GPU hardware freight quote.