B300 for AI Model Labs: What Sustained Training Looks Like on Dedicated Bare Metal

AI model labs running sustained pretraining campaigns have infrastructure requirements that shared cloud was not built for. Here's what dedicated B300 bare metal delivers, and what a 12-month compute commitment actually looks like in practice.

Why the B300 Is the GPU Serious AI Teams Are Planning Around Right Now

The B300 is in mass production and GB300 shipments are projected to grow 129% in 2026. Here's what the architecture delivers technically, and why dedicated bare metal is the right way to access that capacity.

B300 for Production Inference: What Changes When You Move Beyond Training

What the B300's memory capacity, FP4 compute, and latency profile mean for teams serving LLMs at scale, on dedicated bare metal infrastructure.

ISV Certification and GPU Infrastructure: Why It Matters More Than You Think for Media Workloads

What ISV certification actually means for GPU infrastructure — and why it matters for broadcast, VFX, and media SaaS pipelines running professional software at scale."

From H100 to B300: What Changes for Teams Already Running Serious AI Workloads

Running H100 in production and evaluating B300? A clear breakdown of where each makes sense, and why bare metal infrastructure matters for both.

B300 on Bare Metal: What the Architecture Means for LLM Training at Scale

The B300 delivers 3.6x more GPU memory and a generational leap in FP4 compute over the H100. Here's what that means for LLM training at scale, and why bare metal infrastructure makes the difference.