A100 40GB vs A100 80GB: What's the Difference?
Why the memory capacity in an A100 configuration changes model fit, context headroom, and concurrency planning.
Hostnot GPU engineering
GPU, AI, and infrastructure guides
Practical notes for choosing hardware, connecting safely, and building dependable AI workloads. Every guide reflects what the platform actually does today.
Showing 1–4 of 4 published articles
NVIDIA H100 vs H200: Which GPU Should You Choose?
A workload-first framework for choosing between accelerator classes with different memory and platform characteristics.
RTX 5090 vs NVIDIA A100 for AI Workloads
Compare workload fit, memory planning, software validation, and operational tradeoffs without relying on synthetic benchmark claims.
RTX 5090 for AI: VRAM, Inference and Workload Guide
A practical way to evaluate a high-memory consumer GPU for local development, inference, and batch work.