LLM Inference Quantization: 4-bit and 8-bit Guide
Understand weight quantization, formats, accuracy tradeoffs, KV cache memory, and how to validate a quantized deployment.
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
Best GPU Types for AI Inference: A Practical Guide
How to evaluate GPU classes for inference without treating a hardware name as a universal recommendation.
How to Choose a GPU for LLM Inference
A repeatable selection process for model fit, context policy, concurrency, framework support, and cost control.
How Much GPU VRAM Do You Need for LLM Inference?
A memory-planning checklist for weights, quantization, context windows, KV cache, and concurrency.