ENGINEERING GUIDES & BENCHMARKS4 Technical Guides

High-Intent LLM Hardware & Memory Guides

In-depth architectural breakdowns, memory bandwidth analysis, KV cache formulas, and unbiased hardware comparisons for developers self-hosting open-weights AI.

Hardware7 min read • 2026-10-15

RTX 5090 (32GB) vs. Dual RTX 3090 (48GB) for Local LLMs — 2026 Buying Guide

Speed vs. VRAM capacity: Which $2,000 GPU setup is superior for running 70B, 35B MoE, and long-context local AI?

#RTX 5090#RTX 3090#70B Models#Hardware Benchmarks#Dual GPU

By Alex VanceRead Full Guide →

Models6 min read • 2026-10-18

Best GPUs for Running 70B LLMs Locally in 2026 (VRAM, Speed & Quantization)

Complete hardware matrix for running Llama 3.3 70B, Qwen 2.5 70B, and DeepSeek distilled 70B locally.

#70B Models#Llama 3.3#VRAM Sizing#vLLM#Ollama

By Alex VanceRead Full Guide →

VRAM & Memory5 min read • 2026-10-20

How Much VRAM Does KV Cache Really Use? The Exact Formula & Sizing Guide

Demystifying token memory footprint: How context length, attention architectures, and quantization impact GPU memory.

#KV Cache#Memory Math#GQA#MLA#Context Window

By Alex VanceRead Full Guide →

Hardware6 min read • 2026-10-21

Apple Mac Mini M4 Pro (64GB) vs. NVIDIA RTX 4090 (24GB) for Local AI

Can Apple Silicon Unified Memory beat NVIDIA CUDA Tensor Cores for local LLM inference?

#Apple Silicon#M4 Pro#RTX 4090#Metal vs CUDA#Mac Mini

By Alex VanceRead Full Guide →