Want to run AI large models locally, but online opinions are all over the place. Some say you need an RTX 4090, others say 8GB of VRAM is enough, and some claim a MacBook Air with 16GB will do the trick. So what configuration is actually sufficient? This article uses real data to tell you: what hardware different models require, how to build a setup for different budgets, and whether your computer can handle it.

💡 What You Will Learn

Want to run AI large models locally, but online opinions are all over the place. Some say you need an RTX 4090, others say 8GB of VRAM is enough, and some claim a MacBook Air with 16GB will do the tri

📜 Table of Contents

• Memory Requirements (4-bit Q4_K_M)
• Bandwidth = Speed
• Budget Builds
• Mac Users
• Bottom Line

Local LLM Hardware Guide 2026

Memory Requirements (4-bit Q4_K_M)

7B: 4GB | 8B: 4.5GB | 13B: 7GB | 34B: 18GB | 70B: 37GB

Bandwidth = Speed

RTX 4060 (272 GB/s): 30 tok/s for 7B Q4 RTX 4090 (1008 GB/s): 110 tok/s Mac M5 Max (614 GB/s): 68 tok/s DDR5-6000 (~90 GB/s): 10 tok/s

Budget Builds

$500-1000: RTX 4060 8GB + 32GB DDR5 8B Q4 (25-35 tok/s), 13B Q4 hybrid n$1500-2500: RTX 5070 Ti 16GB + 64GB DDR5 34B Q4 (15-25 tok/s), 70B Q3 hybrid Sweet spot for local AI. $3000+: RTX 5090 24GB + 128GB DDR5 70B Q4 on GPU, 130B hybrid

Mac Users

M5 Max 48GB: 70B Q4 at 60 tok/s M4 Pro 24-48GB: 13B Q4 M3 Air 16-24GB: 8B Q4

Bottom Line

Your existing computer can probably run 8B models. Install Ollama and try first.