All Hardware for Running LLMs Locally
Browse 56 GPUs and 33 devices — MacBooks, desktops, AI boxes, and more.
Choosing Hardware for Local AI
VRAM is the most important specification for running LLMs locally. Discrete GPUs offer dedicated VRAM, while Apple Silicon Macs share unified memory between CPU and GPU. AI development kits like NVIDIA Jetson provide optimized inference on the edge. Pick your hardware below to see which models you can run.
Discrete GPUs
View all 56 →NVIDIA, AMD, and Intel GPUs — VRAM is the key spec for local LLMs
NVIDIA GeForce RTX 4090
NVIDIA · Ada Lovelace
NVIDIA GeForce RTX 5090
NVIDIA · Blackwell
NVIDIA GeForce RTX 5080
NVIDIA · Blackwell
NVIDIA GeForce RTX 5070 Ti
NVIDIA · Blackwell
NVIDIA GeForce RTX 4080 SUPER
NVIDIA · Ada Lovelace
NVIDIA GeForce RTX 5070
NVIDIA · Blackwell
Laptops
View all 14 →MacBooks and other laptops with unified or dedicated GPU memory
MacBook Air 13" M3 (16 GB)
Apple · M3 · Laptop
MacBook Air 13" M3 (24 GB)
Apple · M3 · Laptop
MacBook Air 13" M3 (8 GB)
Apple · M3 · Laptop
MacBook Air 13" M4 (16 GB)
Apple · M4 · Laptop
MacBook Air 13" M4 (24 GB)
Apple · M4 · Laptop
MacBook Air 15" M4 (16 GB)
Apple · M4 · Laptop
Desktops & Mini PCs
View all 9 →Mac Studio, Mac Mini, custom PCs, and workstations with maximum memory
Mac Mini M4 (16 GB)
Apple · M4 · Mini PC
Mac Mini M4 (32 GB)
Apple · M4 · Mini PC
Mac Mini M4 Pro (24 GB)
Apple · M4 Pro · Mini PC
Mac Mini M4 Pro (48 GB)
Apple · M4 Pro · Mini PC
Mac Pro M2 Ultra (192 GB)
Apple · M2 Ultra · Desktop
Mac Studio M2 Ultra (192 GB)
Apple · M2 Ultra · Desktop
AI Development Kits
View all 3 →NVIDIA Jetson, dedicated inference hardware, and edge AI devices
Browse by VRAM
Find the best models for your VRAM tier
Entry-level for LLMs (RTX 4060, RX 7600, Apple M-series base) — 7B models at Q4, small models at Q8
Mid-range (RTX 3060, RTX 4070, RTX 5070) — 7-13B models at Q4-Q6
Upper mid-range (RTX 4080, RTX 5070 Ti, Arc A770, Apple M4 16GB) — 13B models, some 30B at Q4
Enthusiast (RTX 3090, RTX 4090, RX 7900 XTX) — 30B+ models at Q4-Q6, 70B at aggressive quant