3 PC builds for running local LLMs in 2026 – from $899 to $2,899 (VRAM first, benchmarks included)

After spending way too many hours testing local models (Llama 3, Mistral, Qwen, DeepSeek) on different hardware, I realised one thing: VRAM is everything. A 16GB card beats a faster 8GB card every time for LLM inference.

So I put together three complete PC builds that prioritise VRAM per dollar. No fluff, just parts that actually work for local AI.

Budget build – ~$899

• GPU: RTX 4060 Ti 16GB (critical: the 16GB version, not 8GB)
• CPU: Ryzen 5 5600X
• RAM: 32GB DDR4
• Runs: 7B–13B models at 30–50 tok/s, 13B–20B with Q4 quantization
• Best for: beginners, students, Ollama on a budget

Mid‑range – ~$1,599

• GPU: RTX 4070 Super 12GB
• CPU: Ryzen 7 7700X
• RAM: 64GB DDR5
• Runs: 34B models (Q4) at 20–30 tok/s, 16B models at full speed
• Best for: developers, enthusiasts, 90% of local LLM use cases

Pro build – ~$2,899

• GPU: RTX 4090 24GB
• CPU: Ryzen 9 7900X
• RAM: 96GB DDR5
• Runs: 70B models (Q4) at 15–20 tok/s, fine‑tune 7B models
• Best for: researchers, heavy fine‑tuning, running the largest open models

Why these parts?

• VRAM > raw GPU speed (consensus in the local LLM community)
• 32GB RAM is the new minimum (context eats memory)
• NVIDIA + CUDA = still the least painful path (sorry AMD fans)