2026 local-LLM PCs that do not waste the budget: how to pick a GPU

Bottom line: For running models, CPU bragging rights and RGB coolers are second. VRAM (GB) and memory bandwidth (GB/s) set token speed. Save a million won, buy 16GB or less, and you will not even load a 32B model.

This is a shopping map. It is not a list of cards sitting in this lab. Our desk is an M1 Max 64GB, M2 Max 96GB, and RTX 4080 16GB (plus planned 128GB boxes). We do not pretend we timed a 4090 or an H100 here.

1. Why a normal gaming quote falls over

Gaming cares about a new CPU (i9, Ryzen 7) and fast RAM. Local LLM inference leans more than 90% on GPU VRAM size and bandwidth.

Spend ₩5 million on new parts and still put in a 16GB card, and the moment a 32B Q4_K_M lands you hit OOM and the box stops.

2. Minimum VRAM by parameter size

Model size	Quant	Min VRAM	Typical GPU mix	Tokens / sec (TPS)
7B ~ 8B (Llama 3, Qwen)	Q8 / FP16	8GB ~ 12GB	RTX 4060 Ti 16GB, RTX 4070	60 ~ 90 TPS
14B ~ 32B (Qwen Coder, DeepSeek)	Q4_K_M	20GB ~ 24GB	RTX 4090 24GB, RTX 3090 24GB	35 ~ 50 TPS
70B (Llama 3.3, Qwen 72B)	Q4_K_M	42GB ~ 48GB	Dual RTX 3090 24GB or Mac 64G+	18 ~ 28 TPS
671B MoE (DeepSeek-V3/R1)	FP8 / Q4	350GB+	Cloud node (RunPod H100 cluster)	40 ~ 60 TPS

Those TPS bands are market ballparks from the original Korean table, not timings from this lab. We do not fill empty cells with a 4090 or H100 we do not own.

3. 2026 builds by budget

Build 1: under ₩1.5 million, used RTX 3090

GPU: used NVIDIA GeForce RTX 3090 24GB (still the cheapest way to 24GB VRAM)
CPU: AMD Ryzen 5 7600
RAM: DDR5 32GB (16GB × 2)
PSU: 850W 80PLUS Gold (for 3090 peaks)
Use: 32B coding models and DeepSeek Distill 14B without drama

Build 2: ~₩4 million, pro workstation

GPU: NVIDIA GeForce RTX 4090 24GB (1,008 GB/s)
CPU: AMD Ryzen 9 7950X / 9950X
RAM: DDR5 64GB
PSU: 1000W–1200W Platinum
Use: vLLM serving, local embedding pipelines

Build 3: quiet, large-weight (Apple Mac Studio)

Box: Mac Studio M3/M4 Max (64GB or 128GB unified)
Pros: You can treat 96GB+ as VRAM-like capacity and keep a 70B running without fan roar.
Cons: Some CUDA-only libraries will not play, and token speed is often about half a 4090.

4. Checklist before you buy

Is the model you actually run 14B and under, or 32B and up?
In 2026, 24GB VRAM is the floor for someone who develops against local models.
For 70B and larger, stretching a PC is usually worse value than renting a cloud GPU (RunPod, Vast.ai) at about $0.4/hour.