I Couldn't Build a Local LLM PC for $1,300 — Budget Tiers and the VRAM Cliffs Between Them

I Couldn't Build a Local LLM PC for $1,300 — Budget Tiers and the VRAM Cliffs Between Them You want to run LLMs locally. But "which GPU should I buy?" has no decent answer. Gaming benchmarks are everywhere. "How many billion parameters fit in this much VRAM?" — almost nowhere. I started at $3,500, then cut to $2,000, $1,700, $1,300. Three breaking points appeared. Scope : New parts only, NVIDIA GPUs. Used cards (RTX 3090), AMD GPUs (RX 7900 XTX), and Apple Silicon are valid alternatives, but each introduces warranty, software compatibility, or availability trade-offs that deserve their own articles. US street pricing as of early 2026. The Premise: VRAM Decides Everything Local LLM inference speed is nothing like gaming fps. Whether the model fits entirely in VRAM creates a discontinuous jump in performance. CUDA core count and clock speed are secondary. If the full model sits in VRAM, inference is fast. If it spills to system RAM, the CPU-bound layers become the bottleneck and speed dr