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Blog · Hardware Building · September 20, 2026 · 8 min read

Building a Dual-GPU 48GB Rig for 70B Models: A Practical Guide

A two-GPU workstation for large AI models

One 48 GB workstation card costs as much as a used car down payment. Two 24 GB consumer cards cost a fraction of that and, for inference, behave like one big 48 GB memory pool. This is the most popular path to running 70B-class models at home — here is how it works and what to honestly expect.

How two cards become one pool

Inference frameworks (llama.cpp, Ollama, vLLM) split the model’s layers across the installed GPUs — a strategy called layer splitting. Half the layers live on card one, half on card two; tokens flow through both in sequence. Key properties:

The shopping list

Honest expectations

SetupFeels like
2× RTX 3090, 70B at Q4Roughly 8–12 t/s — slow-reading pace, genuinely usable
2× RTX 3090, 32B at Q4Comfortable reading pace and lots of context headroom
Same rig, MoE modelsNoticeably snappier — active parameters are small

Set your expectations with the speed formula in our tokens-per-second guide: capacity doubled, bandwidth did not. If the goal is 70B quality at interactive speed on a budget, this rig delivers — and the electricity bill (see the crossover panel — both cards’ TDPs count) is the price of admission.