The Cheapest Ways to 24 GB or More of VRAM, by List Price

November 7, 2026 · 5 min read · LocalAITools

Twenty four gigabytes is the memory line where local AI gets serious: 32B models at INT4 sit comfortably, 70B models run with some offload, and image models stop arguing about batch size. So what is the cheapest way over that line, using only list prices actually published in this directory? 66 GPUs qualify with a US list price attached.

The answer, on launch list prices, is the RTX 3090 class and its successors: the previous generation flagship still anchors the value end, while the RTX 5090 at 32 GB costs more per card but less per gigabyte than several 24 GB options once you divide it out. The cost per GB column is the one to read. It punishes small memory and rewards the big consumer cards, and it is why a used market 3090 and a new 5090 keep showing up in build threads.

GPUs with 24 GB or more and a US list price

The cheapest entries, priced

Two cautions. These are list prices, mostly manufacturer MSRP, and RTX 50 series street prices currently run above them, so the ranking at a real store can shuffle. And a workstation card like the RTX PRO 6000 at 96 GB is not in this table at all, because it is sold on quote; the absence is about pricing practice, not value. For the store side of the hunt, the US price guide collects every listed price in one place.

Our take: if the budget is tight and the workload is inference, the cheapest 24 GB list price wins. If you will train or run agents all day, cost per GB plus power draw matters more, and the 32 GB tier earns its premium.