This gaming PC mod improves fps on decade-old CPUs

Bring old CPUs back to gamers' bar table.

Intel Core CPU and AMD Radeon GPU with ReBar support.

A new mod allows CPUs as old as Intel’s Core 2000 Sandy Bridge chips to enable Resizable Bar. With it comes a welcome promise of extra performance on old hardware that refuses to give up.

Resizable Bar (also called ReBar or Smart Access Memory by AMD) is a PCIe feature allowing the CPU to access the entire GPU VRAM simultaneously instead of in 256MB chunks. In many instances, this feature increases frame rates, especially on AMD Radeon and Intel Arc GPUs. Unfortunately, Resizable Bar is only supported on recent platforms, leaving older generations without its benefits.

Resizable Bar has technically been available since PCIe 3.0. But it didn’t gain popularity until 2020. I remember back in 2011 when the Core i5-2500K was the go-to CPU for gamers. I was still rocking a Core 2 Duo E5300 and a Radeon HD 3750.

ReBar enabled on an Intel Core i5-3470 CPU.

Luckily for users still running these old chips, a mod by GitHub user, xCuri0 aims to fix this inequality. The mod tweaks the UEFI firmware on older motherboards to add Resizable Bar support. Note that you may need some IT knowledge to follow the guide, but the YouTube video below is pretty helpful. Also, not all motherboards are compatible with this mod.

It’s time to go snag one of those old Dell PCs and transform it into a budget gaming machine. After all, you can gain up to 24% on Radeon GPUs and even more with Intel Arc. Combine this with NvStrapsReBar to unlock Resizable Bar on Nvidia’s GTX 16 and RTX 20 graphics cards, and the sky’s the limit.

Though, as usual, not all games will benefit. In fact, some might even potentially lose performance. Depending on how old and powerful your CPU is, it may bottleneck the GPU. Brands also usually create individual Resizable Bar profiles for each game. Without these tailor-made settings, it’ll be trial and error on your part.

Interested? The steps for installing this mod are found on the GitHub post.