Game developer created a scene of his dog with 10 billion polygons in Unreal Engine 5
Unreal Engine 5 passes the test with stellar gradesBy Joao Silva 17 comments
What just happened? Unreal Engine 5 early access just launched and developers are already testing its limits, or at least trying to find them. Soon after release, a game developer loaded a 10 million polygon dog into the engine and replicated it 1,000 times, resulting in a 10 billion polygon scene that the engine had no issue handling.
To make this experiment, Gary Freeman, lead developer of Ionized Games, started by taking 122 photos of his dog sleeping on a bed. Then, he threw all the photos into Reality Capture, created 3D models out of them, and exported the generated assets with a 4K texture into Unreal Engine 5.
Once the 10 million polygon model was loaded into Unreal Engine 5, the developer used Nanite meshes to make 1000 instances of the model, creating a 10 billion polygon scene. As seen in the video, the engine did not struggle, running the scene at 60FPS at all times.
I was able to load a 10 million polygon photoscan of Ziggy in the @UnrealEngine. Using #UE5's Nanite meshes I was able to load 1000 instances of it at 60fps before I got bored. That's 10 billion polygons and it didn't even blink. It could have handled a lot more than this. pic.twitter.com/IMRnQIjFSx--- Sgt. Gary Freeman of the UNC (@IonizedGames) May 26, 2021
It's worth noting that Gary's system isn't exactly a toaster. He detailed his system features a Ryzen 7 5800X, an EVGA RTX 3070 XC, and 32GB of RAM. He plans to create a similar scene using a GTX 750, which he believes will be enough to handle it.
Despite the apparent complexity of the scene, the system wasn't close to full load. The developer also claimed that "any GTX 10 series card or newer is gonna see some mind blowing enhancements."
The developer was also asked about the asset's size, to which he responded it was 1.5GB. Gary added that games will "certainly get bigger," but the final size of a game is still the developer's responsibility. If he had spent some more time around the asset, he believes he could have reduced its size to 50-100MB without sacrificing its quality.