Items are everything in Risk of Rain 2. They boost your damage, provide various buffs, and in rare cases can instant-kill certain enemies. The latter is the case with the Old Guillotine, which will help you wipe out Elite monsters quickly. However, this item doesn’t stack the way you may expect, since its in-game description is slightly misleading. Here’s what you need to know about how the Old Guillotine stacks and what you can do to maximize its effects.
Risk of Rain 2 Old Guillotine | Effects and Stacking
The Old Guillotine in Risk of Rain 2 is an uncommon (green) item that instantly kills Elite monsters below a set health. The lower health limit starts at 13 percent and increases by 13 percent per stack. However, the stack curve is hyperbolic, providing lower-than-expected values with each item obtained.
If that sounds confusing to you, you’re not alone. In a nutshell, the Old Guillotine stack curve is not linear; it doesn’t simply increase the lower limit of health by 13 percent each time. Instead, it applies a formula to determine the lower health limit: 1-1(1+0.13*x), where x is the stack count.
To make matters more complicated, this item doesn’t kill Elites when they reach that health threshold. Instead, it instantly kills them once they’re hit while under that threshold. As an example with a single stack, getting an Elite to 13% health won’t instantly kill them; you’d need to hit them one more time.
In other words, stacking Old Guillotines is less effective than you’d think. Two of them will instant-kill Elites under 20.6 percent health, while eight of them will one-hit enemies under 51 percent health. Because of the hyperbolic curve, you’ll never be able to reach 100 percent, no matter how many you stack.
Still, this is a very useful item, especially when running the Artifact of Honor, which makes all enemies spawn as Elites. If you haven’t unlocked it yet, you can get the Old Guillotine by completing the Cut Down challenge. This simply requires you to kill 500 Elite Monsters, which will happen gradually over time.
