# Gasherbrum2 - how to compare gear

## Mountaineering

I need to choose between a 229 EUR down hoody that weights 319g and one that is 269 EUR and 420g… which one will you go for?

Now, what if I tell you that the first option is 700 CUIN and second one is 800 CUIN? Wait…wait… what? What the heck is CUIN?

### Filters

Enter triangulation shopping where you simplify everything and only play around with 3 main filters:

#### 1. Price

I would argue that price is the first and the most important filter for most people unless you are a double-digit crypto millionaire, only buy Arc'teryx products and don't care about the price at all.

#### 2. Weight

Weight is the second, especially in high-altitude mountaineering where every 100grams matters a lot. You want to enjoy the mountain right? be a wild goat, not a Sherpa.

#### 3. Characteristic

CUIN is what I call the main characteristic of a product or product type (down suits, rain jackets, etc) and is needed to be able to compare apples to apples across multiple brands.

A few examples of characteristics:

• CUbic INches (CUIN) - global - a ratio between weight and volume and is used to measure down products (down jackets, sleeping bags), the bigger the better

• Resistance Value (R-value) - global - used to measure ground insulation products (air mattress, foam pads), same, the bigger the better

• Hydro-static Head (HH) - global - waterproof rating to measure water-proof and water-repellent products (tents, jackets, pants)

• base layer fabric - local (Icebreaker) - the measure of lightweight vs. mid-weight fabric type is different between Icebreaker and Ortovox

• backpacks - none - that comes in a lot of shapes (aka capacity) for different activities (hiking, alpinism) you need to do the dirty work and find out what works best for your needs

• etc

Unfortunately not all products/types have a main characteristic that is used by all gear makers, that's why I came up with 3 categories:

• global: globally available and implemented by most brands (e.g. CUIN for down products) and you can compare apples to apples

• local: specific to each brand, you can't compare products across different makers but you can compare within same brand (e.g. Icebreaker)

• none: there is no common characteristic to compare two different products of the same maker (e.g. backpacks), you need to look at multiple features to figure out what is what.

### Triangulation

With the above in mind we first need to identify the main characteristic (if any) for the products that we want to compare and mentally do calculate:

• the bang for the buck - how much value you get for each buck spent (characteristic / price), the bigger the better which means you get more value for the same money

• weighted bang - multiply the ratio above by the weight (weight * ratio), the smaller the better - which means you get less weight for the same ratio

Let's apply the triangulation to the above example and find out what to buy:

  c1 = 700
p1 = 229
w1 = 318
h1 = c1 / p1 * w1
print(h1)

c2 = 800
p2 = 269
w2 = 420
h2 = c2 / p2 * w2
print(h2)

if h1 < h2:
print("WINNER: #1")
else:
print("WINNER: #2")
972.0524017467249
1249.0706319702601
WINNER: #1


The result is #1 option but keep in mind that:

• we are missing one piece of information, down quality between 700 and 800 CUIN which translates in more warmth through trapped air

• this method is far from perfect but it is a easy way to figure out a better option

Happy shopping!