For dl.google.com, the first user of groupcache, it sounds like the Go runtime was working with relatively few, relatively large chunks of memory (think 2MB chunks of a Chrome binary). Since that doesn't have so many pointer-containing objects, just big chunks of inert data that don't need scanned, it's easyish. On the other hand, something like throwaway2424's case could be a GC stress test--many gigs of RAM holding a network of small, pointer-filled objects.
Really, the tl;dr may be to prototype/measure if you need to know how a GC will do. Assumptions are easy; data is hard.
And as for measuring... it's not cheap (developer time wise) to build a realistic enough model of your application and put realistic enough loads on it for long periods of time to test out each of your hypotheses (and GC theories do require long periods of load). So you have to narrow the space of choices informed by past experiences and sometimes by gathering semi-reliable folk lore. I'm currently engaging in the latter activity :-)
And yes, unfair to ask someone to test every guess they have. But if you do want to know a bit more about what effect GC and Go would have, experimenting with toy programs isn't a bad way to get a feel.
Atom also says 1.0's was more conservative, but, as Brad also said, still didn't scan "objects such as []byte" (meaning all plain-old-data arrays? who knows). The Go 1.1 Release Notes mention the collector becoming more precise, which was a particular issue on 32-bit because big heaps could span a lot of the address space.
You can see the GC source itself doing some per-type switching: https://code.google.com/p/go/source/browse/src/pkg/runtime/m...
At some point, this sort of discussion probably gets you less useful info per unit effort than just playing with a Go distribution, trying out whatever toy programs you find interesting.