You are comparing an apple to an orange though.
When I open a file, the vfs-read-chunk-size relates to the range request it sends to the cloud provider to grab parts of a fie big file.
If I request a 1GB file and use a 512M vfs-read-chunk-size to start, it makes 2 API calls to get the file. If I use 128M, it does ~10. So that helps with reducing API hits. There is the overhead of using a large size so you may waste a little bandwidth, but it's very negligible.
Now, let's say i open that same 1GB file and have a 256M buffer size. If the file continues to be read sequentially, rclone keeps that 256M buffer in memory filled and say you have a light network hiccup, the reading of the file stays consistent because you have a memory buffer going on.
So in the Plex world, if you direct playing a file that is usually opened once and read sequentially so a large buffer may provide some help if there is a bit of latency in reading from your provider. The downside here is that if the file is closed, the buffer is dumped so depending on how it's being used it could be bad to have it big. If a file is constantly opened and closed, a large buffer would have a negative effect since it keeps trying to read ahead, but the player keeps closing the file.
If we move to file caching, that's the strawberry as it is different from all the other two items we talked about. If you have a requirement to keep files on disk or are writing files, that is the where the file caching layer comes into play. The different options for that are described in the file caching section.
Finally, the last option is the cache backend, which is different from the vfs cache layer (very confusing). That allows for chunked reading and it keeps chunks on local storage based on the parameters described. It also offers offline uploading as well.
My use case is plex so I just use standard vfs with no file caching and a larger buffer size since i have gigabit FIOS and no bandwidth caps so a little waste means nothing for me. I also have a 32GB server so plenty of extra memory. Unfortunately, if you set the memory too high and the server doesn't have it, it will crash like any other program or get killed off by the OS. There is no graceful way to handle out of memory conditions as those are mainly configuration issues.