I ran a couple needle-in-a-haystack type queries with just a 32k context length, and was very much not impressed. It often failed to find facts buried in the middle of the prompt, that were stated almost identically to the question being asked.

It's cool that these models are getting such long contexts, but performance definitely degrades the longer the context gets and I haven't seen this characterized or quantified very well anywhere.