Comment by entrope
4 hours ago
What hardware and inference engine do you use? On my Radeon R9700, at least with llama.cpp and some others, the GPU provides as many tok/sec with a single stream as with concurrent ones, so it's just as fast and supports longer contexts to swap contexts to RAM on turn boundaries.
I've experienced the same. Are you saying you're using different context sizes with parallel invocations or just that it's possible to have longer contexts? I've been setting my config to ensure I don't blow out context server side but have not tried to manage it client side.