That's a tricky number. Does it run on an 80GB GPU, does it auto-shave some parameters to fit in 79.99GB like any articifially "intelligent" piece of code would do, or does it give up like an unintelligent piece of code?
There's no concept of 'dedicated GPU memory' as per conventional amd64 arch machines.
Are you asking if the framework automatically quantizes/prunes the model on the fly?
Or are you suggesting the LLM itself should realize it's too big to run, and prune/quantize itself? Your references to "intelligent" almost leads me to the conclusion that you think the LLM should prune itself. Not only is this a chicken and egg problem, but LLMs are statistical models, they aren't inherently self bootstraping.
I hate software that complains (about dependencies, resources) when you try to run it and I think that should be one of the first use cases for LLMs to get L5 autonomous software installation and execution.