2 ms·
> melted away in the face of massive context sizes If only. There is a huge difference between "Gives good responses/can easily spot things within N context si
by embedding-shape 4mo ago
> melted away in the face of massive context sizes
If only. There is a huge difference between "Gives good responses/can easily spot things within N context size" and "Technically works but sucks within N context size", almost all models basically become cave-people once you go beyond 50% of the "supported" context size, meaning while they may technically work with 1 million output tokens, those last 500K tokens are gonna be massively "dumber" than the first 500k tokens.
- fooster 4mo agoI don’t find that to be true?
- ballsac 4mo ago[dead]
- stalfie 4mo agoThere's at least one benchmark that attempts to measure this, but it has been running for a year plus so it's quite infrequently updated now. https://fiction.live/stories/Fiction-liveBench-Mar-25-2025/oQdzQvKHw8JyXbN87 https://fiction.live/stories/Fiction-liveBench-Mar-25-2025/o...