| ▲ | elcomet 10 hours ago | |
Why not using a cheap LLM with thinking completely disabled ? I don't think it will be much more expensive than jev. | ||
| ▲ | nico 9 hours ago | parent | next [-] | |
I’ve tested this with some local LLMs and their accuracy is in general better than Jev/Laya, but they are super slow in comparison as well For example, a typical/stock LLM can’t really play Doom in real time, but a Jev-like model can. Just because of latency Of course, if you want the best Doom player, there are way better and faster adhoc models | ||
| ▲ | ssivark 9 hours ago | parent | prev [-] | |
LLM inference has two very different regimes of work: prefill & decode. You can think of the former roughly as processing a pre-specified prompt, and the latter as sequential processing (auto-regressive token generation) eg. "chain of thought". The latter is very important for LLMs and cannot be ignored; it deeply influences infra design, even necessitates copious amounts of high-bandwidth memory. Jev-like models can ignore the latter and therefore optimize much better for the former, consequently operating at both better cost and latency. | ||