Aside from the pelican, I am sort of impressed by the fact that things are going the way in terms of really impressive small models.
Also I love how this uses N-gram embedding. I think that Longcat was the first one who used it (I submitted that submission on hackernews because I really just loved the idea of it that I understood), I am certainly more interested in local LLM models and its interesting how they are utilizing new architectures to do some really impressive optimizations!
(Do note that I created it using a free rate limited end-point that I found on the huggingface space section: https://victor-chat-with-qwen3-8-flash-next.hf.space)
Wasn't it introduced by Gemma?
I've got it (Qwen 3.8 flash next) working (sans ... MTP working on that now).
https://github.com/rdaum/eider/
~80tok/sec prefill, 12tok/sec decode, ~80GiB memory resident, the n-gram table pages from SSD.