sometimesanotion

Now imagine this as a hashtag generator and so a RAG search can find great context. :)

Neat! I've transitioned from wanting more from a model's one-shot answers to breaking things down and walking through the problem with cached context. This effectively means simulating most of the thinking block, but by tool usage and RAG.

I'm happily using our models from months ago to do it. If anything - even Lamarck 0.7's use of thinking blocks are a bit much. I'm using Lamarck 0.7 Fusion (my best GPQA model, though it didn't break your record and is best used where modest IFEVAL isn't a blocker) and /nothink with ValiantLab's Qwen3 models in concert.

I suspect I'll try some merges soon to give this toolchain better models, leaderboard or no leaderboard!

I've been using Esper3 8B and 14B for first-pass code review. I am quite pleased.

Have you considered fine-tuning a 1.7B or smaller model for autocomplete?

I've been thinking a lot about using small caches of embeddings for local RAG lately. Have you considered an HTTP caching proxy like Squid as a low-impact source? It would retrieve what a user is reading anyway, and what's in their field of interest. A browser extension to signal some limited ingestion when a page is bookmarked might fit a lot of use cases.

For many reasons, smart management of context windows is my top priority with AI now!