Agreed not, but I think we are also moving towards a place where harnesses have code mode built in and where data swizelling and tool use is something the LLMs have to be competent at. I think that's present enough here!

And to beat Qwen3.5-4B with such a capable model is amazing, on top of so many win/draws against 9b in the more general arena.

I can definitely see there being some roles for local agents that offload shell scripting & doing some scut work. I don't know what speed to expect but like, if someone has a decent NPU or GPU and can just get a bunch of basic systems work done with a small local model that could really speed up a lot of workflows that I see day after day after day.

No, especially not for generative coding like all folks do with Claude Code - this model is not meant for that. It will produce code that mixes too many things at once, creating spaghetti code and likely having difficulty producing a compilable artifact. I suppose tool calling is also far from the frontier of class models.

However, after testing it locally, in my imagination I find this model to be a good companion for providing TAB suggestions or essentially an "ask-a-friend" that can generate example snippets of the commonly used libraries (e.g., how to create a pivot table in pandas) or bash programs (ffmpeg command to stream internet radio).

IMHO, expect max capabilities and quality of answers that frontiers models were doing back in late 2024.

definitely would not recommend using it for SWE-style tasks. But chaining a couple bash calls together to find a file? no problem