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Analyzed from 329 words in the discussion.
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#models#agentic#coding#model#smaller#using#tool#workflows#lfm#tiny
Discussion Sentiment
Analyzed from 329 words in the discussion.
Trending Topics
Discussion (13 Comments)Read Original on HackerNews
> We recommend using it for agentic workloads, tool use, data extraction, RAG, and long-context workflows. It is not recommended for agentic coding and knowledge-heavy tasks.
It has to query the tool service, invoke tools, synthesize results, or request new tools. Nothing really complex.
New tool requests from it are plain english and go into a separate pipeline using more appropriate models. It doesnβt have to write anything itself.
Why is Qwen3.5 2B not in the table?
Note how they're much smaller than all other models in the comparison yet match or exceed them. This is for 2.6B params, but they have models as small as 230M. Nobody else designs models that small.
There's a strong incentive to cherry pick in self-reported comparisons. If there is a model that's better, it gets left out. Have you seen Nanbeige4.2-3B or Ling-3.0-tiny?
> Nobody else designs models that small.
There are people building even smaller models.