been messing with a tiny 0.6B model, trying to make it

Used Jev to pick the best of several attempts from a 0.6B model for tool calling, improving dev-set accuracy from 61% to 73% for under $0.50.

The original post

been messing with a tiny 0.6B model, trying to make it better at tool calling without paying for labels it answers each prompt a few times, have Jev pick the right attempt, train on those 61% → 73% on my dev set. spent less than $0.5 cents still early tho :) @typesafeai

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Numbers are a snapshot taken from X when the case was added to the library (schema v1, collected 2026-09-19); they will not match today.

Where this case fits

Filed under agents & workflows, classification & data extraction. In the pattern Jev is built for, the model answers a bounded question per step — and ordinary code acts on the answer, because the answer is already a value rather than a paragraph. Other posts in the same family are on the agents & workflows page.

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Last updated: 2026-09-22 · sources & corrections · every card links to its author's original post