Amazon open-sources a small decision model to cut agent workflow cost and latency
The decision-model field is crowding fast; Amazon's entry confirms demand for cheaper agent workflow steps, with real-world results still unproven.
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Amazon Web Services has open-sourced a small "decision model" that lets agent workflows make routing choices at low cost.
TechCrunch reported on October 1 that AWS's Strands Labs released Strands Decider 2B, fully open-sourced, available now, and small enough to run locally. Built on the torso of Qwen3.5-2B, it does not generate text; it picks among pre-decided options and delivers a confidence score. The project began as a side effort by distinguished engineer Marc Brooker, whose September 28 blog post says it briefly topped the Jevbench ranking for its size class.
The category took off after TypeSafe's Jev. TypeSafe CEO Diogo Almeida said the current batch of imitators seems "more like ML people wanting to implement a cool architecture," and that the hard part is keeping the models actually smart.