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TechPulse take: AWS Strands Labs has introduced Strands Decider 2B, a specialized decision model derived from Qwen3.5-2B that outputs structured choices or probabilities without generating text. By replacing the standard language modeling head with a pointer mechanism, this architecture achieves sub-120ms inference times on consumer hardware for tasks like tool selection and agent routing. The release marks a significant step toward efficient local deployment of System One models, though it remains unsuitable for complex reasoning or generative tasks.

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AWS Strands Labs Releases Strands Decider 2B: An Open Source Decision Model That Picks Options in About 115 ms

MarkTechPost2 octombrie 20264 min de cititArticolul și perspectiva sunt în engleză.

AWS's Strands Agents team released Strands Decider 2B, an Apache-2.0 decision model built on Qwen3.5-2B-Base. It returns choices, yes/no probabilities and scores with calibrated confidence in one forward pass, never text. It runs at a 115 ms median on an RTX 3090 and scores 0.723 on the JevBench public set, which makes it a fast local option for routing, tool selection and guardrails in AI agents. The post AWS Strands Labs Releases Strands Decider 2B: An Open Source Decision Model That Picks Options in About 115 ms appeared first on MarkTechPost.

AWS Strands Labs releases Strands Decider 2B, an open source decision model. It does not generate text. It reads a state and typed questions, then returns a choice, a yes/no probability, or a score with a calibrated confidence. The model has 1.9 billion parameters and runs locally on a CPU, a consumer GPU, or an Apple silicon Mac. Is it deployable? Yes, for local and self-hosted use. Weights are on Hugging Face under Apache-2.0, and…

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