According to MarkTechPost, the Strands Agents team at AWS has released Strands Decider 2B, a new open source decision model based on Qwen3.5-2B-Base and licensed under Apache-2.0. The system is designed to output choices, yes/no probabilities, and calibrated confidence scores directly in a single forward pass without generating conversational text. Testing shows a median execution time of approximately 115 milliseconds on an RTX 3090 graphics card, alongside a score of 0.723 on the JevBench public benchmark set.
Speed and Local Deployment for AI Agents
Decision models like Strands Decider 2B address a specific bottleneck in modern AI agent architectures. Traditional large language models generate text token by token, which can introduce latency when agents need to perform simple routing, select tools, or enforce guardrails. By bypassing text generation entirely and returning structured probabilities and scores in one forward pass, developers can integrate fast, local decision-making steps directly into automated pipelines using consumer-grade hardware.
Unknowns and Hardware Requirements
Despite the release of the model weights and performance benchmarks, the announcement did not specify broader deployment recommendations beyond the RTX 3090 test environment. It remains unclear how the model performs on alternative consumer or enterprise hardware, nor are there details on future model sizes or integration paths with other AWS services. Developers will need to test the model locally to determine how well it fits into specific production workflows.
Strands Decider 2B is available now for developers looking to test open source decision routing for local AI workloads.
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