Strands Agents announced Strands Decider 2B, a small, open-source decision model optimized for fast experimentation and local development. It is a 2 billion parameter model that can return answers in tens of milliseconds, suitable for running on a local CPU or GPU.
Key facts
| Fact | Detail | The source says |
|---|---|---|
| Model Size | 2 billion parameters | “It’s a 2 billion parameter model, suitable for running on a local CPU or GPU” |
| Performance | 3rd in accuracy and 1st in calibration | “strands-decider-2b performs well on accuracy and calibration ( 3rd of 33 in the 2B class, and 1st of 30 excluding the just-over-2B models )” |
| Latency | tens of milliseconds | “can return answers to meaningful questions in tens of milliseconds” |
What happened
Strands Agents introduced Strands Decider 2B, a 2 billion parameter decision model optimized for fast experimentation and local development. Unlike large language models (LLMs), Strands Decider 2B is designed to pick between sets of options and assign simple numerical scores, making it faster and more capable at a given size. The model is built on a pre-trained LLM torso (Qwen3.5-2B) with a pointer head that scores answers offered by the torso for each option. It is available as open source on GitHub, with weights on Hugging Face, and includes all training data and scripts. Strands Decider 2B performs well in accuracy and calibration, ranking third in the 2B class and first excluding models just over 2 billion parameters.
Source: strandsagents.com